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Abstract SbtB is a PII-like protein that regulates the carbon-concentrating mechanism (CCM) in cyanobacteria. SbtB proteins can bind many adenyl nucleotides and possess a characteristic C-terminal redox sensitive loop (R-loop) that forms a disulfide bridge in response to the diurnal state of the cell. SbtBs also possess an ATPase/ADPase activity that is modulated by the redox-state of the R-loop. To investigate the R-loop in the cyanobacterium Synechocystis sp. PCC 6803, site-specific mutants, unable to form the hairpin and permanently in the reduced state, and a R-loop truncation mutant, were characterized under different inorganic carbon (Ci) and light regimes. Growth under diurnal rhythm showed a role of the R-loop as sensor for acclimation to changing light conditions. The redox-state of the R-loop was found to impact the binding of the adenyl-nucleotides to SbtB, its membrane association and thereby the CCM regulation, while these phenotypes disappeared after truncation of the R-loop. Collectively, our data imply that the redox-sensitive R-loop provides an additional regulatory layer to SbtB, linking the CO2-related signaling activity of SbtB with the redox state of cells, mainly reporting the actual light conditions. This regulation not only coordinates CCM activity in the diurnal rhythm but also affects the primary carbon metabolism.

Abstract Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or “suspects,” were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Abstract Antibiotics are central to modern medicine, and yet they are mainly the products of intra and inter-kingdom evolutionary warfare. To understand how nature evolves antibiotics around a common mechanism of action, we investigated the origins of an extremely valuable class of compounds, lipid II targeting glycopeptide antibiotics (GPAs, exemplified by teicoplanin and vancomycin), which are used as last resort for the treatment of antibiotic resistant bacterial infections. Using a molecule-centred approach and computational techniques, we first predicted the nonribosomal peptide synthetase assembly line of paleomycin, the ancestral parent of lipid II targeting GPAs. Subsequently, we employed synthetic biology techniques to produce the predicted peptide and validated its antibiotic activity. We revealed the structure of paleomycin, which enabled us to address how nature morphs a peptide antibiotic scaffold through evolution. In doing so, we obtained temporal snapshots of key selection domains in nonribosomal peptide synthesis during the biosynthetic journey from ancestral, teicoplanin-like GPAs to modern GPAs such as vancomycin. Our study demonstrates the synergy of computational techniques and synthetic biology approaches enabling us to journey back in time, trace the temporal evolution of antibiotics, and revive these ancestral molecules. It also reveals the optimisation strategies nature has applied to evolve modern GPAs, laying the foundation for future efforts to engineer this important class of antimicrobial agents.

Abstract Elective transjugular intrahepatic portosystemic shunt (TIPS) placement can worsen cognitive dysfunction in hepatic encephalopathy (HE) patients due to toxins, including possible microbial metabolites, entering the systemic circulation. We conducted untargeted metabolomics on a prospective cohort of 22 patients with cirrhosis undergoing elective TIPS placement and followed them up to one year post TIPS for HE development. Here we suggest that pre-existing intrahepatic shunting predicts HE severity post-TIPS. Bile acid levels decrease in the peripheral vein post-TIPS, and the abundances of three specific conjugated di- and tri-hydroxylated bile acids are inversely correlated with HE grade. Bilirubins and glycerophosphocholines undergo chemical modifications pre- to post-TIPS and based on HE grade. Our results suggest that TIPS-induced metabolome changes can impact HE development, and that pre-existing intrahepatic shunting could be used to predict HE severity post-TIPS.

Abstract The dominant benthic primary producers in coral reef ecosystems are complex holobionts with diverse microbiomes and metabolomes. In this study, we characterize the tissue metabolomes and microbiomes of corals, macroalgae, and crustose coralline algae via an intensive, replicated synoptic survey of a single coral reef system (Waimea Bay, Oʻahu, Hawaii) and use these results to define associations between microbial taxa and metabolites specific to different hosts. Our results quantify and constrain the degree of host specificity of tissue metabolomes and microbiomes at both phylum and genus level. Both microbiome and metabolomes were distinct between calcifiers (corals and CCA) and erect macroalgae. Moreover, our multi-omics investigations highlight common lipid-based immune response pathways across host organisms. In addition, we observed strong covariation among several specific microbial taxa and metabolite classes, suggesting new metabolic roles of symbiosis to further explore.

Lithified layers of complex microbial mats known as microbialites are ubiquitous in the fossil record, and modern forms are increasingly identified globally. A key challenge to developing an understanding of microbialite formation and environmental role is how to investigate complex and diverse communities in situ. We selected living, layered microbialites (stromatolites) in a peritidal environment near Schoenmakerskop, Eastern Cape, South Africa to conduct a spatial survey mapping the composition and small molecule production of the microbial communities from environmental samples. Substrate core samples were collected from nine sampling stations ranging from the upper point of the freshwater inflow to the lower marine interface where tidal overtopping takes place. Substrate cores provided material for parallel analyses of microbial community diversity by 16S rRNA gene amplicon sequencing and metabolomics using LC-MS2. Species and metabolite diversities were correlated, and prominent specialized metabolites were targeted for preliminary characterization. A new series of cyclic hexadepsipeptides, named ibhayipeptolides, was most abundant in substrate cores of submerged microbialites. These results demonstrate the detection and identification of metabolites from mass-limited environmental samples and contribute knowledge about microbialite chemistry and biology, which facilitates future targeted studies of specialized metabolite function and biosynthesis.

Bioactivity-guided isolation of specialized metabolites is an iterative process. Here, the authors demonstrate a native metabolomics approach that allows for fast screening of complex metabolite extracts against a protein of interest and simultaneous structure annotation.

Zinc is an essential cofactor for bacterial metabolism. Here, the authors show that the probiotic bacterium Escherichia coli Nissle 1917 utilizes the siderophore yersiniabactin as a zincophore, allowing the microbe to grow in zinc-limited media and to thrive in the inflamed gut.

Abstract Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

Untargeted metabolomics is a powerful tool for profiling the biochemical phenotypes of organisms and discovering new metabolites that drive biological function and might be exploited as pharmaceutical leads. Yet, connecting physiological processes to metabolites detected remains a challenge due to the lack of structural and activity annotations and the underlying complexity of mixed samples (e.g., multiple microorganisms, organelles, etc.). To simplify this biological complexity, we separated coral holobionts into host mitochondria and their algal symbionts prior to LC-MS/MS-based untargeted metabolomic analysis followed by molecular networking. We found distinct metabolomic profiles between tissue fractions. Notably, 14% of metabolites detected were only observed in the mitochondria and algal symbionts, not in the holobiont, and thus were masked when the bulk (holobiont) sample was analyzed. The utility of tissue separation for hypothesis testing was assessed using a simple temperature experiment. We tested the hypothesis that membrane lipids of the coral mitochondria and algal symbionts become more saturated at higher temperatures to maintain membrane rigidity. While the holobiont metabolite profiles showed little change in response to elevated temperature, there was a change in lipid saturation of both fractions through time. The fatty acid saturation of both the coral mitochondria and the algal symbionts shifted upon exposure to higher temperatures (1 h) then returned to ambient saturation levels by 4 h, indicating rapid acclimatization to warmer water. Surprisingly, the fractions deviated in opposite directions: during the first hour of the experiment, the mitochondria showed an increase in saturated lipid concentrations, while the algal symbionts showed an increase in unsaturated lipids. Partitioning the holobiont prior to untargeted metabolomic analysis revealed disparate responses to environmental stress that would have gone undetected if only the holobiont/bulk tissue was analyzed. This work illustrates rapid physiological acclimatization to environmental changes in specific host organelles and symbionts, though via different paths.

Recent developments in molecular networking have expanded our ability to characterize the metabolome of diverse samples that contain a significant proportion of ion features with no mass spectral match to known compounds. Manual and tool-assisted natural annotation propagation is readily used to classify molecular networks; however, currently no annotation propagation tools leverage consensus confidence strategies enabled by hierarchical chemical ontologies or enable the use of new in silico tools without significant modification. Herein we present ConCISE (Consensus Classifications of In Silico Elucidations) which is the first tool to fuse molecular networking, spectral library matching and in silico class predictions to establish accurate putative classifications for entire subnetworks. By limiting annotation propagation to only structural classes which are identical for the majority of ion features within a subnetwork, ConCISE maintains a true positive rate greater than 95% across all levels of the ChemOnt hierarchical ontology used by the ClassyFire annotation software (superclass, class, subclass). The ConCISE framework expanded the proportion of reliable and consistent ion feature annotation up to 76%, allowing for improved assessment of the chemo-diversity of dissolved organic matter pools from three complex marine metabolomics datasets comprising dominant reef primary producers, five species of the diatom genus Pseudo-nitzchia, and stromatolite sediment samples.

ABSTRACT Many ant species grow fungus gardens that predigest food as an essential step of the ants’ nutrient uptake. These symbiotic fungus gardens have long been studied and feature a gradient of increasing substrate degradation from top to bottom. To further facilitate the study of fungus gardens and enable the understanding of the predigestion process in more detail than currently known, we applied recent mass spectrometry-based approaches and generated a three-dimensional (3D) molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments to compare with lab-maintained ecosystems. IMPORTANCE The study of complex ecosystems requires an understanding of the chemical processes involving molecules from several sources. Some of the molecules present in fungus-growing ants’ symbiotic system originate from plants. To facilitate the study of fungus gardens from a chemical perspective, we provide a molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments.

Summary: Bacterial communities are in a continuous adaptive and evolutionary race for survival. In this work we expand our knowledge on the chemical interplay and specific mutations that modulate the transition from antagonism to co-existence between two plant-beneficial bacteria, Pseudomonas chlororaphis PCL1606 and Bacillus amyloliquefaciens FZB42. We reveal that the bacteriostatic activity of bacillaene produced by Bacillus relies on an interaction with the protein elongation factor FusA of P. chlororaphis and how mutations in this protein lead to tolerance to bacillaene and other protein translation inhibitors. Additionally, we describe how the unspecific tolerance of B. amyloliquefaciens to antimicrobials associated with mutations in the glycerol kinase GlpK is provoked by a decrease of Bacillus cell membrane permeability, among other pleiotropic responses. We conclude that nutrient specialization and mutations in basic biological functions are bacterial adaptive dynamics that lead to the coexistence of two primary competitive bacterial species rather than their mutual eradication.

The rapidly advancing field of metabolomics encompasses a diverse suite of powerful analytical and bioinformatic tools that can help to reveal the diversity and activity of chemical compounds in individual organisms, species interactions, and entire ecosystems. In this perspective we use examples from studies of coral reefs to illustrate ways in which metabolomics has been and can be applied to understand coastal ecosystems. Examples of new insights that can be provided by metabolomics include resolving metabolite exchange between plants, animals and their microbiota, identifying the relevant metabolite exchanges associated with the onset and maintenance of diverse, microbial mutualisms characterizing unknown molecules that act as cues in coral, reproduction, or defining the suites of compounds involved in coral-algal competition and microbialization of algal-dominated ecosystems. Here we outline sampling, analytical and informatic methods that marine biologists and ecologists can apply to understand the role of chemical processes in ecosystems, with a focus on open access data analysis workflows and democratized databases. Finally, we demonstrate how these metabolomics tools and bioinformatics approaches can provide scientists the opportunity to map detailed metabolic inventories and dynamics for a holistic view of the relationships among reef organisms, their symbionts and their surrounding marine environment.

Pseudomonas and Bacillus can promote plant growth but their mutual interactions are unclear. Here, the authors show that the extracellular matrix protects Bacillus colonies from infiltration by Pseudomonas cells, while the Pseudomonas type VI secretion system stimulates Bacillus sporulation.

All organisms host a diversity of associated viruses, bacteria, and protists, collectively defined as the holobiont. While scientific advancements have enhanced the understanding of the functional roles played by various components of the holobiont, there is a growing need to integrate multiple types of molecular data into spatially and temporally resolved frameworks. To that end, we mapped 16S and 18S rDNA metabarcoding, metatranscriptomics, and metabolomic data onto three-dimensional reconstructions of coral colonies to examine microbial diversity, microbial gene expression, and biochemistry on two colonies of the ecologically important, reef-building coral, Orbicella faveolata and their competitors (i.e., adjacent organisms interacting with the corals: fleshy algae, turf algae, hydrozoans, and other corals). Overall, no statistically significant spatial patterns were observed among the samples for any of the data types; instead, strong signatures of the macroorganismal hosts (e.g., coral, algae, hydrozoa) were detected, in the microbiome, the transcriptome, and the metabolome. The 16S rDNA analysis demonstrated higher abundance of Firmicutes in the coral microbiome than in its competitors. A single bacterial amplicon sequence variant from the genus Clostridium was found exclusively in all O. faveolata samples. In contrast to microbial taxa, a portion of the functionally annotated bacterial RNA transcripts (6.86%) and metabolites (1.95%) were ubiquitous in all coral and competitor samples. Machine learning analysis of microbial transcripts revealed elevated T7-like cyanophage-encoded photosystem II transcripts in O. faveolata samples, while sequences involved in bacterial cell division were elevated in turf algal and interface samples. Similar analysis of metabolites revealed that bacterial-produced antimicrobial and antifungal compounds were highly enriched in coral samples. This study provides insight into the spatial and biological patterning of the coral microbiome, transcriptome, and metabolome.

The bioavailability of organic matter (OM) to marine heterotrophic bacterioplankton is determined by both the chemical composition of OM and the microbial community composition. In the current study, changes in OM bioavailability were identified at Ocean Station Papa as part of the 2018 Export Processes in the Ocean from Remote Sensing (EXPORTS) field study. Removal rates of carbon (C) in controlled experiments were significantly correlated with the initial composition of total hydrolyzable amino acids, and C removal rates were high when the amino acid degradation index suggested a more labile composition. Carbon remineralization rates averaged 0.19 ± 0.08 μmol C L–1 d–1 over 6–10 days while bacterial growth efficiencies averaged 31 ± 7%. Amino acid composition and tandem mass spectrometry analysis of compound classes also revealed transformations to a more degraded OM composition during experiments. There was a log2-fold increase in the relative abundances of 16S rDNA-resolved bacterioplankton taxa in most experiments by members of the Methylophilaceae family (OM43 genus) and KI89A order. Additionally, when OM was more bioavailable, relative abundances increased by at least threefold for the classes Bacteroidetes (Flavobacteriaceae NS2b genus), Alphaproteobacteria (Rhodobacteraceae Sulfitobacter genus), and Gammaproteobacteria (Alteromonadales and Ectothiorhodospiraceae orders). Our data suggest that a diverse group of bacterioplankton was responsible for removing organic carbon and altering the OM composition to a more degraded state. Elevated community diversity, as inferred from the Shannon–Wiener H index, may have contributed to relatively high growth efficiencies by the bacterioplankton. The data presented here shed light on the interconnections between OM bioavailability and key bacterioplankton taxa for the degradation of marine OM.

The potent antibacterial compound albicidin is synthesized by the plant-pathogenic bacterium Xanthomonas albilineans. Here the authors employ a multidisciplinary approach and provide structural and mechanistic insights into how the drug-binding protein AlbA confers albicidin resistance to Klebsiella oxytoca.

Abstract Background Fungal cyclodepsipeptides (CDPs) are non-ribosomally synthesized peptides produced by a variety of filamentous fungi and are of interest to the pharmaceutical industry due to their anticancer, antimicrobial and anthelmintic bioactivities. However, both chemical synthesis and isolation of CDPs from their natural producers are limited due to high costs and comparatively low yields. These challenges might be overcome by heterologous expression of the respective CDP-synthesizing genes in a suitable fungal host. The well-established industrial fungus Aspergillus niger was recently genetically reprogrammed to overproduce the cyclodepsipeptide enniatin B in g/L scale, suggesting that it can generally serve as a high production strain for natural products such as CDPs. In this study, we thus aimed to determine whether other CDPs such as beauvericin and bassianolide can be produced with high titres in A. niger, and whether the generated expression strains can be used to synthesize new-to-nature CDP derivatives. Results The beauvericin and bassianolide synthetases were expressed under control of the tuneable Tet-on promoter, and titres of about 350–600 mg/L for bassianolide and beauvericin were achieved when using optimized feeding conditions, respectively. These are the highest concentrations ever reported for both compounds, whether isolated from natural or heterologous expression systems. We also show that the newly established Tet-on based expression strains can be used to produce new-to-nature beauvericin derivatives by precursor directed biosynthesis, including the compounds 12-hydroxyvalerate-beauvericin and bromo-beauvericin. By feeding deuterated variants of one of the necessary precursors (d-hydroxyisovalerate), we were able to purify deuterated analogues of beauvericin and bassianolide from the respective A. niger expression strains. These deuterated compounds could potentially be used as internal standards in stable isotope dilution analyses to evaluate and quantify fungal spoilage of food and feed products. Conclusion In this study, we show that the product portfolio of A. niger can be expanded from enniatin to other CDPs such as beauvericin and bassianolide, as well as derivatives thereof. This illustrates the capability of A. niger to produce a range of different peptide natural products in titres high enough to become industrially relevant.

The Estremadura Spur pockmarks are a unique and unexplored ecosystem located in the North Atlantic, off the coast of Portugal. A total of 85 marine-derived actinomycetes were isolated and cultured from sediments collected from this ecosystem at a depth of 200 to 350 m. Nine genera, Streptomyces, Micromonospora, Saccharopolyspora, Actinomadura, Actinopolymorpha, Nocardiopsis, Saccharomonospora, Stackebrandtia, and Verrucosispora were identified by 16S rRNA gene sequencing analyses, from which the first two were the most predominant. Non-targeted LC-MS/MS, in combination with molecular networking, revealed high metabolite diversity, including several known metabolites, such as surugamide, antimycin, etamycin, physostigmine, desferrioxamine, ikarugamycin, piericidine, and rakicidin derivatives, as well as numerous unidentified metabolites. Taxonomy was the strongest parameter influencing the metabolite production, highlighting the different biosynthetic potentials of phylogenetically related actinomycetes; the majority of the chemical classes can be used as chemotaxonomic markers, as the metabolite distribution was mostly genera-specific. The EtOAc extracts of the actinomycete isolates demonstrated antimicrobial and antioxidant activity. Altogether, this study demonstrates that the Estremadura Spur is a source of actinomycetes with potential applications for biotechnology. It highlights the importance of investigating actinomycetes from unique ecosystems, such as pockmarks, as the metabolite production reflects their adaptation to this habitat.

Momordica plant species (Cucurbitaceae), have been used for centuries in traditional medicine and for nutritional purposes. Plants from this family are thus claimed to be phytochemically rich, representing an inexhaustible source of natural products. However, the chemical space of these Momordica species has not yet been fully decoded, and due to the inherent complexity of plant metabolomes, the characterization of the Momordica phytochemistry remains challenging. Thus, in this study we propose the use of molecular networking to unravel the molecular families within the metabolomes of four Momordica species (M. cardiospermoides, M. balsamina, M. charantia and M. foetida) and highlight the relevance of molecular networking in exploring the chemotaxonomy of these plants. In silico annotation tools (Network Annotation Propagation and DEREPLICATOR) and an unsupervised substructure identification tool (MS2LDA) were also explored to complement the classical molecular networking output and integration using MolNetEnhancer within GNPS. This allowed for the visualisation of chemical classes and the variety of substructures within the molecular families. The use of computational tools in this study highlighted various classes of metabolites, such as a wide range of flavonoids, terpenoids and lipids. Herein, these species are revealed to be phytochemically rich plants consisting of many biologically active metabolites differentially distributed within the different species, with the metabolome of M. cardiospermoides dereplicated in this paper for the first time.

Humic substance (HS)-based biostimulants show potentials as sustainable strategies for improved crop development and stress resilience. However, cellular and molecular mechanisms governing the agronomically observed effects of HS on plants remain enigmatic. Here, we report a global metabolic reprogramming of maize leaves induced by a humic biostimulant under normal and nutrient starvation conditions. This reconfiguration of the maize metabolism spanned chemical constellations, as revealed by molecular networking approaches. Plant growth and development under normal conditions were characterized by key differential metabolic changes such as increased levels of amino acids, oxylipins and the tricarboxylic acid (TCA) intermediate, isocitric acid. Furthermore, under starvation, the humic biostimulant significantly impacted pathways that are involved in stress-alleviating mechanisms such as redox homeostasis, strengthening of the plant cell wall, osmoregulation, energy production and membrane remodelling. Thus, this study reveals that the humic biostimulant induces a remodelling of inter-compartmental metabolic networks in maize, subsequently readjusting the plant physiology towards growth promotion and stress alleviation. Such insights contribute to ongoing efforts in elucidating modes of action of biostimulants, generating fundamental scientific knowledge that is necessary for development of the biostimulant industry, for sustainable food security.

Matching fragment spectra to reference library spectra is an important procedure for annotating small molecules in untargeted mass spectrometry based metabolomics studies. Here, the authors develop strategies to estimate false discovery rates (FDR) by empirical Bayes and target-decoy based methods which enable a user to define the scoring criteria for spectral matching.

Abstract In this paper we discuss recent significant developments in the field of venom research, specifically the emergence of top-down proteomic applications that allow achieving compositional resolution at the level of the protein species present in the venom, and the absolute quantification of the venom proteins (the term “protein species” is used here to refer to all the different molecular forms in which a protein can be found. Please consult the special issue of Jornal of Proteomics “Towards deciphering proteomes via the proteoform, protein speciation, moonlighting and protein code concepts” published in 2016, vol. 134, pages 1-202). Challenges remain to be solved in order to achieve a compact and automated platform with which to routinely carry out comprehensive quantitative analysis of all toxins present in a venom. This short essay reflects the authors’ view of the immediate future in this direction for the proteomic analysis of venoms, particularly of snakes.

Venom is a known source of novel antimicrobial natural products. The substantial, increasing number of these discoveries have unintentionally culminated in the misconception that venom and venom-producing glands are largely sterile environments. Culture-dependent and -independent studies on the microbial communities in venom microenvironments reveal the presence of archaea, algae, bacteria, fungi, protozoa, and viruses. Venom-centric microbiome studies are relatively sparse to date with the adaptive advantages that venom-associated microbes might offer to their hosts, or that hosts might provide to venom-associated microbes, remaining largely unknown. We highlight the potential for the discovery of venom microbiomes within the adaptive landscape of venom systems. The considerable number of convergently evolved venomous animals, juxtaposed with the comparatively few known studies to identify microbial communities in venom, provides new possibilities for both biodiversity and therapeutic discoveries. We present an evidence-based argument for integrating microbiology as part of venomics (i.e., venom-microbiomics) and introduce iVAMP, the Initiative for Venom Associated Microbes and Parasites (https://ivamp-consortium.github.io/), as a growing collaborative consortium. We express commitment to the diversity, inclusion and scientific collaboration among researchers interested in this emerging subdiscipline through expansion of the iVAMP consortium. Keywords: Bacteria, Coevolution, Holobiont, Microbiome, Symbiont, Virus

Dissolved organic matter (DOM) is arguably one of the most complex exometabolomes on earth, and is comprised of thousands of compounds, that together contribute more than 600 × 1015 g carbon. This reservoir is primarily the product of interactions between the upper ocean's microbial food web, yet abiotic processes that occur over millennia have also modified many of its molecules. The compounds within this reservoir play important roles in determining the rate and extent of element exchange between inorganic reservoirs and the marine biosphere, while also mediating microbe-microbe interactions. As such, there has been a widespread effort to characterize DOM using high-resolution analytical methods including nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). To date, molecular information in DOM has been primarily obtained through calculated molecular formulas from exact mass. This approach has the advantage of being non-targeted, accessing the inherent complexity of DOM. Molecular structures are however still elusive and the most commonly used instruments are costly. More recently, tandem mass spectrometry has been employed to more precisely identify DOM components through comparison to library mass spectra. Here we describe a data acquisition and analysis workflow that expands the repertoire of high-resolution analytical approaches available to access the complexity of DOM molecules that are amenable to electrospray ionization (ESI) MS. We couple liquid chromatographic separation with tandem MS (LC-MS/MS) and a data analysis pipeline, that integrates peak extraction from extracted ion chromatograms (XIC), molecular formula calculation and molecular networking. This provides more precise structural characterization. Although only around 1% of detectable DOM compounds can be annotated through publicly available spectral libraries, community-wide participation in populating and annotating DOM datasets could rapidly increase the annotation rate and should be broadly encouraged. Our analysis also identifies shortcomings of the current data analysis workflow that need to be addressed by the community in the future. This work will lay the foundation for an integrative, non-targeted molecular analysis of DOM which, together with next generation sequencing, meta-proteomics and physical data, will pave the way to a more comprehensive understanding of the role of DOM in structuring marine ecosystems.

Abstract Following publication of the original article [1], the authors reported that there is a mistake in the legend of Figure 4; the explanation of the symbols has been mixed up. The corrected version of Figure 4 is given below.

Snake venoms are extremely important for alternative medicine applications and discovery of new bioactive molecules. Especially in the recent years, there are promising studies in the literature on the development of new therapies for targeting the cancer with the use of snake venom peptides. In the present study, PLA2 and SVMPs venom peptide fractions of M. bulgardaghica were investigated for their apoptotic effects on human cervix adenocarcinoma cell line, HeLa and human lung adenocarcinoma cell line, A549. The cytotoxicity of crude venom was assessed by MTT assay with IC50 values of 4.34 ± 0.19 and 2.60 ± 0.18 µg/mL against HeLa and A549 cells, respectively. Following treatment, the cells with fractions for 48 h, the percentage of apoptotic cells was quantified by Annexin V/PI double staining assay and analyzed with flow cytometry. Our results show that, M. bulgardaghica venom fractions weren’t significantly triggered apoptotic effect on cells but affected the cell cycle in PI staining experiments. As a result, snake venom peptides might have potential use in the treatment of cancer with new drug targeting techniques.