Structural Analysis of Natural Products

Hollow Cathode Discharge Ionization Mass Spectrometry: Detection, Quantification and Gas Phase Ion-Molecule Reactions of Explosives and Related Compounds

Mass spectrometry (MS) has become an essential analytical method in every sector of science and technology. Because of its unique ability to provide direct molecular structure information on analytes, an extra method is rarely required. This review describes fabrication of a variable-pressure hollow cathode discharge (HCD) ion source for MS in detection, quantification and investigation of gas-phase ion molecule reactions of explosives and related compounds using air as a carrier gas. The HCD ion source has been designed in such a way that by altering the ion source pressures, the system can generate both HCD and conventional GD. This design enables for the selective detection and quantification of explosives at trace to ultra-trace levels. The pressure-dependent HCD ion source has also been used to investigate ion-molecule reactions in the gas phase of explosives and related compounds. The mechanism of ion formation in explosive reactions is also discussed.

Comprehensive mass spectrometric metabolomic profiling of a chemically diverse collection of plants of the Celastraceae family

Natural products exhibit interesting structural features and significant biological activities. The discovery of new bioactive molecules is a complex process that requires high-quality metabolite profiling data to properly target the isolation of compounds of interest and enable their complete structural characterization. The same metabolite profiling data can also be used to better understand chemotaxonomic links between species. This Data Descriptor details a dataset resulting from the untargeted liquid chromatography-mass spectrometry metabolite profiling of 76 natural extracts of the Celastraceae family. The spectral annotation results and related chemical and taxonomic metadata are shared, along with proposed examples of data reuse. This data can be further studied by researchers exploring the chemical diversity of natural products. This can serve as a reference sample set for deep metabolome investigation of this chemically rich plant family.

Advances in Natural Product Extraction Techniques, Electrospun Fiber Fabrication, and the Integration of Experimental Design: A Comprehensive Review

The present review explores the growing interest in the techniques employed for extracting natural products. It emphasizes the limitations of conventional extraction methods and introduces superior non-conventional alternatives, particularly ultrasound-assisted extraction. Characterization and quantification of bioactive constituents through chromatography coupled with spectroscopy are recommended, while the importance of method development and validation for biomarker quantification is underscored. At present, electrospun fibers provide a versatile platform for incorporating bioactive extracts and have extensive potential in diverse fields due to their unique structural and functional characteristics. Thus, the review also highlights the fabrication of electrospun fibers containing bioactive extracts. The preparation of biologically active extracts under optimal conditions, including the selection of safe solvents and cost-effective equipment, holds promising potential in the pharmaceutical, food, and cosmetic industries. Integration of experimental design into extraction procedures and formulation development is essential for the efficient production of health products. The review explores potential applications of encapsulating natural product extracts in electrospun fibers, such as wound healing, antibacterial activity, and antioxidant properties, while acknowledging the need for further exploration and optimization in this field. The findings discussed in this review are anticipated to serve as a valuable resource for the processing industry, enabling the utilization of affordable and environmentally friendly, natural, and raw materials.

Infection metallomics for critical care in the post-COVID era

Infection metallomics is a mass spectrometry (MS) platform we established based on the central concept that microbial metallophores are specific, sensitive, noninvasive, and promising biomarkers of invasive infectious diseases. Here we review the in vitro, in vivo, and clinical applications of metallophores from historical and functional perspectives, and identify under-studied and emerging application areas with high diagnostic potential for the post-COVID era. MS with isotope data filtering is fundamental to infection metallomics; it has been used to study the interplay between "frenemies" in hosts and to monitor the dynamic response of the microbiome to antibiotic and antimycotic therapies. During infection in critically ill patients, the hostile environment of the host's body activates secondary bacterial, mycobacterial, and fungal metabolism, leading to the production of metallophores that increase the pathogen's chance of survival in the host. MS can reveal the structures, stability, and threshold concentrations of these metal-containing microbial biomarkers of infection in humans and model organisms, and can discriminate invasive disease from benign colonization based on well-defined thresholds distinguishing proliferation from the colonization steady state.

Quantitation of small molecules from liquid chromatography-mass spectrometric accurate mass datasets using CycloBranch

Gaussian and exponentially modified Gaussian functions were incorporated into integrating algorithms used by an open-source, cross-platform tool called CycloBranch. The quantitation is demonstrated on bacterial pyoverdines separated by fine isotope features. Using our algorithm, we can separate the m/z values 694.25802 and 694.26731 (a 0.009 Da difference), where the former belongs to the most intense peak of pyoverdine D (PvdD), and the latter to the second most intense peak of pyoverdine E (PvdE) in the respective isotopic clusters of [M + Fe-H]²⁺ ions. The areas under chromatographic curves of standards were analyzed for the limit of detection (LOD), limit of quantitation (LOQ), and regression coefficient calculations. The quantitative module returned a LOD and LOQ of 1.4 and 4.3 ng/mL, respectively, for both PvdD and PvdE in human urine. If present and detected in mass spectra, the intensities of user-defined [M + H]⁺, [M + Na]⁺, [M + K]⁺, [M + Fe-H]²⁺, or other ion types, can be accumulated and used for quantitation. The quantitation result is returned by CycloBranch in seconds or minutes, contrary to an hours-long manual approach, prone to user-born errors originating from necessary copying among various software environments. Native Bruker, Waters, Thermo, txt, mgf, mzML, and mzXML data formats are supported in CycloBranch, which is freely available at https://ms.biomed.cas.cz/cyclobranch.

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.

Reassessing the molecular structures of some previously isolated abietane diterpenoids with a naphthalene moiety and the structure-activity relationship (SAR) of quinone diterpenoids

Crystals of previously described para-naphthoquinone abietane diterpenoids 12,16-dideoxy-aegyptinone B and 12-deoxy-salvipisone were obtained from Zhumeria majdae Rech.f. & Wendelbo. However, single-crystal X-ray diffraction analysis followed by reinterpretation of their NMR data revealed that their structures require revision, and they should be revised to the two ortho-naphthoquinones, zhumerianone C and aethiopinone, respectively. Interestingly, a further search through literature revealed that there were more of such cases, in which differentiation between the ortho-/para-orientation had not been carried out correctly in the structure elucidation of naphthalene containing abietane diterpenoids. Therefore, in the current study, we pointed out some 1D and 2D NMR generalizations that would help the unambiguous deduction of the ortho-/para-orientation of naphthalene containing abietanes and revised the structure of some previously described compounds accordingly. Based on these generalizations, structures of sibiriquinones A and B, sahandinone, and sahandone were revised to the known structures 1,2-didehydromiltirone, miltirone, saprorthoquinone, and sahandone B, respectivelyand tebesinone B, arucadiol, and sahandol II were revised to three undescribed structures. It was also proposed that structures of palmitoyl arucadiol and compounds with the salvifolane skeleton need revision. Furthermore, these structure revisions shed light on the structure-activity relationship of the quinone diterpenoids, approving that the ortho-quinone is the critical structural component for cytotoxicity in these compounds.

Overview of Bioactive Fungal Secondary Metabolites: Cytotoxic and Antimicrobial Compounds

Microorganisms are known as important sources of natural compounds that have been studied and applied for different purposes in distinct areas. Specifically, in the pharmaceutical area, fungi have been explored mainly as sources of antibiotics, antiviral, anti-inflammatory, enzyme inhibitors, hypercholesteremic, antineoplastic/antitumor, immunomodulators, and immunosuppressants agents. However, historically, the high demand for new antimicrobial and antitumor agents has not been sufficiently attended by the drug discovery process, highlighting the relevance of intensifying studies to reach sustainable employment of the huge world biodiversity, including the microorganisms. Therefore, this review describes the main approaches and tools applied in the search for bioactive secondary metabolites, as well as presents several examples of compounds produced by different fungi species with proven pharmacological effects and additional examples of fungal cytotoxic and antimicrobial molecules. The review does not cover all fungal secondary metabolites already described; however, it presents some reports that can be useful at any phase of the drug discovery process, mainly for pharmaceutical applications.

Recent Advances in Mass Spectrometry-Based Structural Elucidation Techniques

Mass spectrometry (MS) has become the central technique that is extensively used for the analysis of molecular structures of unknown compounds in the gas phase. It manipulates the molecules by converting them into ions using various ionization sources. With high-resolution MS, accurate molecular weights (MW) of the intact molecular ions can be measured so that they can be assigned a molecular formula with high confidence. Furthermore, the application of tandem MS has enabled detailed structural characterization by breaking the intact molecular ions and protonated or deprotonated molecules into key fragment ions. This approach is not only used for the structural elucidation of small molecules (MW < 2000 Da), but also crucial biopolymers such as proteins and polypeptides; therefore, MS has been extensively used in multiomics studies for revealing the structures and functions of important biomolecules and their interactions with each other. The high sensitivity of MS has enabled the analysis of low-level analytes in complex matrices. It is also a versatile technique that can be coupled with separation techniques, including chromatography and ion mobility, and many other analytical instruments such as NMR. In this review, we aim to focus on the technical advances of MS-based structural elucidation methods over the past five years, and provide an overview of their applications in complex mixture analysis. We hope this review can be of interest for a wide range of audiences who may not have extensive experience in MS-based techniques.

Computational Approaches and Use of Chiroptical Probes in the Absolute Configuration Assignment to Natural Products by ECD Spectroscopy: A 1,2,3-Trihydroxy-p-menthane as a Case Study

In this study, the computational analysis of electronic circular dichroism (ECD) spectra and the employment of biphenyl chiroptical probes were compared in the absolute configuration assignment of (-)-1α,2α,3β-trihydroxy-p-menthane (1), taken as a representative example of a UV-transparent chiral natural product. The usefulness of chiroptical probes in the configurational assignments of natural products and their complementarity to the computational protocols is herein highlighted. The biphenyl probe approach proves to be straightforward, reliable, and suitable for conformationally mobile and ECD silent compounds, not treatable by computational analysis of chiroptical data.

Testing the Scalability of the HS-AUTOFIT Tool in a High-Performance Computing Environment

In the last years, the development of broadband chirped-pulse Fourier transform microwave spectrometers has revolutionized the field of rotational spectroscopy. Currently, it is possible to experimentally obtain a large quantity of spectra that would be difficult to analyze manually due to two main reasons. First, recent instruments allow obtaining a considerable amount of data in very short times, and second, it is possible to analyze complex mixtures of molecules that all contribute to the density of the spectra. AUTOFIT is a spectral assignment software application that was developed in 2013 to support and facilitate the analysis. Notwithstanding the benefits AUTOFIT brings in terms of automation of the analysis of the accumulated data, it still does not guarantee a good performance in terms of execution time because it leverages the computing power of a single computing machine. To cater to this requirement, we developed a parallel version of AUTOFIT, called HS-AUTOFIT, capable of running on high-performance computing (HPC) clusters to shorten the time to explore and analyze spectral big data. In this paper, we report some tests conducted on a real HPC cluster aimed at providing a quantitative assessment of HS-AUTOFIT’s scaling capabilities in a multi-node computing context. The collected results demonstrate the benefits of the proposed approach in terms of a significant reduction in computing time.

Secondary metabolites from hypocrealean entomopathogenic fungi: genomics as a tool to elucidate the encoded parvome

Covering: 2014 up to the third quarter of 2019 Hypocrealean entomopathogenic fungi (HEF) produce a large variety of secondary metabolites (SMs) that are prominent virulence factors or mediate various interactions in the native niches of these organisms. Many of these SMs show insecticidal, immune system modulatory, antimicrobial, cytotoxic and other bioactivities of clinical or agricultural significance. Recent advances in whole genome sequencing technologies and bioinformatics have revealed many biosynthetic gene clusters (BGCs) potentially involved in SM production in HEF. Some of these BGCs are now well characterized, with the structures of the cognate product congeners elucidated, and the proposed biosynthetic functions of key enzymes validated. However, the vast majority of HEF BGCs are still not linked to SM products ("orphan" BGCs), including many clusters that are not expressed (silent) under routine laboratory conditions. Thus, investigations into the encoded parvome (the secondary metabolome predicted from the genome) of HEF allows the discovery of BGCs for known SMs; uncovers novel metabolites based on the BGCs; and catalogues the predicted SM biosynthetic potential of these fungi. Herein, we summarize new developments of the field, and survey the polyketide, nonribosomal peptide, terpenoid and hybrid SM BGCs encoded in the currently available 40 HEF genome sequences. Studying the encoded parvome of HEF will increase our understanding of the multifaceted roles that SMs play in biotic and abiotic interactions and will also reveal biologically active SMs that can be exploited for the discovery of human and veterinary drugs or crop protection agents.

Bioprospecting marine actinomycetes for antileishmanial drugs: current perspectives and future prospects

Revived analysis interests in natural products in the hope of discovering new and novel antileishmanial drug leads have been driven partially by the increasing incidence of drug resistance. However, the search for novel chemotherapeutics to combat drug resistance had previously concentrated on the terrestrial environment. As a result, the marine environment was often overlooked. For example, actinomycetes are an immensely important group of bacteria for antibiotic production, producing two-thirds of the known antibiotics. However, these bacteria have been isolated primarily from terrestrial sources. Consequently, there have been revived efforts to discover new compounds from uncharted or uncommon environments like the marine ecosystem. Isolation, purification and structure elucidation of target compounds from complex metabolic extract are major challenges in natural products chemistry. As a result, marine-derived natural products from actinomycetes that have antileishmanial bioactivity potentials have been understudied. This review highlights metagenomic and bioassay approaches which could help streamline the drug discovery process thereby greatly reducing time and cost of dereplication to identify suitable antileishmanial drug candidates.

MassSpecBlocks: a web-based tool to create building blocks and sequences of nonribosomal peptides and polyketides for tandem mass spectra analysis

Nonribosomal peptides and polyketides are natural products commonly synthesized by microorganisms. They are widely used in medicine, agriculture, environmental protection, and other fields. The structures of natural products are often analyzed by high-resolution tandem mass spectrometry, which becomes more popular with its increasing availability. However, the characterization of nonribosomal peptides and polyketides from tandem mass spectra is a nontrivial task because they are composed of many uncommon building blocks in addition to proteinogenic amino acids. Moreover, many of them have cyclic and branch-cyclic structures. Here, we introduce MassSpecBlocks – an open-source and web-based tool that converts the input chemical structures in SMILES format into sequences of building blocks. The structures can be searched in public databases PubChem, ChemSpider, ChEBI, NP Atlas, COCONUT, and Norine and edited in a user-friendly graphical interface. Although MassSpecBlocks can serve as a stand-alone database, our primary goal was to enable easy construction of custom sequence and building block databases, which can be used to annotate mass spectra in CycloBranch software. CycloBranch is an open-source, cross-platform, and stand-alone tool that we recently released for annotating spectra of linear, cyclic, branched, and branch-cyclic nonribosomal peptides and polyketide siderophores. The sequences and building blocks created in MassSpecBlocks can be easily exported into a plain text format used by CycloBranch. MassSpecBlocks is available online or can be installed entirely offline. It offers a REST API to cooperate with other tools.

Computer Assisted Structure Elucidation (CASE): Current and future perspectives

The first efforts for the development of methods for Computer-Assisted Structure Elucidation (CASE) were published more than 50 years ago. CASE expert systems based on one-dimensional (1D) and two-dimensional (2D) Nuclear Magnetic Resonance (NMR) data have matured considerably by now. The structures of a great number of complex natural products have been elucidated and/or revised using such programs. In this article, we discuss the most likely directions in which CASE will evolve. We act on the premise that a synergistic interaction exists between CASE, new NMR experiments, and methods of computational chemistry, which are continuously being improved. The new developments in NMR experiments (long-range correlation experiments, pure-shift methods, coupling constants measurement and prediction, residual dipolar couplings [RDCs]), and residual chemical shift anisotropies [RCSAs], evolution of density functional theory (DFT), and machine learning algorithms will have an influence on CASE systems and vice versa. This is true also for new techniques for chemical analysis (Atomic Force Microscopy [AFM], "crystalline sponge" X-ray analysis, and micro-Electron Diffraction [micro-ED]), which will be used in combination with expert systems. We foresee that CASE will be utilized widely and become a routine tool for NMR spectroscopists and analysts in academic and industrial laboratories. We believe that the "golden age" of CASE is still in the future.

Complementary Analytical Platforms of NMR Spectroscopy and LCMS Analysis in the Metabolite Profiling of Isochrysis galbana

This study was designed to profile the metabolites of Isochrysis galbana, an indigenous and less explored microalgae species. ¹H Nuclear Magnetic Resonance (NMR) spectroscopy and Liquid Chromatography-Mass Spectrometry (LCMS) were used to establish the metabolite profiles of five different extracts of this microalga, which are hexane (Hex), ethyl acetate (EtOAc), absolute ethanol (EtOH), EtOH:water 1:1 (AqE), and 100% water (Aq). Partial least square discriminant analysis (PLS–DA) of the generated profiles revealed that EtOAc and Aq extracts contain a diverse range of metabolites as compared to the other extracts with a total of twenty-one metabolites, comprising carotenoids, polyunsaturated fatty acids, and amino acids, that were putatively identified from the NMR spectra. Meanwhile, thirty-two metabolites were successfully annotated from the LCMS/MS data, ten of which (palmitic acid, oleic acid, α-linolenic acid, arachidic acid, cholesterol, DHA, DPA, fucoxanthin, astaxanthin, and pheophytin) were similar to those present in the NMR profile. Another eleven glycerophospholipids were discovered using MS/MS-based molecular network (MN) platform. The results of this study, besides providing a better understanding of I.galbana’s chemical make-up, will be of importance in exploring this species potential as a feed ingredient in the aquaculture industry.

MicroED in natural product and small molecule research

Covering: 2013 to 2020The electron cryo-microscopy (cryo-EM) method Microcrystal Electron Diffraction (MicroED) allows the collection of high-resolution structural data from vanishingly small crystals that appear like amorphous powders or very fine needles. Since its debut in 2013, data collection and analysis schemes have been fine-tuned, and there are currently close to 100 structures determined by MicroED. Although originally developed to study proteins, MicroED is also very powerful for smaller systems, with some recent and very promising examples from the field of natural products. Herein, we review what has been achieved so far and provide examples of natural product structures, as well as demonstrate the expected future impact of MicroED to the field of natural product and small molecule research.

Facile NMR approach for profiling curcuminoids present in turmeric

Curcumin, together with demethoxycurcumin and bisdemethoxycurcumin as a whole called curcuminoids, is an active phytochemical constituent present in the turmeric. When it comes to their analysis, most will rely on UV-Visible spectroscopy, HPLC and LC-MS methods. Looking to improve productivity, time and simplicity, we are proposing a ¹H NMR based approach for curcuminoids analysis and its applications to different geographical regions. In the present work, sample preparation protocol is reported for the simultaneous determination of curcuminoids using ¹H NMR. For the quantification of curcuminoids, 6-7 ppm vinylic proton region in the ¹H NMR spectrum was used, where acetone was observed as the suitable solvent in terms of curcuminoids solubility and proper resolution of peak. The result shows that curcumin (46.8-59.50%) was major among all varieties, followed by DMC (22.15-27.70%) and BDMC (17.52-30.29%) except in Andhrapradesh variety, where BDMC (30.29%) was more than DMC (22.89%). These studies were further supported by HPLC analysis.

Gliotoxin, identified from a screen of fungal metabolites, disrupts 7SK snRNP, releases P-TEFb, and reverses HIV-1 latency

A leading pharmacological strategy toward HIV cure requires "shock" or activation of HIV gene expression in latently infected cells with latency reversal agents (LRAs) followed by their subsequent clearance. In a screen for novel LRAs, we used fungal secondary metabolites as a source of bioactive molecules. Using orthogonal mass spectrometry (MS) coupled to latency reversal bioassays, we identified gliotoxin (GTX) as a novel LRA. GTX significantly induced HIV-1 gene expression in latent ex vivo infected primary cells and in CD4⁺ T cells from all aviremic HIV-1⁺ participants. RNA sequencing identified 7SK RNA, the scaffold of the positive transcription elongation factor b (P-TEFb) inhibitory 7SK small nuclear ribonucleoprotein (snRNP) complex, to be significantly reduced upon GTX treatment of CD4⁺ T cells. GTX directly disrupted 7SK snRNP by targeting La-related protein 7 (LARP7), releasing active P-TEFb, which phosphorylated RNA polymerase II (Pol II) C-terminal domain (CTD), inducing HIV transcription.

CycloBranch 2: Molecular Formula Annotations Applied to imzML Data Sets in Bimodal Fusion and LC-MS Data Files

Natural product chemistry, microbiology, and food, human, and plant metabolomics represent a few sources of complex metabolomics data generated by mass spectrometry. Among the medley of software tools used to handle these data sets, no universal tool can qualitatively, quantitatively, or statistically address major biological questions or tasks. CycloBranch 2, an open and platform-free software, at least now provides the de novo generation of molecular formulas of unknown compounds in both liquid chromatography/mass spectrometry and mass spectrometry imaging datafiles. For imaging files, this database-free approach was documented in the bimodal image fusion and characterization of three small molecules, including metallophores. The fine isotope ratio data filtering step distinguished ³⁴S/¹³C₂ and ⁴¹K/¹³C₂ features. The standalone software package is implemented in C++ and can be downloaded from https://ms.biomed.cas.cz/cyclobranch/ and used under GNU General Public License.

The Symbiotic Relationship Between Drug Discovery and Organic Chemistry

All pharmaceutical products contain organic molecules; the source may be a natural product or a fully synthetic molecule, or a combination of both. Thus, it follows that organic chemistry underpins both existing and upcoming pharmaceutical products. The reverse relationship has also affected organic synthesis, changing its landscape towards increasingly complex targets. This Review article sets out to give a concise appraisal of this symbiotic relationship between organic chemistry and drug discovery, along with a discussion of the design concepts and highlighting key milestones along the journey. In particular, criteria for a high-quality compound library design enabling efficient virtual navigation of chemical space, as well as rise and fall of concepts for its synthetic exploration (such as combinatorial chemistry; diversity-, biology-, lead-, or fragment-oriented syntheses; and DNA-encoded libraries) are critically surveyed.

Metagenomics Approaches in Discovery and Development of New Bioactive Compounds from Marine Actinomycetes

Marine actinomycetes are prolific sources of marine drug discovery system contributing for several bioactive compounds of biomedical prominence. Metagenomics, a culture-independent technique through its sequence- and function-based screening has led to the discovery and synthesis of numerous biologically significant compounds like polyketide synthase, Non-ribosomal peptide synthetase, antibiotics, and biocatalyst. While metagenomics offers different advantages over conventional sequencing techniques, they also have certain limitations including bias classification, non-availability of quality DNA samples, heterologous expression, and host selection. The assimilation of advanced amplification and screening methods such as φ29 DNA polymerase, Next-Generation Sequencing, Cosmids, and recent bioinformatics tools like automated genome mining, anti-SMASH have shown promising results to overcome these constrains. Consequently, functional genomics and bioinformatics along with synthetic biology will be crucial for the success of the metagenomic approach and indeed for exploring new possibilities among the microbial consortia for the future drug discovery process.

Characterisation and screening of antimicrobial essential oil components against clinically important antibiotic-resistant bacteria using thin layer chromatography-direct bioautography hyphenated with GC-MS, LC-MS and NMR

INTRODUCTION

The antimicrobial activity of many essential oils (EOs) is well established, indicating that EOs may be a source of compounds for antimicrobial drug development. Thin layer chromatography-direct bioautography (TLC-DB) can quickly identify antimicrobial components in complex mixtures and can be applied to the screening of EOs for lead compounds.

OBJECTIVES

This study aimed to identify antimicrobial components of oregano, rosewood and cumin EOs against antibiotic-sensitive and -resistant bacteria using TLC-DB and a multi-faceted approach of GC-MS, LC-MS and NMR techniques to characterise bioactive compounds. The study also aimed to quantify the antimicrobial activity of bioactive compounds in order to evaluate their potential for the development of therapies against antibiotic-resistant bacteria.

MATERIALS AND METHODS

EOs were eluted on TLC plates and sprayed with a suspension of Staphylococcus aureus, Enterococcus faecium, Escherichia coli or Pseudomonas aeruginosa (antibiotic-sensitive and -resistant isolates). Zones of inhibition, visualised with iodonitrotetrazolium chloride, were subject to GC-MS, LC-MS and NMR to characterise the bioactive compounds.

RESULTS

Seven compounds were identified from the three EOs using GC-MS, while LC-MS and NMR failed to detect the presence of any further non-volatile or heat labile compounds. Carvacrol was most antimicrobial compound identified, with minimum inhibitory concentrations ranging 0.99-31.62 mM.

CONCLUSION

The identified antimicrobial compounds present in oregano, rosewood and cumin EOs including carvacrol may be candidates for the development of novel antimicrobial therapies against antibiotic-resistant bacteria.

Analysis of Microbial Siderophores by Mass Spectrometry

Siderophores represent important microbial virulence factors and infection biomarkers. Their monitoring in fermentation broths, bodily fluids, and tissues should be reproducible. Similar isolation, characterization, and quantitation studies can often have conflicting results, and without proper documentation of sample collection, data processing, and analysis methods, it is difficult to reexamine the data and reconcile these differences. In this Springer Nature Protocol, we present the procedure optimized for ferricrocin/triacetylfusarinine C extraction from biological material as well as for tissue fixation and cryosectioning for optical microscopy and for both elemental and molecular mass spectrometry imaging. Special attention is paid to siderophore data mining from conventional and product ion mass spectra, liquid chromatography, and mass spectrometry imaging datasets, performed here by our free software called CycloBranch.

Scedosporium and Lomentospora: an updated overview of underrated opportunists

Species of Scedosporium and Lomentospora are considered as emerging opportunists, affecting immunosuppressed and otherwise debilitated patients, although classically they are known from causing trauma-associated infections in healthy individuals. Clinical manifestations range from local infection to pulmonary colonization and severe invasive disease, in which mortality rates may be over 80%. These unacceptably high rates are due to the clinical status of patients, diagnostic difficulties, and to intrinsic antifungal resistance of these fungi. In consequence, several consortia have been founded to increase research efforts on these orphan fungi. The current review presents recent findings and summarizes the most relevant points, including the Scedosporium/Lomentospora taxonomy, environmental distribution, epidemiology, pathology, virulence factors, immunology, diagnostic methods, and therapeutic strategies.

CycloBranch: An open tool for fine isotope structures in conventional and product ion mass spectra

Within the growing community of Fourier transform mass spectrometry users, the identification of fine isotope structure has become an indispensable method for molecular formula determination. In this work, the fine isotope envelopes for accessing the mutual ratio of 2 closely related pyoverdines in a mixture were used. Bacterial siderophores pyoverdines D and E cannot be easily separated via liquid chromatography-mass spectrometry because their structures differ in (de)amidation at the respective chromophore parts only. Their mutual ratio was determined in a mixture via nuclear magnetic resonance spectroscopy and semiquantitative mass spectrometry using our open-source software CycloBranch, which represents a genuine free tool supporting the determination of fine isotope structures in both conventional and product ion mass spectra. Native Bruker, Thermo, and Waters data formats are supported in addition to XML and plain text formats.

Non-invasive and invasive diagnoses of aspergillosis in a rat model by mass spectrometry

Invasive pulmonary aspergillosis results in 450,000 deaths per year and complicates cancer chemotherapy, transplantations and the treatment of other immunosuppressed patients. Using a rat model of experimental aspergillosis, the fungal siderophores ferricrocin and triacetylfusarinine C were identified as markers of aspergillosis and quantified in urine, serum and lung tissues. Biomarkers were analyzed by matrix-assisted laser desorption ionization (MALDI) and electrospray ionization mass spectrometry using a 12T SolariX Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. The limits of detection of the ferri-forms of triacetylfusarinine C and ferricrocin in the rat serum were 0.28 and 0.36 ng/mL, respectively. In the rat urine the respective limits of detection achieved 0.02 and 0.03 ng/mL. In the sera of infected animals, triacetylfusarinine C was not detected but ferricrocin concentration fluctuated in the 3–32 ng/mL range. Notably, the mean concentrations of triacetylfusarinine C and ferricrocin in the rat urine were 0.37 and 0.63 μg/mL, respectively. The MALDI FTICR mass spectrometry imaging illustrated the actual microbial ferricrocin distribution in the lung tissues and resolved the false-positive results obtained by the light microscopy and histological staining. Ferricrocin and triacetylfusarinine C detection in urine represents an innovative non-invasive indication of Aspergillus infection in a host.

Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10³-10⁴) and dynamic range (∼10³-10⁴), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.

Synergistic Combination of CASE Algorithms and DFT Chemical Shift Predictions: A Powerful Approach for Structure Elucidation, Verification, and Revision

Structure elucidation of complex natural products and new organic compounds remains a challenging problem. To support this endeavor, CASE (computer-assisted structure elucidation) expert systems were developed. These systems are capable of generating a set of all possible structures consistent with an ensemble of 2D NMR data followed by selection of the most probable structure on the basis of empirical NMR chemical shift prediction. However, in some cases, empirical chemical shift prediction is incapable of distinguishing the correct structure. Herein, we demonstrate for the first time that the combination of CASE and density functional theory (DFT) methods for NMR chemical shift prediction allows the determination of the correct structure even in difficult situations. An expert system, ACD/Structure Elucidator, was used for the CASE analysis. This approach has been tested on three challenging natural products: aquatolide, coniothyrione, and chiral epoxyroussoenone. This work has demonstrated that the proposed synergistic approach is an unbiased, reliable, and very efficient structure verification and de novo structure elucidation method that can be applied to difficult structural problems when other experimental methods would be difficult or impossible to use.