Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

Contribution of Untargeted Metabolomics for Future Assessment of Biotech Crops

The nutritional value and safety of food crops are ultimately determined by their chemical composition. Recent developments in the field of metabolomics have made it possible to characterize the metabolic profile of crops in a comprehensive and high-throughput manner. Here, we propose that state-of-the-art untargeted metabolomics technology should be leveraged for safety assessment of new crop products. We suggest generally applicable experimental design principles that facilitate the efficient and rigorous identification of both intended and unintended metabolic alterations associated with a newly engineered trait. Our proposition could contribute to increased transparency of the safety assessment process for new biotech crops.

Pharmacognosy in the digital era: shifting to contextualized metabolomics

Humans have co-evolved alongside numerous other organisms, some having a profound effect on health and nutrition. As the earliest pharmaceutical subject, pharmacognosy has evolved into a meta-discipline devoted to natural biomedical agents and their functional properties. While the acquisition of expanding data volumes is ongoing, contextualization is lagging. Thus, we assert that the establishment of an integrated and open databases ecosystem will nurture the discipline. After proposing an epistemological framework of knowledge acquisition in pharmacognosy, this study focuses on recent computational and analytical approaches. It then elaborates on the flux of research data, where good practices could foster the implementation of more integrated systems, which will in turn help shaping the future of pharmacognosy and determine its constitutional societal relevance.

Metabolomics-Driven Discovery of Meroterpenoids from a Mussel-Derived Penicillium ubiquetum

Penicillium ubiquetum MMS330 isolated from the blue mussel Mytilus edulis collected on the Loire estuary in France was here investigated. As very few secondary metabolites have been documented for this species, its metabolome was studied following the OSMAC approach to enhance as many biosynthetic pathways as possible. Interestingly, HPLC-HRMS based hierarchical clustering analysis together with MS/MS molecular networking highlighted the selective overproduction of some structurally related compounds when the culture was performed on seawater CYA (Czapek Yeast extract Agar) medium. Mass-guided purification from large scale cultivation on this medium led to the isolation of nine meroterpenoids including two new analogues, 22-deoxyminiolutelide A (1) and 4-hydroxy-22-deoxyminiolutelide B (2), together with seven known compounds (3-9). The structures of 1 and 2 were elucidated on the basis of HR-ESIMS and NMR spectroscopic data analysis. Furthermore, NMR signals of 22-deoxyminiolutelide B (3) were reassigned.

Cacolides: Sesterterpene Butenolides from a Southern Australian Marine Sponge, Cacospongia sp

Chemical analysis of a marine sponge, Cacospongia sp. (CMB-03404), obtained during deep sea commercial fishing activities off the southern coast of Australia, yielded an unprecedented family of sesterterpene α-methyl-γ-hydroxybutenolides, cacolides A–L (1–12), together with biosynthetically related norsesterterpene carboxylic acids, cacolic acids A–C (13–15). Structures were assigned on the basis of detailed spectroscopic analysis with comparisons to known natural products and biosynthetic considerations. In addition to revealing new chemical diversity, this study provided a valuable platform for comparing and contrasting the capabilities of the traditional dereplication technologies of HPLC-DAD, HPLC-MS and NMR, with those of the emerging HPLC-MS/MS approach known as global natural products social molecular networking (GNPS), as applied to marine sponge sesterterpene tetronic acids.

Comparative metabolomics reveals defence-related modification of citrinin by Penicillium citrinum within a synthetic Penicillium-Pseudomonas community

Co-occurring microorganisms have been proved to influence the performance of each other by metabolic means in nature. Here we generated a synthetic fungal-bacterial community comprising Penicillium citrinum and Pseudomonas aeruginosa employing the previously described membrane-separated co-culture device. By applying a newly designed molecular networking routine, new citrinin-related metabolites induced by the fungal-bacterial cross-talk were unveiled in trace amounts. A mechanically cycled co-culture setup with external pumping forces accelerating the chemically interspecies communication was then developed to boost the production of cross-talk-induced metabolites. Multivariate data analysis combined with molecular networking revealed the accumulation of a pair of co-culture-induced molecules whose productions were positively correlated to the exchange rate in the new co-cultures, facilitating the discovery of the previously undescribed antibiotic citrinolide with a novel skeleton. This highly oxidized citrinin adduct showed significantly enhanced antibiotic property against the partner strain P. aeruginosa than its precursor citrinin, suggesting a role in the microbial competition. Thus, we propose competitive-advantage-oriented structural modification driven by microbial defence response mechanism in the interspecies cross-talk might be a promising approach in the search for novel antibiotics. Besides, this study highlights the utility of MS-based metabolomics as an effective tool in the direct biochemical analysis of the community metabolism.

MetGem Software for the Generation of Molecular Networks Based on the t-SNE Algorithm

Molecular networking (MN) is becoming a standard bioinformatics tool in the metabolomic community. Its paradigm is based on the observation that compounds with a high degree of chemical similarity share comparable MS² fragmentation pathways. To afford a clear separation between MS² spectral clusters, only the most relevant similarity scores are selected using dedicated filtering steps requiring time-consuming parameter optimization. Depending on the filtering values selected, some scores are arbitrarily deleted and a part of the information is ignored. The problem of creating a reliable representation of MS² spectra data sets can be solved using algorithms developed for dimensionality reduction and pattern recognition purposes, such as t-distributed stochastic neighbor embedding (t-SNE). This multivariate embedding method pays particular attention to local details by using nonlinear outputs to represent the entire data space. To overcome the limitations inherent to the GNPS workflow and the networking architecture, we developed MetGem. Our software allows the parallel investigation of two complementary representations of the raw data set, one based on a classic GNPS-style MN and another based on the t-SNE algorithm. The t-SNE graph preserves the interactions between related groups of spectra, while the MN output allows an unambiguous separation of clusters. Additionally, almost all parameters can be tuned in real time, and new networks can be generated within a few seconds for small data sets. With the development of this unified interface ( https://metgem.github.io ), we fulfilled the need for a dedicated, user-friendly, local software for MS² comparison and spectral network generation.

Soil Bacteria Isolated From Tunisian Arid Areas Show Promising Antimicrobial Activities Against Gram-Negatives

Arid regions show relatively fewer species in comparison to better-watered biomes, but the competition for the few nutrients is very distinct. Here, in total 373 bacterial strains were isolated from rhizospheric soils obtained from three different sampling sites in Tunisia. Their potential for the production of antimicrobial compounds was evaluated. Bacterial strains, showing antibacterial activity against pathogenic bacteria, were isolated from all three sites, one strain from the Bou-Hedma national park, 15 strains from Chott-Djerid, and 13 strains from Matmata, respectively. The dominant genus was Bacillus, with 27 out of 29 strains. Most interestingly, 93% of the isolates showed activity against Gram-positive and Gram-negative test bacteria. Strain Bacillus sp. M21, harboring high inhibitory potential, even against clinical isolates of Gram-negative bacteria, was analyzed in detail to enable purification and identification of the bioactive compound responsible for its bioactivity. Subsequent HPLC-MS and NMR analyses resulted in the identification of 1-acetyl-β-carboline as active component. Furthermore, fungicides of the bacillomycin and fengycin group, which in addition show antibiotic effects, were identified. This work highlights the high potential of the arid-adapted strains for the biosynthesis of specialized metabolites and suggest further investigation of extreme environments, since they constitute a promising bioresource of biologically active compounds.

Analysis of the Genome and Metabolome of Marine Myxobacteria Reveals High Potential for Biosynthesis of Novel Specialized Metabolites

Comparative genomic/metabolomic analysis is a powerful tool to disclose the potential of microbes for the biosynthesis of novel specialized metabolites. In the group of marine myxobacteria only a limited number of isolated species and sequenced genomes is so far available. However, the few compounds isolated thereof so far show interesting bioactivities and even novel chemical scaffolds; thereby indicating a huge potential for natural product discovery. In this study, all marine myxobacteria with accessible genome data (n = 5), including Haliangium ochraceum DSM 14365, Plesiocystis pacifica DSM 14875, Enhygromyxa salina DSM 15201 and the two newly sequenced species Enhygromyxa salina SWB005 and SWB007, were analyzed. All of these accessible genomes are large (~10 Mb), with a relatively small core genome and many unique coding sequences in each strain. Genome analysis revealed a high variety of biosynthetic gene clusters (BGCs) between the strains and several resistance models and essential core genes indicated the potential to biosynthesize antimicrobial molecules. Polyketides (PKs) and terpenes represented the majority of predicted specialized metabolite BGCs and contributed to the highest share between the strains. BGCs coding for non-ribosomal peptides (NRPs), PK/NRP hybrids and ribosomally synthesized and post-translationally modified peptides (RiPPs) were mostly strain specific. These results were in line with the metabolomic analysis, which revealed a high diversity of the chemical features between the strains. Only 6-11% of the metabolome was shared between all the investigated strains, which correlates to the small core genome of these bacteria (13-16% of each genome). In addition, the compound enhygrolide A, known from E. salina SWB005, was detected for the first time and structurally elucidated from Enhygromyxa salina SWB006. The here acquired data corroborate that these microorganisms represent a most promising source for the detection of novel specialized metabolites.

Gut Microbial and Metabolic Responses to Salmonella enterica Serovar Typhimurium and Candida albicans

The gut microbiota is increasingly recognized for playing a critical role in human health and disease, especially in conferring resistance to both virulent pathogens such as Salmonella, which infects 1.2 million people in the United States every year (E. Scallan, R. M. Hoekstra, F. J. Angulo, R. V. Tauxe, et al., Emerg Infect Dis 17:7–15, 2011, https://doi.org/10.3201/eid1701.P11101), and opportunistic pathogens like Candida, which causes an estimated 46,000 cases of invasive candidiasis each year in the United States (Centers for Disease Control and Prevention, Antibiotic Resistance Threats in the United States, 2013, 2013). Using a gnotobiotic mouse model, we investigate potential changes in gut microbial community structure and function during infection using metagenomics and metabolomics. We observe that changes in the community and in biosynthetic gene cluster potential occur within 3 days for the virulent Salmonella enterica serovar Typhimurium, but there are minimal changes with a poorly colonizing Candida albicans. In addition, the metabolome shifts depending on infection status, including changes in glutathione metabolites in response to Salmonella infection, potentially in response to host oxidative stress.

The gut microbiota confers resistance to pathogens of the intestinal ecosystem, yet the dynamics of pathogen-microbiome interactions and the metabolites involved in this process remain largely unknown. Here, we use gnotobiotic mice infected with the virulent pathogen Salmonella enterica serovar Typhimurium or the opportunistic pathogen Candida albicans in combination with metagenomics and discovery metabolomics to identify changes in the community and metabolome during infection. To isolate the role of the microbiota in response to pathogens, we compared mice monocolonized with the pathogen, uninfected mice “humanized” with a synthetic human microbiome, or infected humanized mice. In Salmonella-infected mice, by 3 days into infection, microbiome community structure and function changed substantially, with a rise in Enterobacteriaceae strains and a reduction in biosynthetic gene cluster potential. In contrast, Candida-infected mice had few microbiome changes. The LC-MS metabolomic fingerprint of the cecum differed between mice monocolonized with either pathogen and humanized infected mice. Specifically, we identified an increase in glutathione disulfide, glutathione cysteine disulfide, inosine 5’-monophosphate, and hydroxybutyrylcarnitine in mice infected with Salmonella in contrast to uninfected mice and mice monocolonized with Salmonella. These metabolites potentially play a role in pathogen-induced oxidative stress. These results provide insight into how the microbiota community members interact with each other and with pathogens on a metabolic level.

Dereplication of plant phenolics using a mass-spectrometry database independent method

INTRODUCTION

Dereplication, an approach to sidestep the efforts involved in the isolation of known compounds, is generally accepted as being the first stage of novel discoveries in natural product research. It is based on metabolite profiling analysis of complex natural extracts.

OBJECTIVE

To present the application of LipidXplorer for automatic targeted dereplication of phenolics in plant crude extracts based on direct infusion high-resolution tandem mass spectrometry data.

MATERIAL AND METHODS

LipidXplorer uses a user-defined molecular fragmentation query language (MFQL) to search for specific characteristic fragmentation patterns in large data sets and highlight the corresponding metabolites. To this end, MFQL files were written to dereplicate common phenolics occurring in plant extracts. Complementary MFQL files were used for validation purposes.

RESULTS

New MFQL files with molecular formula restrictions for common classes of phenolic natural products were generated for the metabolite profiling of different representative crude plant extracts. This method was evaluated against an open-source software for mass-spectrometry data processing (MZMine®) and against manual annotation based on published data.

CONCLUSION

The targeted LipidXplorer method implemented using common phenolic fragmentation patterns, was found to be able to annotate more phenolics than MZMine® that is based on automated queries on the available databases. Additionally, screening for ascarosides, natural products with unrelated structures to plant phenolics collected from the nematode Caenorhabditis elegans, demonstrated the specificity of this method by cross-testing both groups of chemicals in both plants and nematodes.

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.

Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases

In the past decade, advances in liquid chromatography-mass spectrometry (LC-MS) have revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply, researchers are now primed to uncover key metabolites and their associations with diseases. The employment of untargeted metabolomics has led to new biomarker discoveries and a better mechanistic understanding of diseases with applications in precision medicine. However, many major pertinent challenges remain. First, compound identification has been poor, and left an overwhelming number of unidentified peaks. Second, partial, incomplete metabolomes persist due to factors such as limitations in mass spectrometry data acquisition speeds, wide-range of metabolites concentrations, and cellular/tissue/temporal-specific expression changes that confound our understanding of metabolite perturbations. Third, to contextualize metabolites in pathways and biology is difficult because many metabolites partake in multiple pathways, have yet to be described species specificity, or possess unannotated or more-complex functions that are not easily characterized through metabolomics analyses. From a translational perspective, information related to novel metabolite biomarkers, metabolic pathways, and drug targets might be sparser than they should be. Thankfully, significant progress has been made and novel solutions are emerging, achieved through sustained academic and industrial community efforts in terms of hardware, computational, and experimental approaches. Given the rapidly growing utility of metabolomics, this review will offer new perspectives, increase awareness of the major challenges in LC-MS metabolomics that will significantly benefit the metabolomics community and also the broader the biomedical community metabolomics aspire to serve.

Gene-guided discovery and engineering of branched cyclic peptides in plants

The plant kingdom contains vastly untapped natural product chemistry, which has been traditionally explored through the activity-guided approach. Here, we describe a gene-guided approach to discover and engineer a class of plant ribosomal peptides, the branched cyclic lyciumins. Initially isolated from the Chinese wolfberry Lycium barbarum, lyciumins are protease-inhibiting peptides featuring an N-terminal pyroglutamate and a macrocyclic bond between a tryptophan-indole nitrogen and a glycine α-carbon. We report the identification of a lyciumin precursor gene from L. barbarum, which encodes a BURP domain and repetitive lyciumin precursor peptide motifs. Genome mining enabled by this initial finding revealed rich lyciumin genotypes and chemotypes widespread in flowering plants. We establish a biosynthetic framework of lyciumins and demonstrate the feasibility of producing diverse natural and unnatural lyciumins in transgenic tobacco. With rapidly expanding plant genome resources, our approach will complement bioactivity-guided approaches to unlock and engineer hidden plant peptide chemistry for pharmaceutical and agrochemical applications.

Unexpected differential metabolic responses of Campylobacter jejuni to the abundant presence of glutamate and fucose

INTRODUCTION

Campylobacter jejuni is the leading cause of foodborne bacterial enteritis in humans, and yet little is known in regard to how genetic diversity and metabolic capabilities among isolates affect their metabolic phenotype and pathogenicity.

OBJECTIVES

For instance, the C. jejuni 11168 strain can utilize both L-fucose and L-glutamate as a carbon source, which provides the strain with a competitive advantage in some environments and in this study we set out to assess the metabolic response of C. jejuni 11168 to the presence of L-fucose and L-glutamate in the growth medium.

METHODS

To achieve this, untargeted hydrophilic liquid chromatography coupled to mass spectrometry was used to obtain metabolite profiles of supernatant extracts obtained at three different time points up to 24 h.

RESULTS

This study identified both the depletion and the production and subsequent release of a multitude of expected and unexpected metabolites during the growth of C. jejuni 11168 under three different conditions. A large set of standards allowed identification of a number of metabolites. Further mass spectrometry fragmentation analysis allowed the additional annotation of substrate-specific metabolites. The results show that C. jejuni 11168 upon L-fucose addition indeed produces degradation products of the fucose pathway. Furthermore, methionine was faster depleted from the medium, consistent with previously-observed methionine auxotrophy.

CONCLUSIONS

Moreover, a multitude of not previously annotated metabolites in C. jejuni were found to be increased specifically upon L-fucose addition. These metabolites may well play a role in the pathogenicity of this C. jejuni strain.

Sources of variation in foliar secondary chemistry in a tropical forest tree community

Specialist herbivores and pathogens could induce negative conspecific density dependence among their hosts and thereby contribute to the diversity of plant communities. A small number of hyperdiverse genera comprise a large portion of tree diversity in tropical forests. These closely related congeners are likely to share natural enemies. Diverse defenses could still allow congeners to partition niche space defined by natural enemies, but interspecific differences in defenses would have to exceed intraspecific variation in defenses. We ask whether interspecific variation in secondary chemistry exceeds intraspecific variation for species from four hyperdiverse tropical tree genera. We used novel methods to quantify chemical structural similarity for all compounds present in methanol extracts of leaf tissue. We sought to maximize intraspecific variation by selecting conspecific leaves from different ontogenetic stages (expanding immature vs. fully hardened mature), different light environments (deep understory shade vs. large forest gaps), and different seasons (dry vs. wet). Chemical structural similarity differed with ontogeny, light environment, and season, but interspecific differences including those among congeneric species were much larger. Our results suggest that species differences in secondary chemistry are large relative to within-species variation, perhaps sufficiently large to permit niche segregation among congeneric tree species based on chemical defenses.

Dereplication of microbial metabolites through database search of mass spectra

Natural products have traditionally been rich sources for drug discovery. In order to clear the road toward the discovery of unknown natural products, biologists need dereplication strategies that identify known ones. Here we report DEREPLICATOR+, an algorithm that improves on the previous approaches for identifying peptidic natural products, and extends them for identification of polyketides, terpenes, benzenoids, alkaloids, flavonoids, and other classes of natural products. We show that DEREPLICATOR+ can search all spectra in the recently launched Global Natural Products Social molecular network and identify an order of magnitude more natural products than previous dereplication efforts. We further demonstrate that DEREPLICATOR+ enables cross-validation of genome-mining and peptidogenomics/glycogenomics results.

Qiita: rapid, web-enabled microbiome meta-analysis

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, to understand relationships across studies, they must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome comparison platform, which we demonstrate with Human Microbiome Project and iHMP data.

Mining Actinomycetes for Novel Antibiotics in the Omics Era: Are We Ready to Exploit This New Paradigm?

The current spread of multi-drug resistance in a number of key pathogens and the lack of therapeutic solutions in development to address most of the emerging infections in the clinic that are difficult to treat have become major concerns. Microbial natural products represent one of the most important sources for the discovery of potential new antibiotics and actinomycetes have been one of the most relevant groups that are prolific producers of these bioactive compounds. Advances in genome sequencing and bioinformatic tools have collected a wealth of knowledge on the biosynthesis of these molecules. This has revealed the broad untapped biosynthetic diversity of actinomycetes, with large genomes and the capacity to produce more molecules than previously estimated, opening new opportunities to identify the novel classes of compounds that are awaiting to be discovered. Comparative genomics, metabolomics and proteomics and the development of new analysis and genetic engineering tools provide access to the integration of new knowledge and better understanding of the physiology of actinomycetes and their tight regulation of the production of natural products antibiotics. This new paradigm is fostering the development of new genomic-driven and culture-based strategies, which aims to deliver new chemical classes of antibiotics to be developed to the clinic and replenish the exhausted pipeline of drugs for fighting the progression of infection diseases in the near future.

Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

Genome mining of Streptomyces xinghaiensis NRRL B-24674T for the discovery of the gene cluster involved in anticomplement activities and detection of novel xiamycin analogs

Marine actinobacterium Streptomyces xinghaiensis NRRL B-24674^T has been characterized as a novel species, but thus far, its biosynthetic potential remains unexplored. In this study, the high-quality genome sequence of S. xinghaiensis NRRL B-24674^T was obtained, and the production of anticomplement agents, xiamycin analogs, and siderophores was investigated by genome mining. Anticomplement compounds are valuable for combating numerous diseases caused by the abnormal activation of the human complement system. The biosynthetic gene cluster (BGC) nrps1 resembles that of complestatins, which are potent microbial-derived anticomplement agents. The identification of the nrps1 BGC revealed a core peptide that differed from that in complestatin; thus, we studied the anticomplement activity of this strain. The culture broth of S. xinghaiensis NRRL B-24674^T displayed good anticomplement activity. Subsequently, the disruption of the genes in the nrps1 BGC resulted in the loss of anticomplement activity, confirming the involvement of this BGC in the biosynthesis of anticomplement agents. In addition, the mining of the BGC tep5, which resembles that of the antiviral pentacyclic indolosesquiterpene xiamycin, resulted in the discovery of nine xiamycin analogs, including three novel compounds. In addition to the BGCs responsible for desferrioxamine B, neomycin, ectoine, and carotenoid, 18 BGCs present in the genome are predicted to be novel. The results of this study unveil the potential of S. xinghaiensis as a producer of novel anticomplement agents and provide a basis for further exploration of the biosynthetic potential of S. xinghaiensis NRRL B-24674^T for the discovery of novel bioactive compounds by genome mining.

Seeking universal detectors for analytical characterizations

It is highly desirable to have a universal detector that can detect all types of compounds and give a uniform response regardless of the physiochemical properties of the compounds. With such a universal detector, all components in a sample can be accurately quantified without the need for individual standards. This is especially needed for the characterization of unknowns and for non-targeted analysis, or for samples that have no isolated standards available for each component. Over the years, much effort has been put into seeking a universal detection technology. In this review, we discuss the commonly used detectors for analytical characterization, including UV, RI, ELSD, CAD, CLND, FID, VUV, MS, NMR, and hyphenated detection, with the focuses on the "universal" features of these detectors regarding the types of molecules they can detect and the uniformity of responses.

Mind the Gap: Mapping Mass Spectral Databases in Genome-Scale Metabolic Networks Reveals Poorly Covered Areas

The use of mass spectrometry-based metabolomics to study human, plant and microbial biochemistry and their interactions with the environment largely depends on the ability to annotate metabolite structures by matching mass spectral features of the measured metabolites to curated spectra of reference standards. While reference databases for metabolomics now provide information for hundreds of thousands of compounds, barely 5% of these known small molecules have experimental data from pure standards. Remarkably, it is still unknown how well existing mass spectral libraries cover the biochemical landscape of prokaryotic and eukaryotic organisms. To address this issue, we have investigated the coverage of 38 genome-scale metabolic networks by public and commercial mass spectral databases, and found that on average only 40% of nodes in metabolic networks could be mapped by mass spectral information from standards. Next, we deciphered computationally which parts of the human metabolic network are poorly covered by mass spectral libraries, revealing gaps in the eicosanoids, vitamins and bile acid metabolism. Finally, our network topology analysis based on the betweenness centrality of metabolites revealed the top 20 most important metabolites that, if added to MS databases, may facilitate human metabolome characterization in the future.

Opportunities for plant natural products in infection control

The continued spread of antimicrobial resistance represents one of the most serious infectious disease threats to global health. There is consensus that a key component of addressing this threat is to replenish the waning pipeline of antimicrobials, with attention being paid to novel mechanisms of action. This includes the development of new classes of classic bacteriostatic and bactericidal antibiotics as well as antivirulence drugs, and it is especially in these areas where plant natural products demonstrate great potential. To this end, we discuss the unique characteristics of plant natural products, the advantages of plants as a resource for anti-infective drug discovery, and recent technologies that have further enabled this path of inquiry. As a result of emerging realization of their advantages, plant natural products have recently enjoyed increased scrutiny in antimicrobial lead discovery, and they will continue to serve as a source of leads. We conclude that plant natural products represent a promising and largely untapped source of new chemical entities from which novel anti-infectives can be discovered.

Distinct molecular signatures in dissolved organic matter produced by viral lysis of marine cyanobacteria

Dissolved organic matter (DOM) plays a central role in the microbial ecology and biogeochemistry of aquatic environments, yet little is known about how the mechanism of DOM release from its ultimate source, primary producer biomass, affects the molecular composition of the inputs to the dissolved pool. Here we used a model marine phytoplankton, the picocyanobacterium Synechococcus WH7803, to compare the composition of DOM released by three mechanisms: exudation, mechanical cell lysis and infection by the lytic phage S-SM1. A broad, untargeted analytical approach reveals the complexity of this freshly sourced DOM, and comparative analysis between DOM produced by the different mechanisms suggests that exudation and viral lysis are sources of unsaturated, oxygen-rich and possibly novel biomolecules. Furthermore, viral lysis of WH7803 by S-SM1 releases abundant peptides derived from specific proteolysis of the major light-harvesting protein phycoerythrin, raising the possibility that phage infection of these abundant cyanobacteria could be a significant source of high molecular weight dissolved organic nitrogen compounds.

Clerodane furanoditerpenoids as the probable cause of toxic hepatitis induced by Tinospora crispa

Tinospora crispa is a popular traditional herbal plant commonly used throughout the world for treatment of various diseases, in particular type 2 diabetes mellitus. We report here a new case of toxic hepatitis in a 57-year old male patient in the French West Indies following the consumption of two aqueous extracts of fresh Tinospora crispa stems. It thus differs from two previously reported cases that concerned the chronic intake of powdered dry stems delivered in solid oral dosage forms (i.e. pellets and tablets). Liquid Chromatography-Diode Array Detection-Mass Spectrometry (LC/DAD/MS) analyses were performed on an aqueous extract of the offending sample that mimics the swallowed preparation. They revealed the presence of species-specific molecular marker borapetoside C (1) and thus enabled an unambiguous phytochemical identification. The exploration of tandem MS/MS data obtained by ultra-high performance liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-HRMS) allowed the identification of 17 additional cis-clerodane-type furanoditerpenoid lactones, analogues of 1. These results support the hypothesis that the mechanisms underlying hepatotoxicity of Tinospora crispa are the same as those encountered with furanoditerpenoids-containing plants such as Teucrium chamaedrys or Dioscorea bulbifera. In the context of type 2 diabetes treatment, we recommend that Tinospora crispa intake should be more closely monitored for signs of hepatotoxicity.

Identification of Enantiomeric Byproducts During Microalgae-Mediated Transformation of Metoprolol by MS/MS Spectrum Based Networking

Metoprolol (MPL) is a chiral β-blocker ubiquitously detected in various environments due to its low to moderate removal in wastewater treatment plants. This study was conducted to test the potential of using microalgae to degrade emerging contaminant MPL and to characterize the enantiomeric enrichment during MPL degradation by microalgae. The results showed that PO₄³⁻- P, NO₃⁻- N and MPL could be simultaneously removed in the synthetic effluent by the targeted microalgae species, indicating microalgae were promising in wastewater treatment. Stereoselectivity was observed during MPL degradation by microalgae, with R-form enrichment. A marginal linear relationship between MPL degradation and enantiomeric enrichment was observed, implying that the enantiomeric tool, used as a quantitative indicator of biodegradation, could possibly be applied in MPL degradation by microalgae. An efficient liquid chromatograph tandem high resolution mass spectrometry (LC-HRMS/MS) chiral analytical method was developed to identify transformation products (TPs). The results showed that MS/MS spectral similarity networking could be used as a powerful tool to quickly identify unknown TPs. A total of 6 pairs of chiral TPs were identified, among which two new TPs of MPL including hydroxy{4-[2-hydroxy-3-(isopropylamino)propoxy]phenyl}acetic acid (α-HMPLA) and 4-[2-Hydroxy-3-(isopropylamino)propoxy]benzaldehyde (DMPLD) were firstly reported, and proposed transformation pathways of MPL by microalgae were given. Considering the paired TPs detected and that the degradation of the two enantiomers followed first order kinetics, the two enantiomers likely had the same degradation mechanism.

Molecular Networking-Based Metabolome and Bioactivity Analyses of Marine-Adapted Fungi Co-cultivated With Phytopathogens

Fungi represent a rich source of bioactive metabolites and some are marketed as alternatives to synthetic agrochemicals against plant pathogens. However, the culturability of fungal strains in artificial laboratory conditions is still limited and the standard mono-cultures do not reflect their full spectrum chemical diversity. Phytopathogenic fungi and bacteria have successfully been used in the activation of cryptic biosynthetic pathways to promote the production of new secondary metabolites in co-culture experiments. The aim of this study was to map the fungal diversity of Windebyer Noor, a brackish lake connected to Baltic Sea (Germany), to induce the chemical space of the isolated marine-adapted fungi by co-culturing with phytopathogens, and to assess their inhibitory potential against six commercially important phytopathogens. Out of 123 marine-adapted fungal isolates obtained, 21 were selected based on their phylogenetic and metabolite diversity. They were challenged with two phytopathogenic bacteria (Pseudomonas syringae and Ralstonia solanacearum) and two phytopathogenic fungi (Magnaporthe oryzae and Botrytis cinerea) on solid agar. An in-depth untargeted metabolomics approach incorporating UPLC-QToF-HRMS/MS-based molecular networking (MN), in silico MS/MS databases, and manual dereplication was employed for comparative analysis of the extracts belonging to nine most bioactive co-cultures and their respective mono-cultures. The phytopathogens triggered interspecies chemical communications with marine-adapted fungi, leading to the production of new compounds and enhanced expression of known metabolites in co-cultures. MN successfully generated a detailed map of the chemical inventory of both mono- and co-cultures. We annotated overall 18 molecular clusters (belonging to terpenes, alkaloids, peptides, and polyketides), 9 of which were exclusively produced in co-cultures. Several clusters contained compounds, which could not be annotated to any known compounds, suggesting that they are putatively new metabolites. Direct antagonistic effects of the marine-adapted fungi on the phytopathogens were observed and anti-phytopathogenic activity was demonstrated.The untargeted metabolomics approach combined with bioactivity testing allowed prioritization of two co-cultures for purification and characterization of marine fungal metabolites with crop-protective activity. To our knowledge, this is the first study employing plant pathogens to challenge marine-adapted fungi.

Structure-based manual screening and automatic networking for systematically exploring sansanmycin analogues using high performance liquid chromatography tandem mass spectroscopy

Sansanmycins (SS), one of several known uridyl peptide antibiotics (UPAs) possessing a unique chemical scaffold, showed a good inhibitory effect on the highly refractory pathogens Pseudomonas aeruginosa and Mycobacterium tuberculosis, especially on the multi-drug resistant M. tuberculosis. This study employed high performance liquid chromatography-mass spectrometry detector (HPLC-MSD) ion trap and LTQ orbitrap tandem mass spectrometry (MS/MS) to explore sansanmycin analogues manually and automatically by re-analysis of the Streptomyces sp. SS fermentation broth. The structure-based manual screening method, based on analysis of the fragmentation pathway of known UPAs and on comparisons of the MS/MS spectra with that of sansanmycin A (SS-A), resulted in identifying twenty sansanmycin analogues, including twelve new structures (1-12). Furthermore, to deeply explore sansanmycin analogues, we utilized a GNPS based molecular networking workflow to re-analyze the HPLC-MS/MS data automatically. As a result, eight more new sansanmycins (13-20) were discovered. Compound 1 was discovered to lose two amino acids of residue 1 (AA₁) and (2S, 3S)-N³-methyl-2,3-diamino butyric acid (DABA) from the N-terminus, and compounds 6, 11 and 12 were found to contain a 2',3'-dehydrated 4',5'-enamine-3'-deoxyuridyl moiety, which have not been reported before. Interestingly, three trace components with novel 5,6-dihydro-5'-aminouridyl group (16-18) were detected for the first time in the sansanmycin-producing strain. Their structures were primarily determined by detail analysis of the data from MS/MS. Compounds 8 and 10 were further confirmed by nuclear magnetic resonance (NMR) data, which proved the efficiency and accuracy of the method of HPLC-MS/MS for exploration of novel UPAs. Comparing to manual screening, the networking method can provide systematic visualization results. Manual screening and networking method may complement with each other to facilitate the mining of novel UPAs.

A tutorial in small molecule identification via electrospray ionization-mass spectrometry: The practical art of structural elucidation

The identification of unknown molecules has been one of the cornerstone applications of mass spectrometry for decades. This tutorial reviews the basics of the interpretation of electrospray ionization-based MS and MS/MS spectra in order to identify small-molecule analytes (typically below 2000 Da). Most of what is discussed in this tutorial also applies to other atmospheric pressure ionization methods like atmospheric pressure chemical/photoionization. We focus primarily on the fundamental steps of MS-based structural elucidation of individual unknown compounds, rather than describing strategies for large-scale identification in complex samples. We critically discuss topics like the detection of protonated and deprotonated ions ([M + H]+ and [M - H]- ) as well as other adduct ions, the determination of the molecular formula, and provide some basic rules on the interpretation of product ion spectra. Our tutorial focuses primarily on the fundamental steps of MS-based structural elucidation of individual unknown compounds (eg, contaminants in chemical production, pharmacological alteration of drugs), rather than describing strategies for large-scale identification in complex samples. This tutorial also discusses strategies to obtain useful orthogonal information (UV/Vis, H/D exchange, chemical derivatization, etc) and offers an overview of the different informatics tools and approaches that can be used for structural elucidation of small molecules. It is primarily intended for beginning mass spectrometrists and researchers from other mass spectrometry sub-disciplines that want to get acquainted with structural elucidation are interested in some practical tips and tricks.

Mining for Microbial Gems: Integrating Proteomics in the Postgenomic Natural Product Discovery Pipeline

Natural products (NPs) are a major source of compounds for medical, agricultural, and biotechnological industries. Many of these compounds are of microbial origin, and, in particular, from Actinobacteria or filamentous fungi. To successfully identify novel compounds that correlate to a bioactivity of interest, or discover new enzymes with desired functions, systematic multiomics approaches have been developed over the years. Bioinformatics tools harness the rapidly expanding wealth of genome sequence information, revealing previously unsuspected biosynthetic diversity. Varying growth conditions or application of elicitors are applied to activate cryptic biosynthetic gene clusters, and metabolomics provide detailed insights into the NPs they specify. Combining these technologies with proteomics-based approaches to profile the biosynthetic enzymes provides scientists with insights into the full biosynthetic potential of microorganisms. The proteomics approaches include enrichment strategies such as employing activity-based probes designed by chemical biology, as well as unbiased (quantitative) proteomics methods. In this review, the opportunities and challenges in microbial NP research are discussed, and, in particular, the application of proteomics to link biosynthetic enzymes to the molecules they produce, and vice versa.

Niche partitioning of a pathogenic microbiome driven by chemical gradients

Environmental microbial communities are stratified by chemical gradients that shape the structure and function of these systems. Similar chemical gradients exist in the human body, but how they influence these microbial systems is more poorly understood. Understanding these effects can be particularly important for dysbiotic shifts in microbiome structure that are often associated with disease. We show that pH and oxygen strongly partition the microbial community from a diseased human lung into two mutually exclusive communities of pathogens and anaerobes. Antimicrobial treatment disrupted this chemical partitioning, causing complex death, survival, and resistance outcomes that were highly dependent on the individual microorganism and on community stratification. These effects were mathematically modeled, enabling a predictive understanding of this complex polymicrobial system. Harnessing the power of these chemical gradients could be a drug-free method of shaping microbial communities in the human body from undesirable dysbiotic states.

Assembling the Community-Scale Discoverable Human Proteome

The increasing throughput and sharing of proteomics mass spectrometry data have now yielded over one-third of a million public mass spectrometry runs. However, these discoveries are not continuously aggregated in an open and error-controlled manner, which limits their utility. To facilitate the reusability of these data, we built the MassIVE Knowledge Base (MassIVE-KB), a community-wide, continuously updating knowledge base that aggregates proteomics mass spectrometry discoveries into an open reusable format with full provenance information for community scrutiny. Reusing >31 TB of public human data stored in a mass spectrometry interactive virtual environment (MassIVE), the MassIVE-KB contains >2.1 million precursors from 19,610 proteins (48% larger than before; 97% of the total) and doubles proteome coverage to 6 million amino acids (54% of the proteome) with strict library-scale false discovery controls, thereby providing evidence for 430 proteins for which sufficient protein-level evidence was previously missing. Furthermore, MassIVE-KB can inform experimental design, helps identify and quantify new data, and provides tools for community construction of specialized spectral libraries.

Wang et al. introduce MassIVE-KB, a program designed to distill the entire community’s mass spectrometry data into reusable spectral library resources. As a result, the statistically-significant discovery of a peptide or protein in a single researcher’s data will thus be made available to the whole community to support its identification (in shotgun experiments) or quantitative detection (in targeted experiments) in all future analyses.

The plant pathogen Pseudomonas aeruginosa triggers a DELLA-dependent seed germination arrest in Arabidopsis

To anticipate potential seedling damage, plants block seed germination under unfavorable conditions. Previous studies investigated how seed germination is controlled in response to abiotic stresses through gibberellic and abscisic acid signaling. However, little is known about whether seeds respond to rhizosphere bacterial pathogens. We found that Arabidopsis seed germination is blocked in the vicinity of the plant pathogen Pseudomonas aeruginosa. We identified L-2-amino-4-methoxy-trans-3-butenoic acid (AMB), released by P. aeruginosa, as a biotic compound triggering germination arrest. We provide genetic evidence that in AMB-treated seeds DELLA factors promote the accumulation of the germination repressor ABI5 in a GA-independent manner. AMB production is controlled by the quorum sensing system IQS. In vitro experiments show that the AMB-dependent germination arrest protects seedlings from damage induced by AMB. We discuss the possibility that this could serve as a protective response to avoid severe seedling damage induced by AMB and exposure to a pathogen.

The plant embryo within a seed is well protected. While it cannot stay within the seed forever, the embryo can often wait for the right conditions before it develops into a seedling and continues its life cycle. Indeed, plants have evolved several ways to time this process – which is known as germination – to maximize the chances that their seedlings will survive. For example, if the environment is too hot or too dark, the seed will make a hormone that stops it from germinating.

In addition to environmental factors like light and temperature, a seed in the real word is continuously confronted with soil microbes that may harm or benefit the plant. However, few researchers have asked whether seeds control their germination in response to other living organisms.

The bacterium Pseudomonas aeruginosa lives in a wide spectrum of environments, including the soil, and can cause diseases in both and plants and animals. Chahtane et al. now report that seeds of the model plant Arabidopsis thaliana do indeed repress their germination when this microbe is present. Specifically, the seeds respond to a molecule released from the bacteria called L-2-amino-4-methoxy-trans-3-butenoic acid, or AMB for short. Like the bacteria, AMB is harmful to young seedlings, but Chahtane et al. showed that the embryo within the seed is protected from its toxic effects.

Further experiments revealed that the seed's response to the bacterial molecule requires many of the same signaling components that repress germination when environmental conditions are unfavorable. However, Chahtane et al. note that AMB activates these components in an unusual way that they still do not understand.

The genes that control the production of AMB are known to also control how bacterial populations behave as they accumulate to high densities. It is therefore likely that Pseudomonas aeruginosa would make AMB if it reached a high density in the soil. This raises the possibility that plants have specifically evolved to stop germination if there are enough microbes nearby to pose a risk of disease. This hypothesis, however, is only one of several possible explanations and remains speculative at this stage; further work is now needed to evaluate it. Nevertheless, identifying how AMB interferes with the signaling components that control germination and plant growth may guide the design of new herbicides that could, for example, control weeds in the farming industry.

Targeted Isolation of Neuroprotective Dicoumaroyl Neolignans and Lignans from Sageretia theezans Using in Silico Molecular Network Annotation Propagation-Based Dereplication

The integration of LC-MS/MS molecular networking and in silico MS/MS fragmentation is an emerging method for dereplication of natural products. In the present study, a targeted isolation of natural products using a new in silico-based annotation tool named Network Annotation Propagation (NAP) is described. NAP improves accuracy of in silico fragmentation analyses by reranking candidate structures based on the network topology from MS/MS-based molecular networking. Annotation for the MS/MS spectral network of the Sageratia theezans twig extract was performed using NAP, and most molecular families within the network, including the known triterpenoids 1-7, could be putatively annotated, without relying on any previous reports of molecules from this species. Based on the in silico dereplication results, molecules were prioritized for isolation. In total, six dicoumaroyl 8- O-4' neolignans (8-13) and three dicoumaroyl lignans (14-16) were isolated from the twigs of S. theezans and structurally characterized by spectroscopic analyses. Isolates were evaluated for their neuroprotective activity, and compounds 14-16 showed potent protective effects against glutamate-induced oxidative stress in mouse HT22 cells at a concentration of 12.5 μM.

Coproporphyrin III Produced by the Bacterium Glutamicibacter arilaitensis Binds Zinc and Is Upregulated by Fungi in Cheese Rinds

Bacterium-fungus interactions play key roles in the assembly of cheese rind microbial communities, but the molecular mechanisms underlying these interactions are poorly characterized. Moreover, millions of people around the world enjoy eating cheeses and cheese rinds, but our understanding of the diversity of microbial metabolites ingested during cheese consumption is limited. The discovery of zinc coproporphyrin III as the cause of pink pigment production by Glutamicibacter arilaitensis suggests that secretion of this molecule is important for microbial acquisition of trace metals.

Microbial communities of fermented food microbiomes typically exhibit predictable patterns of microbial succession. However, the biochemical mechanisms that control the diversity and dynamics of these communities are not well described. Interactions between bacteria and fungi may be one mechanism controlling the development of cheese rind microbiomes. This study characterizes a specific bacterium-fungus interaction previously discovered on cheese rinds between the bacterium Glutamicibacter arilaitensis (formerly Arthrobacter arilaitensis) and fungi of the genus Penicillium and identifies the specialized metabolites produced during cocultures. G. arilaitensis was previously shown to produce an unknown pink pigment in response to the presence of Penicillium. Using a combination of mass spectrometry, nuclear magnetic resonance (NMR), and transcriptome sequencing (RNA-seq), we determined that this pigment production is associated with production of coproporphyrin III. The discovery that coproporphyrin III preferentially bound zinc over other trace metals found in cheese curds highlights the value of using analytical chemistry to confirm identity of predicted chemical species.

IMPORTANCE Bacterium-fungus interactions play key roles in the assembly of cheese rind microbial communities, but the molecular mechanisms underlying these interactions are poorly characterized. Moreover, millions of people around the world enjoy eating cheeses and cheese rinds, but our understanding of the diversity of microbial metabolites ingested during cheese consumption is limited. The discovery of zinc coproporphyrin III as the cause of pink pigment production by Glutamicibacter arilaitensis suggests that secretion of this molecule is important for microbial acquisition of trace metals.

Author Video: An author video summary of this article is available.

Before platelets: the production of platelet-activating factor during growth and stress in a basal marine organism

Corals and humans represent two extremely disparate metazoan lineages and are therefore useful for comparative evolutionary studies. Two lipid-based molecules that are central to human immunity, platelet-activating factor (PAF) and Lyso-PAF were recently identified in scleractinian corals. To identify processes in corals that involve these molecules, PAF and Lyso-PAF biosynthesis was quantified in conditions known to stimulate PAF production in mammals (tissue growth and exposure to elevated levels of ultraviolet light) and in conditions unique to corals (competing with neighbouring colonies over benthic space). Similar to observations in mammals, PAF production was higher in regions of active tissue growth and increased when corals were exposed to elevated levels of ultraviolet light. PAF production also increased when corals were attacked by the stinging cells of a neighbouring colony, though only the attacked coral exhibited an increase in PAF. This reaction was observed in adjacent areas of the colony, indicating that this response is coordinated across multiple polyps including those not directly subject to the stress. PAF and Lyso-PAF are involved in coral stress responses that are both shared with mammals and unique to the ecology of cnidarians.

Fate and Biological Activity of the Antimicrobial Lasso Peptide Microcin J25 Under Gastrointestinal Tract Conditions

The bacteriocin microcin J25 (MccJ25) inhibits the growth of Gram-negative pathogens including Salmonella and Shigella species, and Escherichia coli. This 21-amino acid peptide has remarkable stability to heat and extreme pH values and resistance to many proteases, thanks to a characteristic lasso structure. In this study, we used the dynamic simulator TIM-1 as gastro-intestinal tract model to evaluate the stability and antibacterial activity of MccJ25 during passage through the proximal portion of the human gastrointestinal tract. MccJ25 concentration was measured in the different simulator sections by HPLC, and inhibition of Salmonella enterica serotype Enteritidis was evaluated using qualitative and quantitative assays. LC-MS/MS analysis and subsequent molecular networking analysis on the Global Natural Product Social Molecular Networking platform (GNPS) and analysis of the peptide degradation in the presence of proteolytic enzymes mimicking the gastro-intestinal conditions permitted to delineate the fate of MccJ25 through identification of the main degradation products. MccJ25 was relatively stable under gastric conditions, but degraded rapidly in the compartment mimicking the duodenum, notably in the presence of pancreatin. Among pancreatin components, elastase I appeared primarily responsible for MccJ25 breakdown, while α-chymotrypsin was less efficient.

Targeted Isolation of Tsitsikammamines from the Antarctic Deep-Sea Sponge Latrunculia biformis by Molecular Networking and Anticancer Activity

The Antarctic deep-sea sponge Latrunculia (Latrunculia) biformis Kirkpatrick, 1908 (Class Demospongiae Sollas, Order Poecilosclerida Topsent, Latrunculiidae Topsent) was selected for chemical analyses due to its potent anticancer activity. Metabolomic analysis of its crude extract by HRMS/MS-based molecular networking showed the presence of several clusters of pyrroloiminoquinone alkaloids, i.e., discorhabdin and epinardin-type brominated pyridopyrroloquinolines and tsitsikammamines, the non-brominated bis-pyrroloiminoquinones. Molecular networking approach combined with a bioactivity-guided isolation led to the targeted isolation of the known pyrroloiminoquinone tsitsikammamine A (1) and its new analog 16,17-dehydrotsitsikammamine A (2). The chemical structures of the compounds 1 and 2 were elucidated by spectroscopic analysis (one-dimensional (1D) and two-dimensional (2D) NMR, HR-ESIMS). Due to minute amounts, molecular modeling and docking was used to assess potential affinities to potential targets of the isolated compounds, including DNA intercalation, topoisomerase I-II, and indoleamine 2,3-dioxygenase enzymes. Tsitsikammamines represent a small class of pyrroloiminoquinone alkaloids that have only previously been reported from the South African sponge genus Tsitsikamma Samaai & Kelly and an Australian species of the sponge genus Zyzzya de Laubenfels. This is the first report of tsitsikammamines from the genus Latrunculia du Bocage and the successful application of molecular networking in the identification of comprehensive chemical inventory of L.biformis followed by targeted isolation of new molecules. This study highlights the high productivity of secondary metabolites of Latrunculia sponges and may shed new light on their biosynthetic origin and chemotaxonomy.