Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.

Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.

Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow.

Illuminating the dark metabolome of Pseudo-nitzschia-microbiome associations.

The exchange of metabolites mediates algal and bacterial interactions that maintain ecosystem function. Yet, while thousands of metabolites are produced, only a few molecules have been identified in these associations. Using the ubiquitous microalgae Pseudo-nitzschia sp., as a model, we employed an untargeted metabolomics strategy to assign structural characteristics to the metabolites that distinguished specific diatom-microbiome associations. We cultured five species of Pseudo-nitzschia, including two species that produced the toxin domoic acid, and examined their microbiomes and metabolomes. A total of 4826 molecular features were detected by tandem mass spectrometry. Only 229 of these could be annotated using available mass spectral libraries, but by applying new in silico annotation tools, characterization was expanded to 2710 features. The metabolomes of the Pseudo-nitzschia-microbiome associations were distinct and distinguished by structurally diverse nitrogen compounds, ranging from simple amines and amides to cyclic compounds such as imidazoles, pyrrolidines and lactams. By illuminating the dark metabolomes, this study expands our capacity to discover new chemical targets that facilitate microbial partnerships and uncovers the chemical diversity that underpins algae-bacteria interactions.

SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information.

Mass spectrometry is a predominant experimental technique in metabolomics and related fields, but metabolite structural elucidation remains highly challenging. We report SIRIUS 4 (https://bio.informatik.uni-jena.de/sirius/), which provides a fast computational approach for molecular structure identification. SIRIUS 4 integrates CSI:FingerID for searching in molecular structure databases. Using SIRIUS 4, we achieved identification rates of more than 70% on challenging metabolomics datasets.

Bayesian networks for mass spectrometric metabolite identification via molecular fingerprints.

Motivation: Metabolites, small molecules that are involved in cellular reactions, provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem mass spectrometry to identify the thousands of compounds in a biological sample. Recently, we presented CSI:FingerID for searching in molecular structure databases using tandem mass spectrometry data. CSI:FingerID predicts a molecular fingerprint that encodes the structure of the query compound, then uses this to search a molecular structure database such as PubChem. Scoring of the predicted query fingerprint and deterministic target fingerprints is carried out assuming independence between the molecular properties constituting the fingerprint. Results: We present a scoring that takes into account dependencies between molecular properties. As before, we predict posterior probabilities of molecular properties using machine learning. Dependencies between molecular properties are modeled as a Bayesian tree network; the tree structure is estimated on the fly from the instance data. For each edge, we also estimate the expected covariance between the two random variables. For fixed marginal probabilities, we then estimate conditional probabilities using the known covariance. Now, the corrected posterior probability of each candidate can be computed, and candidates are ranked by this score. Modeling dependencies improves identification rates of CSI:FingerID by 2.85 percentage points. Availability and implementation: The new scoring Bayesian (fixed tree) is integrated into SIRIUS 4.0 (https://bio.informatik.uni-jena.de/software/sirius/).

Network analysis of transcriptomics expands regulatory landscapes in Synechococcus sp. PCC 7002.

Cyanobacterial regulation of gene expression must contend with a genome organization that lacks apparent functional context, as the majority of cellular processes and metabolic pathways are encoded by genes found at disparate locations across the genome and relatively few transcription factors exist. In this study, global transcript abundance data from the model cyanobacterium Synechococcus sp. PCC 7002 grown under 42 different conditions was analyzed using Context-Likelihood of Relatedness (CLR). The resulting network, organized into 11 modules, provided insight into transcriptional network topology as well as grouping genes by function and linking their response to specific environmental variables. When used in conjunction with genome sequences, the network allowed identification and expansion of novel potential targets of both DNA binding proteins and sRNA regulators. These results offer a new perspective into the multi-level regulation that governs cellular adaptations of the fast-growing physiologically robust cyanobacterium Synechococcus sp. PCC 7002 to changing environmental variables. It also provides a methodological high-throughput approach to studying multi-scale regulatory mechanisms that operate in cyanobacteria. Finally, it provides valuable context for integrating systems-level data to enhance gene grouping based on annotated function, especially in organisms where traditional context analyses cannot be implemented due to lack of operon-based functional organization.

Zn2+-Inducible Expression Platform for Synechococcus sp. Strain PCC 7002 Based on the smtA Promoter/Operator and smtB Repressor.

Synechococcus sp. strain PCC 7002 has been gaining significance as both a model system for photosynthesis research and for industrial applications. Until recently, the genetic toolbox for this model cyanobacterium was rather limited and relied primarily on tools that only allowed constitutive gene expression. This work describes a two-plasmid, Zn2+-inducible expression platform that is coupled with a zurA mutation, providing enhanced Zn2+ uptake. The control elements are based on the metal homeostasis system of a class II metallothionein gene (smtA7942) and its cognate SmtB7942 repressor from Synechococcus elongatus strain PCC 7942. Under optimal induction conditions, yellow fluorescent protein (YFP) levels were about half of those obtained with the strong, constitutive phycocyanin (cpcBA6803) promoter of Synechocystis sp. strain PCC 6803. This metal-inducible expression system in Synechococcus sp. strain PCC 7002 allowed the titratable gene expression of YFP that was up to 19-fold greater than the background level. This system was utilized successfully to control the expression of the Drosophila melanogaster ß-carotene 15,15'-dioxygenase, NinaB, which is toxic when constitutively expressed from a strong promoter in Synechococcus sp. strain PCC 7002. Together, these properties establish this metal-inducible system as an additional useful tool that is capable of controlling gene expression for applications ranging from basic research to synthetic biology in Synechococcus sp. strain PCC 7002. IMPORTANCE: This is the first metal-responsive expression system in cyanobacteria, to our knowledge, that does not exhibit low sensitivity for induction, which is one of the major hurdles for utilizing this class of genetic tools. In addition, high levels of expression can be generated that approximate those of established constitutive systems, with the added advantage of titratable control. Together, these properties establish this Zn2+-inducible system, which is based on the smtA7942 operator/promoter and smtB7942 repressor, as a versatile gene expression platform that expands the genetic toolbox of Synechococcus sp. strain PCC 7002.

ChlR protein of Synechococcus sp. PCC 7002 is a transcription activator that uses an oxygen-sensitive [4Fe-4S] cluster to control genes involved in pigment biosynthesis.

Synechococcus sp. PCC 7002 and many other cyanobacteria have two genes that encode key enzymes involved in chlorophyll a, biliverdin, and heme biosynthesis: acsFI/acsFII, ho1/ho2, and hemF/hemN. Under atmospheric O2 levels, AcsFI synthesizes 3,8-divinyl protochlorophyllide from Mg-protoporphyrin IX monomethyl ester, Ho1 oxidatively cleaves heme to form biliverdin, and HemF oxidizes coproporphyrinogen III to protoporphyrinogen IX. Under microoxic conditions, another set of genes directs the synthesis of alternative enzymes AcsFII, Ho2, and HemN. In Synechococcus sp. PCC 7002, open reading frame SynPCC7002_A1993 encodes a MarR family transcriptional regulator, which is located immediately upstream from the operon comprising acsFII, ho2, hemN, and desF (the latter encodes a putative fatty acid desaturase). Deletion and complementation analyses showed that this gene, denoted chlR, is a transcriptional activator that is essential for transcription of the acsFII-ho2-hemN-desF operon under microoxic conditions. Global transcriptome analyses showed that ChlR controls the expression of only these four genes. Co-expression of chlR with a yfp reporter gene under the control of the acsFII promoter from Synechocystis sp. PCC 6803 in Escherichia coli demonstrated that no other cyanobacterium-specific components are required for proper functioning of this regulatory circuit. A combination of analytical methods and Mössbauer and EPR spectroscopies showed that reconstituted, recombinant ChlR forms homodimers that harbor one oxygen-sensitive [4Fe-4S] cluster. We conclude that ChlR is a transcriptional activator that uses a [4Fe-4S] cluster to sense O2 levels and thereby control the expression of the acsFII-ho2-hemN-desF operon.

Altered carbohydrate metabolism in glycogen synthase mutants of Synechococcus sp. strain PCC 7002: Cell factories for soluble sugars.

Glycogen and compatible solutes are the major polymeric and soluble carbohydrates in cyanobacteria and function as energy reserves and osmoprotectants, respectively. Glycogen synthase null mutants (glgA-I glgA-II) were constructed in the cyanobacterium Synechococcus sp. strain PCC 7002. Under standard conditions the double mutant produced no glycogen and more soluble sugars. When grown under hypersaline conditions, the glgA-I glgA-II mutant accumulated 1.8-fold more soluble sugars (sucrose and glucosylglycer-(ol/ate)) than WT, and these cells spontaneously excreted soluble sugars into the medium at high levels without the need for additional transporters. An average of 27% more soluble sugars was released from the glgA-I glgA-II mutant than WT by hypo-osmotic shock. Extracellular vesicles budding from the outer membrane were observed by transmission electron microscopy in glgA-I glgA-II cells grown under hypersaline conditions. The glgA-I glgA-II mutant serves as a starting point for developing cell factories for photosynthetic production and excretion of sugars.

MAD HATTER Correctly Annotates 98% of Small Molecule Tandem Mass Spectra Searching in PubChem.

Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics usually relies on mass spectrometry, a technology capable of detecting thousands of compounds in a biological sample. Metabolite annotation is executed using tandem mass spectrometry. Spectral library search is far from comprehensive, and numerous compounds remain unannotated. So-called in silico methods allow us to overcome the restrictions of spectral libraries, by searching in much larger molecular structure databases. Yet, after more than a decade of method development, in silico methods still do not reach the correct annotation rates that users would wish for. Here, we present a novel computational method called Mad Hatter for this task. Mad Hatter combines CSI:FingerID results with information from the searched structure database via a metascore. Compound information includes the melting point, and the number of words in the compound description starting with the letter 'u'. We then show that Mad Hatter reaches a stunning 97.6% correct annotations when searching PubChem, one of the largest and most comprehensive molecular structure databases. Unfortunately, Mad Hatter is not a real method. Rather, we developed Mad Hatter solely for the purpose of demonstrating common issues in computational method development and evaluation. We explain what evaluation glitches were necessary for Mad Hatter to reach this annotation level, what is wrong with similar metascores in general, and why metascores may screw up not only method evaluations but also the analysis of biological experiments. This paper may serve as an example of problems in the development and evaluation of machine learning models for metabolite annotation.

High-confidence structural annotation of metabolites absent from spectral libraries.

Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but, typically, only a small fraction of spectra can be matched. Previous in silico methods search in structure databases but cannot distinguish between correct and incorrect annotations. Here we introduce the COSMIC workflow that combines in silico structure database generation and annotation with a confidence score consisting of kernel density P value estimation and a support vector machine with enforced directionality of features. On diverse datasets, COSMIC annotates a substantial number of hits at low false discovery rates and outperforms spectral library search. To demonstrate that COSMIC can annotate structures never reported before, we annotated 12 natural bile acids. The annotation of nine structures was confirmed by manual evaluation and two structures using synthetic standards. In human samples, we annotated and manually validated 315 molecular structures currently absent from the Human Metabolome Database. Application of COSMIC to data from 17,400 metabolomics experiments led to 1,715 high-confidence structural annotations that were absent from spectral libraries.

Differential accumulation of nif structural gene mRNA in Azotobacter vinelandii.

Northern analysis was employed to investigate mRNA produced by mutant strains of Azotobacter vinelandii with defined deletions in the nif structural genes and in the intergenic noncoding regions. The results indicate that intergenic RNA secondary structures effect the differential accumulation of transcripts, supporting the high Fe protein-to-MoFe protein ratio required for optimal diazotrophic growth.

Transcriptional profiling of nitrogen fixation in Azotobacter vinelandii.

Most biological nitrogen (N(2)) fixation results from the activity of a molybdenum-dependent nitrogenase, a complex iron-sulfur enzyme found associated with a diversity of bacteria and some methanogenic archaea. Azotobacter vinelandii, an obligate aerobe, fixes nitrogen via the oxygen-sensitive Mo nitrogenase but is also able to fix nitrogen through the activities of genetically distinct alternative forms of nitrogenase designated the Vnf and Anf systems when Mo is limiting. The Vnf system appears to replace Mo with V, and the Anf system is thought to contain Fe as the only transition metal within the respective active site metallocofactors. Prior genetic analyses suggest that a number of nif-encoded components are involved in the Vnf and Anf systems. Genome-wide transcription profiling of A. vinelandii cultured under nitrogen-fixing conditions under various metal amendments (e.g., Mo or V) revealed the discrete complement of genes associated with each nitrogenase system and the extent of cross talk between the systems. In addition, changes in transcript levels of genes not directly involved in N(2) fixation provided insight into the integration of central metabolic processes and the oxygen-sensitive process of N(2) fixation in this obligate aerobe. The results underscored significant differences between Mo-dependent and Mo-independent diazotrophic growth that highlight the significant advantages of diazotrophic growth in the presence of Mo.

[NiFe] and [FeS] cofactors in the membrane-bound hydrogenase of Ralstonia eutropha investigated by X-ray absorption spectroscopy: insights into O(2)-tolerant H(2) cleavage.

Molecular features that allow certain [NiFe] hydrogenases to catalyze the conversion of molecular hydrogen (H(2)) in the presence of dioxygen (O(2)) were investigated. Using X-ray absorption spectroscopy (XAS), we compared the [NiFe] active site and FeS clusters in the O(2)-tolerant membrane-bound hydrogenase (MBH) of Ralstonia eutropha and the O(2)-sensitive periplasmic hydrogenase (PH) of Desulfovibrio gigas. Fe-XAS indicated an unusual complement of iron-sulfur centers in the MBH, likely based on a specific structure of the FeS cluster proximal to the active site. This cluster is a [4Fe4S] cubane in PH. For MBH, it comprises less than ~2.7 Å Fe-Fe distances and additional longer vectors of ≥3.4 Å, consistent with an Fe trimer with a more isolated Fe ion. Ni-XAS indicated a similar architecture of the [NiFe] site in MBH and PH, featuring Ni coordination by four thiolates of conserved cysteines, i.e., in the fully reduced state (Ni-SR). For oxidized states, short Ni-µO bonds due to Ni-Fe bridging oxygen species were detected in the Ni-B state of the MBH and in the Ni-A state of the PH. Furthermore, a bridging sulfenate (CysSO) is suggested for an inactive state (Ni(ia)-S) of the MBH. We propose that the O(2) tolerance of the MBH is mainly based on a dedicated electron donation from a modified proximal FeS cluster to the active site, which may favor formation of the rapidly reactivated Ni-B state instead of the slowly reactivated Ni-A state. Thereby, the catalytic activity of the MBH is facilitated in the presence of both H(2) and O(2).

Studying Charge Migration Fragmentation of Sodiated Precursor Ions in Collision-Induced Dissociation at the Library Scale.

Interpretation of fragmentation mass spectra depends on our knowledge of collision-induced dissociation mechanisms. Computational methods for the annotation of fragmentation mechanisms operate within the boundaries of recognized fragmentation pathways. The prevalence of charge migration fragmentation (CMF) in sodiated ion fragmentation spectra, which produces nonsodiated fragment ions, is unknown. Here, we investigated the extent of CMF in the fragmentation spectra of sodiated precursors by mining the NIST17 spectral library using a diagnostic mass difference. Our results showed that a substantial amount of fragment ions in sodiated precursor spectra are derived from CMF, indicating that this fragmentation mechanism should be commonly considered by computational methods for compound annotation.

Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra.

Metabolomics using nontargeted tandem mass spectrometry can detect thousands of molecules in a biological sample. However, structural molecule annotation is limited to structures present in libraries or databases, restricting analysis and interpretation of experimental data. Here we describe CANOPUS (class assignment and ontology prediction using mass spectrometry), a computational tool for systematic compound class annotation. CANOPUS uses a deep neural network to predict 2,497 compound classes from fragmentation spectra, including all biologically relevant classes. CANOPUS explicitly targets compounds for which neither spectral nor structural reference data are available and predicts classes lacking tandem mass spectrometry training data. In evaluation using reference data, CANOPUS reached very high prediction performance (average accuracy of 99.7% in cross-validation) and outperformed four baseline methods. We demonstrate the broad utility of CANOPUS by investigating the effect of microbial colonization in the mouse digestive system, through analysis of the chemodiversity of different Euphorbia plants and regarding the discovery of a marine natural product, revealing biological insights at the compound class level.

Functional and structural characterization of the 2/2 hemoglobin from Synechococcus sp. PCC 7002.

Cyanobacterium Synechococcus sp. PCC 7002 contains a single gene (glbN) coding for GlbN, a protein of the 2/2 hemoglobin lineage. The precise function of GlbN is not known, but comparison to similar 2/2 hemoglobins suggests that reversible dioxygen binding is not its main activity. In this report, the results of in vitro and in vivo experiments probing the role of GlbN are presented. Transcription profiling indicated that glbN is not strongly regulated under any of a large number of growth conditions and that the gene is probably constitutively expressed. High levels of nitrate, used as the sole source of nitrogen, and exposure to nitric oxide were tolerated better by the wild-type strain than a glbN null mutant, whereas overproduction of GlbN in the null mutant background restored the wild-type growth. The cellular contents of reactive oxygen/nitrogen species were elevated in the null mutant under all conditions and were highest under NO challenge or in the presence of high nitrate concentrations. GlbN overproduction attenuated these contents significantly under the latter conditions. The analysis of cell extracts revealed that the heme of GlbN was covalently bound to overproduced GlbN apoprotein in cells grown under microoxic conditions. A peroxidase assay showed that purified GlbN does not possess significant hydrogen peroxidase activity. It was concluded that GlbN protects cells from reactive nitrogen species that could be encountered naturally during growth on nitrate or under denitrifying conditions. The solution structure of covalently modified GlbN was determined and used to rationalize some of its chemical properties.

Roles of xanthophyll carotenoids in protection against photoinhibition and oxidative stress in the cyanobacterium Synechococcus sp. strain PCC 7002.

Synechococcus sp. strain PCC 7002 is a robust, genetically tractable cyanobacterium that produces six different xanthophyll carotenoids (zeaxanthin, cryptoxanthin, myxoxanthophyll (myxol-2'-fucoside), echinenone, 3'-hydroxyechinenone, and synechoxanthin) and tolerates many environmental stresses, including high light intensities. Targeted mutations were introduced to block the branches of the carotenoid biosynthetic pathway leading to specific xanthophylls, and a mutant lacking all xanthophylls was constructed. Some of the mutants showed severe growth defects at high light intensities, and multi-locus mutants had somewhat lower chlorophyll contents and lower photosystem I levels. The results suggested that xanthophylls, particularly zeaxanthin and echinenone, might play regulatory roles in thylakoid biogenesis. Measurements of reactive oxygen (ROS) and nitrogen (RNS) species in the mutants showed that all xanthophylls participate in preventing ROS/RNS accumulation and that a mutant lacking all xanthophylls accumulated very high levels of ROS/RNS. Results from transcription profiling showed that mRNA levels for most genes encoding the enzymes of carotenogenesis are significantly more abundant after exposure to high light. These studies indicated that all xanthophylls contribute to protection against photo-oxidative stress.

Impact of amino acid substitutions near the catalytic site on the spectral properties of an O2-tolerant membrane-bound [NiFe] hydrogenase.

[NiFe] hydrogenases are widespread among microorganisms and catalyze the reversible cleavage of molecular hydrogen. However, only a few bacteria, such as Ralstonia eutropha H16 (Re), synthesize [NiFe] hydrogenases that perform H(2) cycling in the presence of O(2). These enzymes are of special interest for biotechnological applications. To gain further insight into the mechanism(s) responsible for the remarkable O(2) tolerance, we employ FTIR and EPR spectroscopy to study mutant variants of the membrane-bound hydrogenase (MBH) of Re-carrying substitutions of a particular cysteine residue in the vicinity of the [NiFe] active site that is characteristic of O(2)-tolerant membrane-bound [NiFe] hydrogenases. We demonstrate that these MBH variants, despite minor changes in the electronic structure and in the interaction behavior with the embedding protein matrix, display all relevant catalytic and noncatalytic states of the wild-type enzyme, as long as they are still located in the cytoplasmic membrane. Notably, in the oxidized Ni(r)-B state and the fully reduced forms, the CO stretching frequency increases with increasing polarity of the respective amino acid residue at the specific position of the cysteine residue. We purified the MBH mutant protein with a cysteine-to-alanine exchange to apparent homogeneity as dimeric enzyme after detergent solubilization from the membrane. This purified version displays increased oxygen sensitivity, which is reflected by detection of the oxygen-inhibited Ni(u)-A state, an irreversible inactive redox state, and the light-induced Ni(a)-L state even at room temperature.

H2 conversion in the presence of O2 as performed by the membrane-bound [NiFe]-hydrogenase of Ralstonia eutropha.

[NiFe]-hydrogenases catalyze the oxidation of H(2) to protons and electrons. This reversible reaction is based on a complex interplay of metal cofactors including the Ni-Fe active site and several [Fe-S] clusters. H(2) catalysis of most [NiFe]-hydrogenases is sensitive to dioxygen. However, some bacteria contain hydrogenases that activate H(2) even in the presence of O(2). There is now compelling evidence that O(2) affects hydrogenase on three levels: 1) H(2) catalysis, 2) hydrogenase maturation, and 3) H(2)-mediated signal transduction. Herein, we summarize the genetic, biochemical, electrochemical, and spectroscopic properties related to the O(2) tolerance of hydrogenases resident in the facultative chemolithoautotroph Ralstonia eutropha H16. A focus is given to the membrane-bound [NiFe]-hydogenase, which currently represents the best-characterized member of O(2)-tolerant hydrogenases.