Phylogenetic classification of natural product biosynthetic gene clusters based on regulatory mechanisms.

The natural products (NPs) biosynthetic gene clusters (BGCs) represent the adapting biochemical toolkit for microorganisms to thrive different microenvironments. Despite their high diversity, particularly at the genomic level, detecting them in a shake-flask is challenging and remains the primary obstacle limiting our access to valuable chemicals. Studying the molecular mechanisms that regulate BGC expression is crucial to design of artificial conditions that derive on their expression. Here, we propose a phylogenetic analysis of regulatory elements linked to biosynthesis gene clusters, to classify BGCs to regulatory mechanisms based on protein domain information. We utilized Hidden Markov Models from the Pfam database to retrieve regulatory elements, such as histidine kinases and transcription factors, from BGCs in the MIBiG database, focusing on actinobacterial strains from three distinct environments: oligotrophic basins, rainforests, and marine environments. Despite the environmental variations, our isolated microorganisms share similar regulatory mechanisms, suggesting the potential to activate new BGCs using activators known to affect previously characterized BGCs.

Biosynthetic gene profiling and genomic potential of the novel photosynthetic marine bacterium Roseibaca domitiana.

Shifting the bioprospecting targets toward underexplored bacterial groups combined with genome mining studies contributes to avoiding the rediscovery of known compounds by revealing novel, promising biosynthetic gene clusters (BGCs). With the aim of determining the biosynthetic potential of a novel marine bacterium, strain V10T, isolated from the Domitian littoral in Italy, a comparative phylogenomic mining study was performed across related photosynthetic bacterial groups from an evolutionary perspective. Studies on polyphasic and taxogenomics showed that this bacterium constitutes a new species, designated Roseibaca domitiana sp. nov. To date, this genus has only one other validly described species, which was isolated from a hypersaline Antarctic lake. The genomic evolutionary study linked to BGC diversity revealed that there is a close relationship between the phylogenetic distance of the members of the photosynthetic genera Roseibaca, Roseinatronobacter, and Rhodobaca and their BGC profiles, whose conservation pattern allows discriminating between these genera. On the contrary, the rest of the species related to Roseibaca domitiana exhibited an individual species pattern unrelated to genome size or source of isolation. This study showed that photosynthetic strains possess a streamlined content of BGCs, of which 94.34% of the clusters with biotechnological interest (NRPS, PKS, RRE, and RiPP) are completely new. Among these stand out T1PKS, exclusive of R. domitiana V10T, and RRE, highly conserved only in R. domitiana V10T and R. ekhonensis, both categories of BGCs involved in the synthesis of plant growth-promoting compounds and antitumoral compounds, respectively. In all cases, with very low homology with already patented molecules. Our findings reveal the high biosynthetic potential of infrequently cultured bacterial groups, suggesting the need to redirect attention to microbial minorities as a novel and vast source of bioactive compounds still to be exploited.

Omicron-BA.1 Dispersion Rates in Mexico Varied According to the Regional Epidemic Patterns and the Diversity of Local Delta Subvariants.

PURPOSE: The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In this work, a characterization of the spread of this variant in Mexico is presented. METHODS: The time to fixation of BA.1, the diversity of Delta sublineages, the population density, and the level of virus circulation during the inter-wave interval were determined to analyze differences in BA.1 spread. RESULTS: BA.1 began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in Mexico. Unlike previous variants, BA.1 did not exhibit a geographically distinct circulation pattern. However, a regional difference in the speed of the replacement of the Delta variant was observed. CONCLUSIONS: Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics, in addition to population density. Nonetheless, if there is a significant difference in the fitness of the variants, or if the time allowed for the competition is sufficiently long, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico.

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters.

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

Metagenomics Bioinformatic Pipeline.

Microbial communities' taxonomic and functional diversity has been broadly studied since sequencing technologies enabled faster and cheaper data obtainment. Nevertheless, the programming skills needed and the amount of software available may be overwhelming to someone trying to analyze these data. Here, we present a comprehensive and straightforward pipeline that takes shotgun metagenomics data through the needed steps to obtain valuable results. The raw data goes through a quality control process, metagenomic assembly, binning (the obtention of single genomes from a metagenome), taxonomic assignment, and taxonomic diversity analysis and visualization.

ActinoBase: tools and protocols for researchers working on Streptomyces and other filamentous actinobacteria.

Actinobacteria is an ancient phylum of Gram-positive bacteria with a characteristic high GC content to their DNA. The ActinoBase Wiki is focused on the filamentous actinobacteria, such as Streptomyces species, and the techniques and growth conditions used to study them. These organisms are studied because of their complex developmental life cycles and diverse specialised metabolism which produces many of the antibiotics currently used in the clinic. ActinoBase is a community effort that provides valuable and freely accessible resources, including protocols and practical information about filamentous actinobacteria. It is aimed at enabling knowledge exchange between members of the international research community working with these fascinating bacteria. ActinoBase is an anchor platform that underpins worldwide efforts to understand the ecology, biology and metabolic potential of these organisms. There are two key differences that set ActinoBase apart from other Wiki-based platforms: [1] ActinoBase is specifically aimed at researchers working on filamentous actinobacteria and is tailored to help users overcome challenges working with these bacteria and [2] it provides a freely accessible resource with global networking opportunities for researchers with a broad range of experience in this field.

Dominance of Three Sublineages of the SARS-CoV-2 Delta Variant in Mexico.

In this study, we analyzed the sequences of SARS-CoV-2 isolates of the Delta variant in Mexico, which has completely replaced other previously circulating variants in the country due to its transmission advantage. Among all the Delta sublineages that were detected, 81.5 % were classified as AY.20, AY.26, and AY.100. According to publicly available data, these only reached a world prevalence of less than 1%, suggesting a possible Mexican origin. The signature mutations of these sublineages are described herein, and phylogenetic analyses and haplotype networks are used to track their spread across the country. Other frequently detected sublineages include AY.3, AY.62, AY.103, and AY.113. Over time, the main sublineages showed different geographical distributions, with AY.20 predominant in Central Mexico, AY.26 in the North, and AY.100 in the Northwest and South/Southeast. This work describes the circulation, from May to November 2021, of the primary sublineages of the Delta variant associated with the third wave of the COVID-19 pandemic in Mexico and highlights the importance of SARS-CoV-2 genomic surveillance for the timely identification of emerging variants that may impact public health.

Evolutionary Genome Mining for the Discovery and Engineering of Natural Product Biosynthesis.

Genome mining has become an invaluable tool in natural products research to quickly identify and characterize the biosynthetic pathways that assemble secondary or specialized metabolites. Recently, evolutionary principles have been incorporated into genome mining strategies in an effort to better assess and prioritize novelty and understand their chemical diversification for engineering purposes. Here, we provide an introduction to the principles underlying evolutionary genome mining, including bioinformatic strategies and natural product biosynthetic databases. We introduce workflows for traditional genome mining, focusing on the popular pipeline antiSMASH, and methods to predict enzyme substrate specificity from genomic information. We then provide an in-depth discussion of evolutionary genome mining workflows, including EvoMining, CORASON, ARTS, and others, as adopted by our group for the discovery and prioritization of natural products biosynthetic gene clusters and their products.

The Alpha Variant (B.1.1.7) of SARS-CoV-2 Failed to Become Dominant in Mexico.

During the coronavirus disease 2019 (COVID-19) pandemic, the emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in the United Kingdom in September 2020, was well documented in different areas of the world and became a global public health concern because of its increased transmissibility. The B.1.1.7 lineage was first detected in Mexico during December 2020, showing a slow progressive increase in its circulation frequency, which reached its maximum in May 2021 but never became predominant. In this work, we analyzed the patterns of diversity and distribution of this lineage in Mexico using phylogenetic and haplotype network analyses. Despite the reported increase in transmissibility of the B.1.1.7 lineage, in most Mexican states, it did not displace cocirculating lineages, such as B.1.1.519, which dominated the country from February to May 2021. Our results show that the states with the highest prevalence of B.1.1.7 were those at the Mexico-U.S. border. An apparent pattern of dispersion of this lineage from the northern states of Mexico toward the center or the southeast was observed in the largest transmission chains, indicating possible independent introduction events from the United States. However, other entry points cannot be excluded, as shown by multiple introduction events. Local transmission led to a few successful haplotypes with a localized distribution and specific mutations indicating sustained community transmission. IMPORTANCE The emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world were due to its increased transmissibility. However, it did not displace cocirculating lineages in most of Mexico, particularly B.1.1.519, which dominated the country from February to May 2021. In this work, we analyzed the distribution of B.1.1.7 in Mexico using phylogenetic and haplotype network analyses. Our results show that the states with the highest prevalence of B.1.1.7 (around 30%) were those at the Mexico-U.S. border, which also exhibited the highest lineage diversity, indicating possible introduction events from the United States. Also, several haplotypes were identified with a localized distribution and specific mutations, indicating that sustained community transmission occurred in the country.

Unveiling the genomic potential of Pseudomonas type strains for discovering new natural products.

Microbes host a huge variety of biosynthetic gene clusters that produce an immeasurable array of secondary metabolites with many different biological activities such as antimicrobial, anticarcinogenic and antiviral. Despite the complex task of isolating and characterizing novel natural products, microbial genomic strategies can be useful for carrying out these types of studies. However, although genomic-based research on secondary metabolism is on the increase, there is still a lack of reports focusing specifically on the genus Pseudomonas. In this work, we aimed (i) to unveil the main biosynthetic systems related to secondary metabolism in Pseudomonas type strains, (ii) to study the evolutionary processes that drive the diversification of their coding regions and (iii) to select Pseudomonas strains showing promising results in the search for useful natural products. We performed a comparative genomic study on 194 Pseudomonas species, paying special attention to the evolution and distribution of different classes of biosynthetic gene clusters and the coding features of antimicrobial peptides. Using EvoMining, a bioinformatic approach for studying evolutionary processes related to secondary metabolism, we sought to decipher the protein expansion of enzymes related to the lipid metabolism, which may have evolved toward the biosynthesis of novel secondary metabolites in Pseudomonas. The types of metabolites encoded in Pseudomonas type strains were predominantly non-ribosomal peptide synthetases, bacteriocins, N-acetylglutaminylglutamine amides and ß-lactones. Also, the evolution of genes related to secondary metabolites was found to coincide with Pseudomonas species diversification. Interestingly, only a few Pseudomonas species encode polyketide synthases, which are related to the lipid metabolism broadly distributed among bacteria. Thus, our EvoMining-based search may help to discover new types of secondary metabolite gene clusters in which lipid-related enzymes are involved. This work provides information about uncharacterized metabolites produced by Pseudomonas type strains, whose gene clusters have evolved in a species-specific way. Our results provide novel insight into the secondary metabolism of Pseudomonas and will serve as a basis for the prioritization of the isolated strains. This article contains data hosted by Microreact.

Genomic study and lipidomic bioassay of Leeuwenhoekiella parthenopeia: A novel rare biosphere marine bacterium that inhibits tumor cell viability.

The fraction of low-abundance microbiota in the marine environment is a promising target for discovering new bioactive molecules with pharmaceutical applications. Phenomena in the ocean such as diel vertical migration (DVM) and seasonal dynamic events influence the pattern of diversity of marine bacteria, conditioning the probability of isolation of uncultured bacteria. In this study, we report a new marine bacterium belonging to the rare biosphere, Leeuwenhoekiella parthenopeia sp. nov. Mr9T, which was isolated employing seasonal and diel sampling approaches. Its complete characterization, ecology, biosynthetic gene profiling of the whole genus Leeuwenhoekiella, and bioactivity of its extract on human cells are reported. The phylogenomic and microbial diversity studies demonstrated that this bacterium is a new and rare species, barely representing 0.0029% of the bacterial community in Mediterranean Sea metagenomes. The biosynthetic profiling of species of the genus Leeuwenhoekiella showed nine functionally related gene cluster families (GCF), none were associated with pathways responsible to produce known compounds or registered patents, therefore revealing its potential to synthesize novel bioactive compounds. In vitro screenings of L. parthenopeia Mr9T showed that the total lipid content (lipidome) of the cell membrane reduces the prostatic and brain tumor cell viability with a lower effect on normal cells. The lipidome consisted of sulfobacin A, WB 3559A, WB 3559B, docosenamide, topostin B-567, and unknown compounds. Therefore, the bioactivity could be attributed to any of these individual compounds or due to their synergistic effect. Beyond the rarity and biosynthetic potential of this bacterium, the importance and novelty of this study is the employment of sampling strategies based on ecological factors to reach the hidden microbiota, as well as the use of bacterial membrane constituents as potential novel therapeutics. Our findings open new perspectives on cultivation and the relationship between bacterial biological membrane components and their bioactivity in eukaryotic cells, encouraging similar studies in other members of the rare biosphere.

The confluence of big data and evolutionary genome mining for the discovery of natural products.

This review covers literature between 2003-2021The development and application of genome mining tools has given rise to ever-growing genetic and chemical databases and propelled natural products research into the modern age of Big Data. Likewise, an explosion of evolutionary studies has unveiled genetic patterns of natural products biosynthesis and function that support Darwin's theory of natural selection and other theories of adaptation and diversification. In this review, we aim to highlight how Big Data and evolutionary thinking converge in the study of natural products, and how this has led to an emerging sub-discipline of evolutionary genome mining of natural products. First, we outline general principles to best utilize Big Data in natural products research, addressing key considerations needed to provide evolutionary context. We then highlight successful examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes. Rather than an exhaustive list of evolution-driven discoveries, we highlight examples where Big Data and evolutionary thinking have been embraced for the evolutionary genome mining of natural products. After reviewing the nascent history of this sub-discipline, we discuss the challenges and opportunities of genomic and metabolomic tools with evolutionary foundations and/or implications and provide a future outlook for this emerging and exciting field of natural product research.

Integrating perspectives in actinomycete research: an ActinoBase review of 2020-21.

Last year ActinoBase, a Wiki-style initiative supported by the UK Microbiology Society, published a review highlighting the research of particular interest to the actinomycete community. Here, we present the second ActinoBase review showcasing selected reports published in 2020 and early 2021, integrating perspectives in the actinomycete field. Actinomycetes are well-known for their unsurpassed ability to produce specialised metabolites, of which many are used as therapeutic agents with antibacterial, antifungal, or immunosuppressive activities. Much research is carried out to understand the purpose of these metabolites in the environment, either within communities or in host interactions. Moreover, many efforts have been placed in developing computational tools to handle big data, simplify experimental design, and find new biosynthetic gene cluster prioritisation strategies. Alongside, synthetic biology has provided advances in tools to elucidate the biosynthesis of these metabolites. Additionally, there are still mysteries to be uncovered in understanding the fundamentals of filamentous actinomycetes' developmental cycle and regulation of their metabolism. This review focuses on research using integrative methodologies and approaches to understand the bigger picture of actinomycete biology, covering four research areas: i) technology and methodology; ii) specialised metabolites; iii) development and regulation; and iv) ecology and host interactions.

Catalytically impaired TrpA subunit of tryptophan synthase from Chlamydia trachomatis is an allosteric regulator of TrpB.

Intracellular growth and pathogenesis of Chlamydia species is controlled by the availability of tryptophan, yet the complete biosynthetic pathway for l-Trp is absent among members of the genus. Some representatives, however, preserve genes encoding tryptophan synthase, TrpAB - a bifunctional enzyme catalyzing the last two steps in l-Trp synthesis. TrpA (subunit α) converts indole-3-glycerol phosphate into indole and glyceraldehyde-3-phosphate (α reaction). The former compound is subsequently used by TrpB (subunit ß) to produce l-Trp in the presence of l-Ser and a pyridoxal 5'-phosphate cofactor (ß reaction). Previous studies have indicated that in Chlamydia, TrpA has lost its catalytic activity yet remains associated with TrpB to support the ß reaction. Here, we provide detailed analysis of the TrpAB from C. trachomatis D/UW-3/CX, confirming that accumulation of mutations in the active site of TrpA renders it enzymatically inactive, despite the conservation of the catalytic residues. We also show that TrpA remains a functional component of the TrpAB complex, increasing the activity of TrpB by four-fold. The side chain of non-conserved ßArg267 functions as cation effector, potentially rendering the enzyme less susceptible to the solvent ion composition. The observed structural and functional changes detected herein were placed in a broader evolutionary and genomic context, allowing identification of these mutations in relation to their trp gene contexts in which they occur. Moreover, in agreement with the in vitro data, partial relaxation of purifying selection for TrpA, but not for TrpB, was detected, reinforcing a partial loss of TrpA functions during the course of evolution.

ActDES - a curated Actinobacterial Database for Evolutionary Studies.

Actinobacteria is a large and diverse phylum of bacteria that contains medically and ecologically relevant organisms. Many members are valuable sources of bioactive natural products and chemical precursors that are exploited in the clinic and made using the enzyme pathways encoded in their complex genomes. Whilst the number of sequenced genomes has increased rapidly in the last 20 years, the large size, complexity and high G+C content of many actinobacterial genomes means that the sequences remain incomplete and consist of large numbers of contigs with poor annotation, which hinders large-scale comparative genomic and evolutionary studies. To enable greater understanding and exploitation of actinobacterial genomes, specialized genomic databases must be linked to high-quality genome sequences. Here, we provide a curated database of 612 high-quality actinobacterial genomes from 80 genera, chosen to represent a broad phylogenetic group with equivalent genome re-annotation. Utilizing this database will provide researchers with a framework for evolutionary and metabolic studies, to enable a foundation for genome and metabolic engineering, to facilitate discovery of novel bioactive therapeutics and studies on gene family evolution. This article contains data hosted by Microreact.

MIBiG 2.0: a repository for biosynthetic gene clusters of known function.

Fueled by the explosion of (meta)genomic data, genome mining of specialized metabolites has become a major technology for drug discovery and studying microbiome ecology. In these efforts, computational tools like antiSMASH have played a central role through the analysis of Biosynthetic Gene Clusters (BGCs). Thousands of candidate BGCs from microbial genomes have been identified and stored in public databases. Interpreting the function and novelty of these predicted BGCs requires comparison with a well-documented set of BGCs of known function. The MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established in 2015 to enable curation and storage of known BGCs. Here, we present MIBiG 2.0, which encompasses major updates to the schema, the data, and the online repository itself. Over the past five years, 851 new BGCs have been added. Additionally, we performed extensive manual data curation of all entries to improve the annotation quality of our repository. We also redesigned the data schema to ensure the compliance of future annotations. Finally, we improved the user experience by adding new features such as query searches and a statistics page, and enabled direct link-outs to chemical structure databases. The repository is accessible online at https://mibig.secondarymetabolites.org/.

Evolutionary dynamics of natural product biosynthesis in bacteria.

Covering: 2008 up to 2019The forces of biochemical adaptive evolution operate at the level of genes, manifesting in complex phenotypes and the global biodiversity of proteins and metabolites. While evolutionary histories have been deciphered for some other complex traits, the origins of natural product biosynthesis largely remain a mystery. This fundamental knowledge gap is surprising given the many decades of research probing the genetic, chemical, and biophysical mechanisms of bacterial natural product biosynthesis. Recently, evolutionary thinking has begun to permeate this otherwise mechanistically dominated field. Natural products are now sometimes referred to as 'specialized' rather than 'secondary' metabolites, reinforcing the importance of their biological and ecological functions. Here, we review known evolutionary mechanisms underlying the overwhelming chemical diversity of bacterial secondary metabolism, focusing on enzyme promiscuity and the evolution of enzymatic domains that enable metabolic traits. We discuss the mechanisms that drive the assembly of natural product biosynthetic gene clusters and propose formal definitions for 'specialized' and 'secondary' metabolism. We further explore how biosynthetic gene clusters evolve to synthesize related molecular species, and in turn how the biological and ecological roles that emerge from metabolic diversity are acted on by selection. Finally, we reconcile chemical, functional, and genetic data into an evolutionary model, the dynamic chemical matrix evolutionary hypothesis, in which the relationships between chemical distance, biomolecular activity, and relative fitness shape adaptive landscapes.

A computational framework to explore large-scale biosynthetic diversity.

Genome mining has become a key technology to exploit natural product diversity. Although initially performed on a single-genome basis, the process is now being scaled up to mine entire genera, strain collections and microbiomes. However, no bioinformatic framework is currently available for effectively analyzing datasets of this size and complexity. In the present study, a streamlined computational workflow is provided, consisting of two new software tools: the 'biosynthetic gene similarity clustering and prospecting engine' (BiG-SCAPE), which facilitates fast and interactive sequence similarity network analysis of biosynthetic gene clusters and gene cluster families; and the 'core analysis of syntenic orthologues to prioritize natural product gene clusters' (CORASON), which elucidates phylogenetic relationships within and across these families. BiG-SCAPE is validated by correlating its output to metabolomic data across 363 actinobacterial strains and the discovery potential of CORASON is demonstrated by comprehensively mapping biosynthetic diversity across a range of detoxin/rimosamide-related gene cluster families, culminating in the characterization of seven detoxin analogues.

EvoMining reveals the origin and fate of natural product biosynthetic enzymes.

Natural products (NPs), or specialized metabolites, are important for medicine and agriculture alike, and for the fitness of the organisms that produce them. NP genome-mining aims at extracting biosynthetic information from the genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process, the likelihood of identifying truly novel systems by this approach is low. To overcome this limitation, we previously introduced EvoMining, a genome-mining approach that incorporates evolutionary principles. Here, we release and use our latest EvoMining version, which includes novel visualization features and customizable databases, to analyse 42 central metabolic enzyme families (EFs) conserved throughout Actinobacteria, Cyanobacteria, Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these 42 families are lineage specific, opening the metabolic space related to 'shell' enzymes. These enzymes, which have been overlooked, are EFs with orthologues present in most of the genomes of a taxonomic group, but not in all. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving Archaea and Bacteria adaptive evolution. By defining the origin and fate of enzymes, EvoMining complements traditional genome-mining approaches as an unbiased strategy and opens the door to gaining insights into the evolution of NP biosynthesis. We anticipate that EvoMining will be broadly used for evolutionary studies, and for generating predictions of unprecedented chemical scaffolds and new antibiotics. This article contains data hosted by Microreact.

Cycad Coralloid Roots Contain Bacterial Communities Including Cyanobacteria and Caulobacter spp. That Encode Niche-Specific Biosynthetic Gene Clusters.

Cycads are the only early seed plants that have evolved a specialized root to host endophytic bacteria that fix nitrogen. To provide evolutionary and functional insights into this million-year old symbiosis, we investigate endophytic bacterial sub-communities isolated from coralloid roots of species from Dioon (Zamiaceae) sampled from their natural habitats. We employed a sub-community co-culture experimental strategy to reveal both predominant and rare bacteria, which were characterized using phylogenomics and detailed metabolic annotation. Diazotrophic plant endophytes, including Bradyrhizobium, Burkholderia, Mesorhizobium, Rhizobium, and Nostoc species, dominated the epiphyte-free sub-communities. Draft genomes of six cyanobacteria species were obtained after shotgun metagenomics of selected sub-communities. These data were used for whole-genome inferences that suggest two Dioon-specific monophyletic groups, and a level of specialization characteristic of co-evolved symbiotic relationships. Furthermore, the genomes of these cyanobacteria were found to encode unique biosynthetic gene clusters, predicted to direct the synthesis of specialized metabolites, mainly involving peptides. After combining genome mining with detection of pigment emissions using multiphoton excitation fluorescence microscopy, we also show that Caulobacter species co-exist with cyanobacteria, and may interact with them by means of a novel indigoidine-like specialized metabolite. We provide an unprecedented view of the composition of the cycad coralloid root, including phylogenetic and functional patterns mediated by specialized metabolites that may be important for the evolution of ancient symbiotic adaptations.