MS/MS-based networking and peptidogenomics guided genome mining revealed the stenothricin gene cluster in Streptomyces roseosporus

A new strain of Rhodococcus indonesiensis T22.7.1T and its functional potential for deacetylation of chitin and chitooligsaccharides

Introduction

Chitin, abundant in marine environments, presents significant challenges in terms of transformation and utilization. A strain, T22.7.1T, with notable chitin deacetylation capabilities, was isolated from the rhizosphere of Acanthus ebracteatus in the North Sea of China. Comparative 16S rDNA sequence analysis showed that the new isolate had the highest sequence similarity (99.79%) with Rhodococcus indonesiensis CSLK01-03T, followed by R. ruber DSM 43338T, R. electrodiphilus JC435T, and R. aetherivorans 10bc312T (98.97%, 98.81%, and 98.83%, respectively). Subsequent genome sequencing and phylogenetic analysis confirmed that strain T22.7.1T belongs to the R. indonesiensis species. However, additional taxonomic characterization identified strain T22.7.1T as a novel type strain of R. indonesiensis distinct from CSLK01-03T.

Methods

This study refines the taxonomic description of R. indonesiensis and investigates its application in converting chitin into chitosan. The chitin deacetylase (RiCDA) activity of strain T22.7.1T was optimized, and the enzyme was isolated and purified from the fermentation products.

Results

Through optimization, the RiCDA activity of strain T22.7.1T reached 287.02 U/mL, which is 34.88 times greater than the original enzyme's activity (8.0 U/mL). The natural CDA enzyme was purified with a purification factor of 31.83, and the specific activity of the enzyme solution reached 1200.33 U/mg. RiCDA exhibited good pH and temperature adaptability and stability, along with a wide range of substrate adaptabilities, effectively deacetylating chitin, chitooligosaccharides, N-acetylglucosamine, and other substrates.

Discussion

Product analysis revealed that RiCDA treatment increased the deacetylation degree (DD) of natural chitin to 83%, surpassing that of commercial chitosan. Therefore, RiCDA demonstrates significant potential as an efficient deacetylation tool for natural chitin and chitooligosaccharides, highlighting its applicability in the biorefining of natural polysaccharides.

NMR-Metabolomic Profiling and Genome Mining Drive the Discovery of Cyclic Decapeptides from a Marine Streptomyces

The integration of NMR-metabolomic and genomic analyses can provide enhanced identification of structural properties as well as key biosynthetic information, thus achieving the targeted discovery of new natural products. For this purpose, NMR-based metabolomic profiling of the marine-derived Streptomyces sp. S063 (CGMCC 14582) was performed, by which N-methylated peptides possessing unusual negative 1H NMR chemical shift values were tracked. Meanwhile, genome mining of this strain revealed the presence of an unknown NRPS gene cluster (len) with piperazic-acid-encoding genes (lenE and lenF). Under the guidance of the combined information, two cyclic decapeptides, lenziamides D1 (1) and B1 (2), were isolated from Streptomyces sp. S063, which contains piperazic acids with negative 1H NMR values. The structures of 1 and 2 were determined by extensive spectroscopic analysis combined with Marfey's method and ECD calculations. Furthermore, we provided a detailed model of lenziamide (1 and 2) biosynthesis in Streptomyces sp. S063. In the cytotoxicity evaluation, 1 and 2 showed moderate growth inhibition against the human cancer cells HEL, H1975, H1299, and drug-resistant A549-taxol with IC50 values of 8-24 μM.

Potentiality of Actinomycetia Prevalent in Selected Forest Ecosystems in Assam, India to Combat Multi-Drug-Resistant Microbial Pathogens

Actinomycetia are known for their ability to produce a wide range of bioactive secondary metabolites having significant therapeutic importance. This study aimed to explore the potential of actinomycetia as a source of bioactive compounds with antimicrobial properties against multi-drug-resistant (MDR) clinical pathogens. A total of 65 actinomycetia were isolated from two unexplored forest ecosystems, namely the Pobitora Wildlife Sanctuary (PWS) and the Deepor Beel Wildlife Sanctuary (DBWS), located in the Indo-Burma mega-biodiversity hotspots of northeast India, out of which 19 isolates exhibited significant antimicrobial activity. 16S rRNA gene sequencing was used for the identification and phylogenetic analysis of the 19 potent actinomycetia isolates. The results reveal that the most dominant genus among the isolates was Streptomyces (84.21%), followed by rare actinomycetia genera such as Nocardia, Actinomadura, and Nonomuraea. Furthermore, seventeen of the isolates tested positive for at least one antibiotic biosynthetic gene, specifically type II polyketide synthase (PKS-II) and nonribosomal peptide synthetases (NRPSs). These genes are associated with the production of bioactive compounds with antimicrobial properties. Among the isolated strains, three actinomycetia strains, namely Streptomyces sp. PBR1, Streptomyces sp. PBR36, and Streptomyces sp. DBR11, demonstrated the most potent antimicrobial activity against seven test pathogens. This was determined through in vitro antimicrobial bioassays and the minimum inhibitory concentration (MIC) values of ethyl acetate extracts. Gas chromatography-mass spectrometry (GS-MS) and whole-genome sequencing (WGS) of the three strains revealed a diverse group of bioactive compounds and secondary metabolite biosynthetic gene clusters (smBGCs), respectively, indicating their high therapeutic potential. These findings highlight the potential of these microorganisms to serve as a valuable resource for the discovery and development of novel antibiotics and other therapeutics with high therapeutic potential.

CaExTun: Mitigating Cas9-Related Toxicity in Streptomyces through Species-Specific Expression Tuning with Randomized Constitutive Promoters

The CRISPR/Cas9 system provides an efficient tool for engineering genomes. However, its application to Streptomyces genome engineering has been hampered by excessive toxicity associated with overexpression of Cas9 protein. As the level of Cas9 toxicity varies significantly between Streptomyces species, species-specific optimization of Cas9 expression is a strategy to mitigate its toxicity while maintaining sufficient double-strand break (DSB) activity for genome engineering. Using a pool of randomized constitutive promoters and a blue pigment indigoidine biosynthetic gene (IndC) as a reporter, we developed the CaExTun (Cas9 Expression Tuning) platform, which enables rapid screening of a large pool of promoter-Cas9 constructs to quickly recover the one with high DSB activity and no apparent toxicity. We demonstrate the utility of CaExTun using four model Streptomyces species. We also show that CaExTun can be applied to the CRISPRi system by allowing the construction of a library of promoter-dCas9 constructs that confer a wide range of gene repression levels. As demonstrated here, CaExTun is a versatile tool for the rapid optimization of the CRISPR/Cas9 system in a species-specific manner and thus will facilitate CRISPR/Cas9-based genome engineering efforts in Streptomyces.

Lunaemycins, New Cyclic Hexapeptide Antibiotics from the Cave Moonmilk-Dweller Streptomyces lunaelactis MM109T

Streptomyces lunaelactis strains have been isolated from moonmilk deposits, which are calcium carbonate speleothems used for centuries in traditional medicine for their antimicrobial properties. Genome mining revealed that these strains are a remarkable example of a Streptomyces species with huge heterogeneity regarding their content in biosynthetic gene clusters (BGCs) for specialized metabolite production. BGC 28a is one of the cryptic BGCs that is only carried by a subgroup of S. lunaelactis strains for which in silico analysis predicted the production of nonribosomal peptide antibiotics containing the non-proteogenic amino acid piperazic acid (Piz). Comparative metabolomics of culture extracts of S. lunaelactis strains either holding or not holding BGC 28a combined with MS/MS-guided peptidogenomics and ¹H/¹³C NMR allowed us to identify the cyclic hexapeptide with the amino acid sequence (D-Phe)-(L-HO-Ile)-(D-Piz)-(L-Piz)-(D-Piz)-(L-Piz), called lunaemycin A, as the main compound synthesized by BGC 28a. Molecular networking further identified 18 additional lunaemycins, with 14 of them having their structure elucidated by HRMS/MS. Antimicrobial assays demonstrated a significant bactericidal activity of lunaemycins against Gram-positive bacteria, including multi-drug resistant clinical isolates. Our work demonstrates how an accurate in silico analysis of a cryptic BGC can highly facilitate the identification, the structural elucidation, and the bioactivity of its associated specialized metabolites.

Genome mining for drug discovery: progress at the front end

Microbial genome mining for drug discovery and development has been accelerating in recent years, driven by technical advancements in genome sequencing, bioinformatics, metabolomics/metabologenomics, and synthetic biology. Microbial genome mining is a multistep process that starts with the sequencing of microbes that encode multiple secondary metabolites and identifying new and novel secondary metabolite biosynthetic gene clusters (BGCs) to pursue. The initial steps in the process are critical for the overall success, and they encompass the most innovative new technologies to revitalize natural product discovery. As microbial genome mining has matured in recent years, unvalidated conjectures about what microbes to pursue, how to identify legitimate secondary metabolite BGCs, and how to sequence DNA to satisfactory levels of completion have been identified. The solutions to correct the misconceptions around these topics are beginning to be implemented.

In Silico/In Vitro Strategies Leading to the Discovery of New Nonribosomal Peptide and Polyketide Antibiotics Active against Human Pathogens

Antibiotics are majorly important molecules for human health. Following the golden age of antibiotic discovery, a period of decline ensued, characterised by the rediscovery of the same molecules. At the same time, new culture techniques and high-throughput sequencing enabled the discovery of new microorganisms that represent a potential source of interesting new antimicrobial substances to explore. The aim of this review is to present recently discovered nonribosomal peptide (NRP) and polyketide (PK) molecules with antimicrobial activity against human pathogens. We highlight the different in silico/in vitro strategies and approaches that led to their discovery. As a result of technological progress and a better understanding of the NRP and PK synthesis mechanisms, these new antibiotic compounds provide an additional option in human medical treatment and a potential way out of the impasse of antibiotic resistance.

Applications and Restrictions of Integrated Genomic and Metabolomic Screening: An Accelerator for Drug Discovery from Actinomycetes?

Since the golden age of antibiotics in the 1950s and 1960s actinomycetes have been the most prolific source for bioactive natural products. However, the number of discoveries of new bioactive compounds decreases since decades. New procedures (e.g., activating strategies or innovative fermentation techniques) were developed to enhance the productivity of actinomycetes. Nevertheless, compound identification remains challenging among others due to high rediscovery rates. Rapid and cheap genome sequencing as well as the advent of bioinformatical analysis tools for biosynthetic gene cluster identification in combination with mass spectrometry-based molecular networking facilitated the tedious process of dereplication. In recent years several studies have been dedicated to accessing the biosynthetic potential of Actinomyces species, especially streptomycetes, by using integrated genomic and metabolomic screening in order to boost the discovery rate of new antibiotics. This review aims to present the various possible applications of this approach as well as the newly discovered molecules, covering studies between 2014 and 2021. Finally, the effectiveness of this approach with regard to find new bioactive agents from actinomycetes will be evaluated.

Thirtieth Anniversary of the Discovery of Laxaphycins. Intriguing Peptides Keeping a Part of Their Mystery

Lipopeptides are a class of compounds generally produced by microorganisms through hybrid biosynthetic pathways involving non-ribosomal peptide synthase and a polyketyl synthase. Cyanobacterial-produced laxaphycins are examples of this family of compounds that have expanded over the past three decades. These compounds benefit from technological advances helping in their synthesis and characterization, as well as in deciphering their biosynthesis. The present article attempts to summarize most of the articles that have been published on laxaphycins. The current knowledge on the ecological role of these complex sets of compounds will also be examined.

Biosynthetic Potential of Streptomyces Rationalizes Genome-Based Bioprospecting

Streptomyces are the most prolific source of structurally diverse microbial natural products. Advancing genome-based analysis reveals the previously unseen potential of Streptomyces to produce numerous novel secondary metabolites, which allows us to take natural product discovery to the next phase. However, at present there is a huge disproportion between the rate of genome reports and discovery of new compounds. From this perspective of harnessing the enduring importance of Streptomyces, we discuss the recent genome-directed advancements inspired by hidden biosynthetic wealth that provide hope for future antibiotics.

Interpretation of the absorbed constituents and pharmacological effect of Spica Schizonepetae extract on non-small cell lung cancer

As a traditional Chinese medicine (TCM) with a usage history of over 2,000 years in China, Spica Schizonepetae possesses definite clinical activity in the treatment of non-small cell lung cancer (NSCLC). However, its active ingredients and mechanism of action remain unclear at present. The further exploration of its active components and underlying mechanism will provide a basis for the development of candidate anti-tumor drugs. Our previous study explored the chemical constituents of Spica Schizonepetae extract (SSE). On this basis, molecular networking technology was applied in analyzing the QTOF-MS/MS data of rat plasma after intragastric administration of SSE using the GNPS database platform. A total of 26 components were found, including 9 proterotype components and 17 metabolites, which revealed the potential active ingredients of SSE. Later, the Lewis lung cancer mouse model was established, and the inhibition rate and histopathological sections were used as the indicators to investigate the anti-tumor effect of SSE, whereas the body weight, survival rate, thymus index and spleen index served as the indicators to explore the pharmacological effects of SSE on improving mouse immunity. The results showed that SSE had comparable anti-tumor efficacy to cisplatin, which enhanced the immunity, improved the quality of life, and extended the survival time of lung cancer mice. Furthermore, human A549 lung tumor cells were selected to explore the mechanism of SSE in treating NSCLC based on cell metabonomics. After data mining by the MPP software, 23 differential endogenous metabolites were identified between SSE and tumor groups. Moreover, results of pathway enrichment analysis using the MetaboAnalyst 4.0 software indicated that these metabolites were mainly enriched in four metabolic pathways (p < 0.1). By adopting the network pharmacology method, the metabolic pathways discovered by cell metabolomics were verified against the ChEMBL, STITCH, UniProt and TCGA databases, and differences in the underlying mechanism between cells and humans were found. It was proved that SSE affected the metabolism of purine, arachidonic acid and histidine to exert the anti-tumor efficacy. Furthermore, the multi-target, multi-pathway, and immunoenhancement mechanism of SSE in anti-tumor treatment was revealed, which provided a scientific basis for new drug development and the rational application of Spica Schizonepetae in clinic.

Coupling Mass Spectral and Genomic Information to Improve Bacterial Natural Product Discovery Workflows

Bacterial natural products possess potent bioactivities and high structural diversity and are typically encoded in biosynthetic gene clusters. Traditional natural product discovery approaches rely on UV- and bioassay-guided fractionation and are limited in terms of dereplication. Recent advances in mass spectrometry, sequencing and bioinformatics have led to large-scale accumulation of genomic and mass spectral data that is increasingly used for signature-based or correlation-based mass spectrometry genome mining approaches that enable rapid linking of metabolomic and genomic information to accelerate and rationalize natural product discovery. In this mini-review, these approaches are presented, and discovery examples provided. Finally, future opportunities and challenges for paired omics-based natural products discovery workflows are discussed.

Systems and synthetic biology to elucidate secondary metabolite biosynthetic gene clusters encoded in Streptomyces genomes

Covering: 2010 to 2020 Over the last few decades, Streptomyces have been extensively investigated for their ability to produce diverse bioactive secondary metabolites. Recent advances in Streptomyces research have been largely supported by improvements in high-throughput technology 'omics'. From genomics, numerous secondary metabolite biosynthetic gene clusters were predicted, increasing their genomic potential for novel bioactive compound discovery. Additional omics, including transcriptomics, translatomics, interactomics, proteomics and metabolomics, have been applied to obtain a system-level understanding spanning entire bioprocesses of Streptomyces, revealing highly interconnected and multi-layered regulatory networks for secondary metabolism. The comprehensive understanding derived from this systematic information accelerates the rational engineering of Streptomyces to enhance secondary metabolite production, integrated with the exploitation of the highly efficient 'Design-Build-Test-Learn' cycle in synthetic biology. In this review, we describe the current status of omics applications in Streptomyces research to better understand the organism and exploit its genetic potential for higher production of valuable secondary metabolites and novel secondary metabolite discovery.

Elucidating the Diversity and Potential Function of Nonribosomal Peptide and Polyketide Biosynthetic Gene Clusters in the Root Microbiome

Polyketides (PKs) and nonribosomal peptides (NRPs) are two microbial secondary metabolite (SM) families known for their variety of functions, including antimicrobials, siderophores, and others. Despite their involvement in bacterium-bacterium and bacterium-plant interactions, root-associated SMs are largely unexplored due to the limited cultivability of bacteria. Here, we analyzed the diversity and expression of SM-encoding biosynthetic gene clusters (BGCs) in root microbiomes by culture-independent amplicon sequencing, shotgun metagenomics, and metatranscriptomics. Roots (tomato and lettuce) harbored distinct compositions of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) relative to the adjacent bulk soil, and specific BGC markers were both enriched and highly expressed in the root microbiomes. While several of the highly abundant and expressed sequences were remotely associated with known BGCs, the low similarity to characterized genes suggests their potential novelty. Low-similarity genes were screened against a large set of soil-derived cosmid libraries, from which five whole BGCs of unknown function were retrieved. Three clusters were taxonomically affiliated with Actinobacteria, while the remaining were not associated with known bacteria. One Streptomyces-derived BGC was predicted to encode a polyene with potential antifungal activity, while the others were too novel to predict chemical structure. Screening against a suite of metagenomic data sets revealed higher abundances of retrieved clusters in roots and soil samples. In contrast, they were almost completely absent in aquatic and gut environments, supporting the notion that they might play an important role in root ecosystems. Overall, our results indicate that root microbiomes harbor a specific assemblage of undiscovered SMs.IMPORTANCE We identified distinct secondary-metabolite-encoding genes that are enriched (relative to adjacent bulk soil) and expressed in root ecosystems yet almost completely absent in human gut and aquatic environments. Several of the genes were distantly related to genes encoding antimicrobials and siderophores, and their high sequence variability relative to known sequences suggests that they may encode novel metabolites and may have unique ecological functions. This study demonstrates that plant roots harbor a diverse array of unique secondary-metabolite-encoding genes that are highly enriched and expressed in the root ecosystem. The secondary metabolites encoded by these genes might assist the bacteria that produce them in colonization and persistence in the root environment. To explore this hypothesis, future investigations should assess their potential role in interbacterial and bacterium-plant interactions.

Genomic-based classification of Catenulispora pinisilvae sp. nov., novel actinobacteria isolated from a pine forest soil in Poland and emended description of Catenulispora rubra

Two actinobacteria, strains NF3 and NH11^T, isolated from a pine forest soil, near Torun, Poland were examined for diverse chemotaxonomic and morphological properties that placed them in the genus Catenulispora. They produced an extensively branched stable mycelium, contained LL-diaminopimelic acid as the diamino acid of the peptidoglycan, arabinose as the diagnostic whole-organism sugar, tetra-, hexa- and octa-hydrogenated menaquinones with nine isoprenoid units as the predominant isoprenologues, iso-C_16:0 and anteiso-C_17:0 as major fatty acids, and formed a well supported clade within the Catenulispora 16S rRNA gene tree together with Catenulispora acidiphila DSM 44928^T and Catenulispora rubra DSM 44948^T sharing sequence similarities with the latter of 98.8 and 99.0%, respectively. The sizes of whole genome sequences generated for the isolates and the C. rubra strain ranged from 11.20 to 12.80 Mbp with corresponding in silico DNA G+C values of 69.9-70.0%. The isolates and the C. acidiphila and C. rubra strains formed a well supported branch in the actinobacterial phylogenomic tree. Isolates NF3 and NH11^T belong to the same species as they have identical 16S rRNA gene sequences, share many chemotaxonomic, cultural and phenotypic features and show very high average nucleotide identity (ANI) and digital DNA:DNA relatedness (dDDH) similarities. They can be distinguished from their closest phylogenomic neighbours by using a combination of chemotaxonomic and phenotypic properties and by ANI and dDDH values well below the thresholds of these metrics used to assign closely related strains to different species. Consequently, we propose that the isolates be classified as a new Catenulispora species, Catenulispora pinisilvae sp. nov., the type strain is NH11^T (=DSM 111109^T =PCM 3046^T). An emended description is given for C. rubra based on data acquired in the present study. Analyses of the draft genomes of the isolates and the C. acidiphila and C. rubra strains revealed the presence of many biosynthetic gene clusters with the potential to synthesize novel drug-like metabolites. In vitro screens showed that the isolates inhibited the growth of Gram-positive bacteria and wheat pathogens belonging to the genus Fusarium.

Role of symbiosis in the discovery of novel antibiotics

Antibiotic resistance has been an ongoing challenge that has emerged almost immediately after the initial discovery of antibiotics and requires the development of innovative new antibiotics and antibiotic combinations that can effectively mitigate the development of resistance. More than 35,000 people die each year from antibiotic resistant infections in just the United States. This signifies the importance of identifying other alternatives to antibiotics for which resistance has developed. Virtually, all currently used antibiotics can trace their genesis to soil derived bacteria and fungi. The bacteria and fungi involved in symbiosis is an area that still remains widely unexplored for the discovery and development of new antibiotics. This brief review focuses on the challenges and opportunities in the application of symbiotic microbes and also provides an interesting platform that links natural product chemistry with evolutionary biology and ecology.

Genome Mining as New Challenge in Natural Products Discovery

Drug discovery is based on bioactivity screening of natural sources, traditionally represented by bacteria fungi and plants. Bioactive natural products and their secondary metabolites have represented the main source for new therapeutic agents, used as drug leads for new antibiotics and anticancer agents. After the discovery of the first biosynthetic genes in the last decades, the researchers had in their hands the tool to understand the biosynthetic logic and genetic basis leading to the production of these compounds. Furthermore, in the genomic era, in which the number of available genomes is increasing, genome mining joined to synthetic biology are offering a significant help in drug discovery. In the present review we discuss the importance of genome mining and synthetic biology approaches to identify new natural products, also underlining considering the possible advantages and disadvantages of this technique. Moreover, we debate the associated techniques that can be applied following to genome mining for validation of data. Finally, we review on the literature describing all novel natural drugs isolated from bacteria, fungi, and other living organisms, not only from the marine environment, by a genome-mining approach, focusing on the literature available in the last ten years.

Noursamycins, Chlorinated Cyclohexapeptides Identified from Molecular Networking of Streptomyces noursei NTR-SR4

The noursamycins A-F are chlorinated cyclic hexapeptides, which were identified and isolated from the strain Streptomyces noursei NTR-SR4 overexpressing a LuxR-like transcriptional activator. The molecules were structurally characterized by mass spectrometric analyses and 1D and 2D NMR spectroscopic techniques. The enzymatic machinery involved in the biosynthesis of these peptides is represented by a modular nonribosomal peptide synthetase (NRPS), and the corresponding gene cluster was identified in the S. noursei genome. The latter suggested the biosynthetic pathway for the noursamycins. Spectral networking analysis uncovered noursamycin derivatives that were later found to result from a relaxed substrate specificity of the A₃ and A₄ adenylation domains of the NRPS. The stereochemistry of the amino acid constituents of the noursamycins was resolved by chemical derivatization, subsequent enantiomer analytics by GC-EIMS, and in silico data analyses. Noursamycins A and B exhibited antibacterial activity against Gram-positive and Gram-negative bacteria, while no apparent cytotoxicity was observed.

Streptomyces tirandamycinicus sp. nov., a Novel Marine Sponge-Derived Actinobacterium With Antibacterial Potential Against Streptococcus agalactiae

A novel actinobacterium, strain HNM0039T, was isolated from a marine sponge sample collected at the coast of Wenchang, Hainan, China and its polyphasic taxonomy was studied. The isolate had morphological and chemical characteristics consistent with the genus Streptomyces. Based on the 16S rRNA gene sequence analysis, strain HNM0039T was closely related to Streptomyces wuyuanensis CGMCC 4.7042T (99.38%) and Streptomyces spongiicola HNM0071T (99.05%). The organism formed a well-delineated subclade with S. wuyuanensis CGMCC 4.7042T and S. spongiicola HNM0071T in the Streptomyces 16S rRNA gene tree. Multi-locus sequence analysis (MLSA) based on five house-keeping gene alleles (atpD, gyrB, rpoB, recA, trpB) further confirmed their relationship. DNA-DNA relatedness between strain HNM0039T and its closest type strains, namely S. wuyuanensis CGMCC 4.7042T and S. spongiicola HNM0071T, were 46.5 and 45.1%, respectively. The average nucleotide identity (ANI) between strain HNM0039T and its two neighbor strains were 89.65 and 91.44%, respectively. The complete genome size of strain HNM0039T was 7.2 Mbp, comprising 6226 predicted genes with DNA G+C content of 72.46 mol%. Thirty-one putative secondary metabolite biosynthetic gene clusters were also predicted in the genome of strain HNM0039T. Among them, the tirandamycin biosynthetic gene cluster has been characterized completely. The crude extract of strain HNM0039T exhibited potent antibacterial activity against Streptococcus agalactiae in Nile tilapia. And tirandamycins A and B were further identified as the active components with MIC values of 2.52 and 2.55 μg/ml, respectively. Based on genotypic and phenotypic characteristics, it is concluded that strain HNM0039T represents a novel species of the genus Streptomyces whose name was proposed as Streptomyces tirandamycinicus sp. nov. The type strain is HNM0039T (= CCTCC AA 2018045T = KCTC 49236T).

Computational identification of co-evolving multi-gene modules in microbial biosynthetic gene clusters

The biosynthetic machinery responsible for the production of bacterial specialised metabolites is encoded by physically clustered group of genes called biosynthetic gene clusters (BGCs). The experimental characterisation of numerous BGCs has led to the elucidation of subclusters of genes within BGCs, jointly responsible for the same biosynthetic function in different genetic contexts. We developed an unsupervised statistical method able to successfully detect a large number of modules (putative functional subclusters) within an extensive set of predicted BGCs in a systematic and automated manner. Multiple already known subclusters were confirmed by our method, proving its efficiency and sensitivity. In addition, the resulting large collection of newly defined modules provides new insights into the prevalence and putative biosynthetic role of these modular genetic entities. The automated and unbiased identification of hundreds of co-evolving group of genes is an essential breakthrough for the discovery and biosynthetic engineering of high-value compounds.

Analysis of the complete genome sequence of a marine-derived strain Streptomyces sp. S063 CGMCC 14582 reveals its biosynthetic potential to produce novel anti-complement agents and peptides

Genome sequences of marine streptomycetes are valuable for the discovery of useful enzymes and bioactive compounds by genome mining. However, publicly available complete genome sequences of marine streptomycetes are still limited. Here, we present the complete genome sequence of a marine streptomycete Streptomyces sp. S063 CGMCC 14582. Species delineation based on the pairwise digital DNA-DNA hybridization and genome comparison ANI (average nucleotide identity) value showed that Streptomyces sp. S063 CGMCC 14582 possesses a unique genome that is clearly different from all of the other available genomes. Bioactivity tests showed that Streptomyces sp. S063 CGMCC 14582 produces metabolites with anti-complement activities, which are useful for treatment of numerous diseases that arise from inappropriate activation of the human complement system. Analysis of the genome reveals no biosynthetic gene cluster (BGC) which shows even low similarity to that of the known anti-complement agents was detected in the genome, indicating that Streptomyces sp. S063 CGMCC 14582 may produce novel anti-complement agents of microbial origin. Four BGCs which are potentially involved in biosynthesis of non-ribosomal peptides were disrupted, but no decrease of anti-complement activities was observed, suggesting that these four BGCs are not involved in biosynthesis of the anti-complement agents. In addition, LC-MS/MS analysis and subsequent alignment through the Global Natural Products Social Molecular Networking (GNPS) platform led to the detection of novel peptides produced by the strain. Streptomyces sp. S063 CGMCC 14582 grows rapidly and is salt tolerant, which benefits efficient secondary metabolite production via seawater-based fermentation. Our results indicate that Streptomyces sp. S063 has great potential to produce novel bioactive compounds, and also is a good host for heterologous production of useful secondary metabolites for drug discovery.

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.

Inter-Kingdom beach warfare: Microbial chemical communication activates natural chemical defences

An inter-kingdom beach warfare between a Streptomyces sp. and Aspergillus sp. co-isolated from shallow water beach sand, collected off Heron Island, Queensland, Australia, saw the bacteriostatic Aspergillus metabolite cyclo-(L-Phe-trans-4-hydroxy-L-Pro) (3) stimulate the Streptomyces to produce nitric oxide (NO), which in turn mediated transcriptional activation of a silent biosynthetic gene cluster (BGC) for fungistatic heronapyrrole B (1). Structure activity relationship studies, coupled with the use of NO synthase inhibitors, donors and scavangers, and both genomic and transcriptomic analyses, confirmed the extraordinary chemical cue specificity of 3, and its NO-mediated mechanism of transcriptional action. Our findings reveal the importance of inter-kingdom (fungal-bacterial) chemical communication in the regulation of silent BGCs coding for chemical defenses. We propose that the detection and characterisation of NO mediated transcriptional activation (NOMETA) of silent chemical defences in the environment, may inspire broader application in the field of microbial biodiscovery.

Auroramycin: A Potent Antibiotic from Streptomyces roseosporus by CRISPR-Cas9 Activation

Silent biosynthetic gene clusters represent a potentially rich source of new bioactive compounds. We report the discovery, characterization, and biosynthesis of a novel doubly glycosylated 24-membered polyene macrolactam from a silent biosynthetic gene cluster in Streptomyces roseosporus by using the CRISPR-Cas9 gene cluster activation strategy. Structural characterization of this polyketide, named auroramycin, revealed a rare isobutyrylmalonyl extender unit and a unique pair of amino sugars. Relative and absolute stereochemistry were determined by using a combination of spectroscopic analyses, chemical derivatization, and computational analysis. The activated gene cluster for auroramycin production was also verified by transcriptional analyses and gene deletions. Finally, auroramycin exhibited potent anti-methicillin-resistant Staphylococcus aureus (anti-MRSA) activity towards clinical drug-resistant isolates.

Concepts and Methods to Access Novel Antibiotics from Actinomycetes

Actinomycetes have been proven to be an excellent source of secondary metabolites for more than half a century. Exhibiting various bioactivities, they provide valuable approved drugs in clinical use. Most microorganisms are still untapped in terms of their capacity to produce secondary metabolites, since only a small fraction can be cultured in the laboratory. Thus, improving cultivation techniques to extend the range of secondary metabolite producers accessible under laboratory conditions is an important first step in prospecting underexplored sources for the isolation of novel antibiotics. Currently uncultured actinobacteria can be made available by bioprospecting extreme or simply habitats other than soil. Furthermore, bioinformatic analysis of genomes reveals most producers to harbour many more biosynthetic gene clusters than compounds identified from any single strain, which translates into a silent biosynthetic potential of the microbial world for the production of yet unknown natural products. This review covers discovery strategies and innovative methods recently employed to access the untapped reservoir of natural products. The focus is the order of actinomycetes although most approaches are similarly applicable to other microbes. Advanced cultivation methods, genomics- and metagenomics-based approaches, as well as modern metabolomics-inspired methods are highlighted to emphasise the interplay of different disciplines to improve access to novel natural products.

Correlating chemical diversity with taxonomic distance for discovery of natural products in myxobacteria

Some bacterial clades are important sources of novel bioactive natural products. Estimating the magnitude of chemical diversity available from such a resource is complicated by issues including cultivability, isolation bias and limited analytical data sets. Here we perform a systematic metabolite survey of ~2300 bacterial strains of the order Myxococcales, a well-established source of natural products, using mass spectrometry. Our analysis encompasses both known and previously unidentified metabolites detected under laboratory cultivation conditions, thereby enabling large-scale comparison of production profiles in relation to myxobacterial taxonomy. We find a correlation between taxonomic distance and the production of distinct secondary metabolite families, further supporting the idea that the chances of discovering novel metabolites are greater by examining strains from new genera rather than additional representatives within the same genus. In addition, we report the discovery and structure elucidation of rowithocin, a myxobacterial secondary metabolite featuring an uncommon phosphorylated polyketide scaffold.

It is thought that the chances for discovery of novel natural products increase by screening rare organisms. Here the authors analyse metabolites produced by over 2300 myxobacterial strains and, indeed, find a correlation between taxonomic distance and production of distinct secondary metabolite families.

Environmentally Friendly Procedure Based on Supercritical Fluid Chromatography and Tandem Mass Spectrometry Molecular Networking for the Discovery of Potent Antiviral Compounds from Euphorbia semiperfoliata

A supercritical fluid chromatography-based targeted purification procedure using tandem mass spectrometry and molecular networking was developed to analyze, annotate, and isolate secondary metabolites from complex plant extract mixture. This approach was applied for the targeted isolation of new antiviral diterpene esters from Euphorbia semiperfoliata whole plant extract. The analysis of bioactive fractions revealed that unknown diterpene esters, including jatrophane esters and phorbol esters, were present in the samples. The purification procedure using semipreparative supercritical fluid chromatography led to the isolation and identification of two new jatrophane esters (13 and 14) and one known (15) and three new 4-deoxyphorbol esters (16-18). The structure and absolute configuration of compound 16 were confirmed by X-ray crystallography. This compound was found to display antiviral activity against Chikungunya virus (EC₅₀ = 0.45 μM), while compound 15 proved to be a potent and selective inhibitor of HIV-1 replication in a recombinant virus assay (EC₅₀ = 13 nM). This study showed that a supercritical fluid chromatography-based protocol and molecular networking can facilitate and accelerate the discovery of bioactive small molecules by targeting molecules of interest, while minimizing the use of toxic solvents.

Small Molecule Accurate Recognition Technology (SMART) to Enhance Natural Products Research

Various algorithms comparing 2D NMR spectra have been explored for their ability to dereplicate natural products as well as determine molecular structures. However, spectroscopic artefacts, solvent effects, and the interactive effect of functional group(s) on chemical shifts combine to hinder their effectiveness. Here, we leveraged Non-Uniform Sampling (NUS) 2D NMR techniques and deep Convolutional Neural Networks (CNNs) to create a tool, SMART, that can assist in natural products discovery efforts. First, an NUS heteronuclear single quantum coherence (HSQC) NMR pulse sequence was adapted to a state-of-the-art nuclear magnetic resonance (NMR) instrument, and data reconstruction methods were optimized, and second, a deep CNN with contrastive loss was trained on a database containing over 2,054 HSQC spectra as the training set. To demonstrate the utility of SMART, several newly isolated compounds were automatically located with their known analogues in the embedded clustering space, thereby streamlining the discovery pipeline for new natural products.

Symbiosis-inspired approaches to antibiotic discovery

Covering: 2010 up to 2017Life on Earth is characterized by a remarkable abundance of symbiotic and highly refined relationships among life forms. Defined as any kind of close, long-term association between two organisms, symbioses can be mutualistic, commensalistic or parasitic. Historically speaking, selective pressures have shaped symbioses in which one organism (typically a bacterium or fungus) generates bioactive small molecules that impact the host (and possibly other symbionts); the symbiosis is driven fundamentally by the genetic machineries available to the small molecule producer. The human microbiome is now integral to the most recent chapter in animal-microbe symbiosis studies and plant-microbe symbioses have significantly advanced our understanding of natural products biosynthesis; this also is the case for studies of fungal-microbe symbioses. However, much less is known about microbe-microbe systems involving interspecies interactions. Microbe-derived small molecules (i.e. antibiotics and quorum sensing molecules, etc.) have been shown to regulate transcription in microbes within the same environmental niche, suggesting interspecies interactions whereas, intraspecies interactions, such as those that exploit autoinducing small molecules, also modulate gene expression based on environmental cues. We, and others, contend that symbioses provide almost unlimited opportunities for the discovery of new bioactive compounds whose activities and applications have been evolutionarily optimized. Particularly intriguing is the possibility that environmental effectors can guide laboratory expression of secondary metabolites from "orphan", or silent, biosynthetic gene clusters (BGCs). Notably, many of the studies summarized here result from advances in "omics" technologies and highlight how symbioses have given rise to new anti-bacterial and antifungal natural products now being discovered.

CRISPR-Cas9 strategy for activation of silent Streptomyces biosynthetic gene clusters

Here we report an efficient CRISPR-Cas9 knock-in strategy to activate silent biosynthetic gene clusters (BGCs) in streptomycetes. We applied this one-step strategy to activate multiple BGCs of different classes in five Streptomyces species and triggered the production of unique metabolites, including a novel pentangular type II polyketide in Streptomyces viridochromogenes. This potentially scalable strategy complements existing activation approaches and facilitates discovery efforts to uncover new compounds with interesting bioactivities.

Dereplication of peptidic natural products through database search of mass spectra

Peptidic Natural Products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. While recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers utilize dereplication strategies that identify known PNPs and lead to the discovery of new ones even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enabled high-throughput PNP identification and that is compatible with large-scale mass spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts.

Rapid Inhibition Profiling in Bacillus subtilis to Identify the Mechanism of Action of New Antimicrobials

Increasing antimicrobial resistance has become a major public health crisis. New antimicrobials with novel mechanisms of action (MOA) are desperately needed. We previously developed a method, bacterial cytological profiling (BCP), which utilizes fluorescence microscopy to rapidly identify the MOA of antimicrobial compounds. BCP is based upon our discovery that cells treated with antibiotics affecting different metabolic pathways generate different cytological signatures, providing quantitative information that can be used to determine a compound's MOA. Here, we describe a system, rapid inhibition profiling (RIP), for creating cytological profiles of new antibiotic targets for which there are currently no chemical inhibitors. RIP consists of the fast, inducible degradation of a target protein followed by BCP. We demonstrate that degrading essential proteins in the major metabolic pathways for DNA replication, transcription, fatty acid biosynthesis, and peptidoglycan biogenesis in Bacillus subtilis rapidly produces cytological profiles closely matching that of antimicrobials targeting the same pathways. Additionally, RIP and antibiotics targeting different steps in fatty acid biosynthesis can be differentiated from each other. We utilize RIP and BCP to show that the antibacterial MOA of four nonsteroidal anti-inflammatory antibiotics differs from that proposed based on in vitro data. RIP is a versatile method that will extend our knowledge of phenotypes associated with inactivating essential bacterial enzymes and thereby allow for screening for molecules that inhibit novel essential targets.

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

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

CAB, Torres-Mendoza D, Gonzalez DJ, Silva DB, Marques LM, Demarque DP, Pociute E, O'Neill EC, Briand E, Helfrich EJN, Granatosky EA, Glukhov E, Ryffel F, Houson H, Mohimani H, Kharbush JJ, Zeng Y, Vorholt JA, Kurita KL, Charusanti P, McPhail KL, Nielsen KF, Vuong L, Elfeki M, Traxler MF, Engene N, Koyama N, Vining OB, Baric R, Silva RR, Mascuch SJ, Tomasi S, Jenkins S, Macherla V, Hoffman T, Agarwal V, Williams PG, Dai J, Neupane R, Gurr J, Rodríguez AMC, Lamsa A, Zhang C, Dorrestein K, Duggan BM, Almaliti J, Allard PM, Phapale P, Nothias LF, Alexandrov T, Litaudon M, Wolfender JL, Kyle JE, Metz TO, Peryea T, Nguyen DT, VanLeer D, Shinn P, Jadhav A, Müller R, Waters KM, Shi W, Liu X, Zhang L, Knight R, Jensen PR, Palsson BO, Pogliano K, Linington RG, Gutiérrez M, Lopes NP, Gerwick WH, Moore BS, Dorrestein PC, Bandeira N. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Antibiotic drug discovery

Due to the threat posed by the increase of highly resistant pathogenic bacteria, there is an urgent need for new antibiotics; all the more so since in the last 20 years, the approval for new antibacterial agents had decreased. The field of natural product discovery has undergone a tremendous development over the past few years. This has been the consequence of several new and revolutionizing drug discovery and development techniques, which is initiating a ‘New Age of Antibiotic Discovery’. In this review, we concentrate on the most significant discovery approaches during the last and present years and comment on the challenges facing the community in the coming years.

Dissecting Bottromycin Biosynthesis Using Comparative Untargeted Metabolomics

Bottromycin A2 is a structurally unique ribosomally synthesized and post-translationally modified peptide (RiPP) that possesses potent antibacterial activity towards multidrug-resistant bacteria. The structural novelty of bottromycin stems from its unprecedented macrocyclic amidine and rare β-methylated amino acid residues. The N-terminus of a precursor peptide (BtmD) is converted into bottromycin A2 by tailoring enzymes encoded in the btm gene cluster. However, little was known about key transformations in this pathway, including the unprecedented macrocyclization. To understand the pathway in detail, an untargeted metabolomic approach that harnesses mass spectral networking was used to assess the metabolomes of a series of pathway mutants. This analysis has yielded key information on the function of a variety of previously uncharacterized biosynthetic enzymes, including a YcaO domain protein and a partner protein that together catalyze the macrocyclization.

Dung-inhabiting fungi: a potential reservoir of novel secondary metabolites for the control of plant pathogens

Coprophilous fungi are a large group of saprotrophic fungi mostly found in herbivore dung. The number of these fungi undergoing investigation is continually increasing, and new species and genera continue to be described. Dung-inhabiting fungi play an important ecological role in decomposing and recycling nutrients from animal dung. They produce a large array of bioactive secondary metabolites and have a potent enzymatic arsenal able to utilise even complex molecules. Bioactive secondary metabolites are actively involved in interaction with and defence against other organisms whose growth can be inhibited, resulting in an enhanced ecological fitness of producer strains. Currently, these antibiotics and bioactive secondary metabolites are of interest in medicine in particular, while very little information is available concerning their potential use in agriculture. This review introduces the ecology of dung-inhabiting fungi, with particular emphasis on the production of antibiotic compounds as a means to compete with other microorganisms. Owing to the fast pace of technological progress, new approaches to predicting the biosynthesis of bioactive metabolites are proposed. Coprophilous fungi should be considered as elite candidate organisms for the discovery of novel antifungal compounds, above all in view of their exploitation for crop protection.

Leucanicidin and Endophenasides Result from Methyl-Rhamnosylation by the Same Tailoring Enzymes in Kitasatospora sp. MBT66

The increasing bacterial multidrug resistance necessitates novel drug-discovery efforts. One way to obtain novel chemistry is glycosylation, which is prevalent in nature, with high diversity in both the sugar moieties and the targeted aglycones. Kitasatospora sp. MBT66 produces endophenaside antibiotics, which is a family of (methyl-)rhamnosylated phenazines. Here we show that this strain also produces the plecomacrolide leucanicidin (1), which is derived from bafilomycin A1 by glycosylation with the same methyl-rhamnosyl moiety as present in the endophenasides. Immediately adjacent to the baf genes for bafilomycin biosynthesis lie leuA and leuB, which encode a sugar-O-methyltransferase and a glycosyltransferase, respectively. LeuA and LeuB are the only enzymes encoded by the genome of Kitasatospora sp. MBT66 that are candidates for the methyl-rhamnosylation of natural products, and mutation of leuB abolished glycosylation of both families of natural products. Thus, LeuA and -B mediate the post-PKS methyl-rhamnosylation of bafilomycin A1 to leucanicidin and of phenazines to endophenasides, showing surprising promiscuity by tolerating both macrolide and phenazine skeletons as the substrates. Detailed metabolic analysis by MS/MS based molecular networking facilitated the characterization of nine novel phenazine glycosides 6-8, 16, and 22-26, whereby compounds 23 and 24 represent an unprecedented tautomeric glyceride phenazine, further enriching the structural diversity of endophenasides.

Dereplication, sequencing and identification of peptidic natural products: from genome mining to peptidogenomics to spectral networks

Covering: 2000 to 2015. While recent breakthroughs in the discovery of peptide antibiotics and other Peptidic Natural Products (PNPs) raise a challenge for developing new algorithms for their analyses, the computational technologies for high-throughput PNP discovery are still lacking. We discuss the computational bottlenecks in analyzing PNPs and review recent advances in genome mining, peptidogenomics, and spectral networks that are now enabling the discovery of new PNPs via mass spectrometry. We further describe the connections between these advances and the new generation of software tools for PNP dereplication, de novo sequencing, and identification.

Metabolomics in chemical ecology

Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

Mapping Microbial Response Metabolomes for Induced Natural Product Discovery

Intergeneric microbial interactions may originate a significant fraction of secondary metabolic gene regulation in nature. Herein, we expose a genomically characterized Nocardiopsis strain, with untapped polyketide biosynthetic potential, to intergeneric interactions via coculture with low inoculum exposure to Escherichia, Bacillus, Tsukamurella, and Rhodococcus. The challenge-induced responses of extracted metabolites were characterized via multivariate statistical and self-organizing map (SOM) analyses, revealing the magnitude and selectivity engendered by the limiting case of low inoculum exposure. The collected inventory of cocultures revealed substantial metabolomic expansion in comparison to monocultures with nearly 14% of metabolomic features in cocultures undetectable in monoculture conditions and many features unique to coculture genera. One set of SOM-identified responding features was isolated, structurally characterized by multidimensional NMR, and revealed to comprise previously unreported polyketides containing an unusual pyrrolidinol substructure and moderate and selective cytotoxicity. Designated ciromicin A and B, they are detected across mixed cultures with intergeneric preferences under coculture conditions. The structural novelty of ciromicin A is highlighted by its ability to undergo a diastereoselective photochemical 12-π electron rearrangement to ciromicin B at visible wavelengths. This study shows how organizing trends in metabolomic responses under coculture conditions can be harnessed to characterize multipartite cultures and identify previously silent secondary metabolism.

Mass spectrometry tools and workflows for revealing microbial chemistry

Since the time Van Leeuwenhoek was able to observe microbes through a microscope, an innovation that led to the birth of the field of microbiology, we have aimed to understand how microorganisms function, interact and communicate. The exciting progress in the development of analytical technologies and workflows has demonstrated that mass spectrometry is a very powerful technique for the interrogation of microbiology at the molecular level. In this review, we aim to highlight the available and emerging tools in mass spectrometry for microbial analysis by overviewing the methods and workflow advances for taxonomic identification, microbial interaction, dereplication and drug discovery. We emphasize their potential for future development and point out unsolved problems and future directions that would aid in the analysis of the chemistry produced by microbes.