Dissecting Disease-Suppressive Rhizosphere Microbiomes by Functional Amplicon Sequencing and 10× Metagenomics

Exploring the biosynthesis potential of permafrost microbiomes

BACKGROUND

Permafrost microbiomes are of paramount importance for the biogeochemistry of high latitude soils and while endemic biosynthetic domain sequences involved in secondary metabolism have been found in polar surface soils, the biosynthetic potential of permafrost microbiomes remains unexplored. Moreover, the nature of these ecosystems facilitates the unique opportunity to study the distribution and diversity of biosynthetic genes in relic DNA from ancient microbiomes. To explore the biosynthesis potential in permafrost, we used adenylation (AD) domain sequencing to evaluate non-ribosomal peptide (NRP) production in permafrost cores housing microbiomes separated at kilometer and kiloyear scales.

RESULTS

Permafrost microbiomes represented NRP repertoires significantly different from that of temperate soil microbiomes, but as for temperate soils, the estimated domain richness and diversity was strongly correlated to the bacterial taxonomic diversity across locations. Furthermore, we found significant differences in both community composition and AD domain composition across geographical and temporal distances. Overall, the vast majority of biosynthetic domains showed below 90% amino acid similarity to characterized BGCs, confirming the high degree of novelty of NRPs inherent to permafrost microbiomes. Using available metagenomic sequences, we further identified a high biosynthetic diversity beyond NRPs throughout arctic surface soils down to deep and ancient (megayear old) permafrost microbiomes.

CONCLUSION

We have shown that arctic permafrost microbiomes harbor a unique biosynthetic repertoire rich in hitherto undescribed NRPs. This diversity is driven by geographic separation across kilometer scales and by the bacterial taxonomic diversity between microbiomes confined in separate permafrost layers. Hence the permafrost biome represents a unique resource for studying secondary metabolism, and potentially for the discovery of novel drug leads.

From Microbes to Microbiomes: Applications for Plant Health and Sustainable Agriculture

Plant-microbe interaction research has had a transformative trajectory, from individual microbial isolate studies to comprehensive analyses of plant microbiomes within the broader phytobiome framework. Acknowledging the indispensable role of plant microbiomes in shaping plant health, agriculture, and ecosystem resilience, we underscore the urgent need for sustainable crop production strategies in the face of contemporary challenges. We discuss how the synergies between advancements in 'omics technologies and artificial intelligence can help advance the profound potential of plant microbiomes. Furthermore, we propose a multifaceted approach encompassing translational considerations, transdisciplinary research initiatives, public-private partnerships, regulatory policy development, and pragmatic expectations for the practical application of plant microbiome knowledge across diverse agricultural landscapes. We advocate for strategic collaboration and intentional transdisciplinary efforts to unlock the benefits offered by plant microbiomes and address pressing global issues in food security. By emphasizing a nuanced understanding of plant microbiome complexities and fostering realistic expectations, we encourage the scientific community to navigate the transformative journey from discoveries in the laboratory to field applications. As companies specializing in agricultural microbes and microbiomes undergo shifts, we highlight the necessity of understanding how to approach sustainable agriculture with site-specific management solutions. While cautioning against overpromising, we underscore the excitement of exploring the many impacts of microbiome-plant interactions. We emphasize the importance of collaborative endeavors with societal partners to accelerate our collective capacity to harness the diverse and yet-to-be-discovered beneficial activities of plant microbiomes.

LRTK: a platform agnostic toolkit for linked-read analysis of both human genome and metagenome

BACKGROUND

Linked-read sequencing technologies generate high-base quality short reads that contain extrapolative information on long-range DNA connectedness. These advantages of linked-read technologies are well known and have been demonstrated in many human genomic and metagenomic studies. However, existing linked-read analysis pipelines (e.g., Long Ranger) were primarily developed to process sequencing data from the human genome and are not suited for analyzing metagenomic sequencing data. Moreover, linked-read analysis pipelines are typically limited to 1 specific sequencing platform.

FINDINGS

To address these limitations, we present the Linked-Read ToolKit (LRTK), a unified and versatile toolkit for platform agnostic processing of linked-read sequencing data from both human genome and metagenome. LRTK provides functions to perform linked-read simulation, barcode sequencing error correction, barcode-aware read alignment and metagenome assembly, reconstruction of long DNA fragments, taxonomic classification and quantification, and barcode-assisted genomic variant calling and phasing. LRTK has the ability to process multiple samples automatically and provides users with the option to generate reproducible reports during processing of raw sequencing data and at multiple checkpoints throughout downstream analysis. We applied LRTK on linked reads from simulation, mock community, and real datasets for both human genome and metagenome. We showcased LRTK's ability to generate comparative performance results from preceding benchmark studies and to report these results in publication-ready HTML document plots.

CONCLUSIONS

LRTK provides comprehensive and flexible modules along with an easy-to-use Python-based workflow for processing linked-read sequencing datasets, thereby filling the current gap in the field caused by platform-centric genome-specific linked-read data analysis tools.

Non-ribosomal peptide synthase profiles remain structurally similar despite minimally shared features across fungus-farming termite microbiomes

Fungus-farming termites (Macrotermitinae) engage in an obligate mutualism with members of the fungal genus Termitomyces, which they maintain as a monoculture on specialized comb structures. Both these comb structures and the guts of the termites host diverse bacterial communities that are believed to assist in sustaining monoculture farming through antagonist suppression. Among candidate bacteria-derived compounds serving this function are non-ribosomal peptides (NRPs), which are a highly bioactive class of specialized metabolites, frequently produced by symbionts within eukaryotic hosts. However, our understanding of specialized metabolites in termite-associated microbiomes is limited. Here we use amplicon sequencing to characterize both bacterial composition and NRP potential. We show that bacterial and NRP diversity are correlated and that the former varies more than the latter across termite host and gut and comb samples. Compositions of the two are governed by host species and sample type, with topological similarity indicating a diverse set of biosynthetic potential that is consistent with the long evolutionary history of the Macrotermitinae. The structure of both bacterial and NRP compositional networks varied similarly between guts and combs across the Macrotermitinae albeit with auxiliary termite genus-specific patterns. We observed minimal termite species-specific cores, with essentially no Macrotermitinae-wide core and an abundance of putatively novel biosynthetic gene clusters, suggesting that there is likely no single solution to antagonist suppression via specialized NRP metabolites. Our findings contribute to an improved understanding of the distribution of NRP potential in the farming termite symbiosis and will help guide targeted exploration of specialized metabolite production.

Plant Growth-Promoting Bacteria of Soil: Designing of Consortia Beneficial for Crop Production

Plant growth-promoting bacteria are commonly used in agriculture, particularly for seed inoculation. Multispecies consortia are believed to be the most promising form of these bacteria. However, designing and modeling bacterial consortia to achieve desired phenotypic outcomes in plants is challenging. This review aims to address this challenge by exploring key antimicrobial interactions. Special attention is given to approaches for developing soil plant growth-promoting bacteria consortia. Additionally, advanced omics-based methods are analyzed that allow soil microbiomes to be characterized, providing an understanding of the molecular and functional aspects of these microbial communities. A comprehensive discussion explores the utilization of bacterial preparations in biofertilizers for agricultural applications, focusing on the intricate design of synthetic bacterial consortia with these preparations. Overall, the review provides valuable insights and strategies for intentionally designing bacterial consortia to enhance plant growth and development.

Present and future outlooks on environmental DNA-based methods for antibiotic discovery

Novel antibiotics are in constant demand to combat a global increase in antibiotic-resistant infections. Bacterial natural products have been a long-standing source of antibiotic compounds, and metagenomic mining of environmental DNA (eDNA) has increasingly provided new antibiotic leads. The metagenomic small-molecule discovery pipeline can be divided into three main steps: surveying eDNA, retrieving a sequence of interest, and accessing the encoded natural product. Improvements in sequencing technology, bioinformatic algorithms, and methods for converting biosynthetic gene clusters into small molecules are steadily increasing our ability to discover metagenomically encoded antibiotics. We predict that, over the next decade, ongoing technological improvements will dramatically increase the rate at which antibiotics are discovered from metagenomes.

Role of Fungi in Imparting General Disease Suppressiveness in Soil from Organic Field

Soil microbial communities are key players responsible for imparting suppressive potential to the soil against soil-borne phytopathogens. Fungi have an immense potential to inhibit soil-borne phytopathogens, but the fungal counterpart has been less explored in this context. We assessed the composition of fungal communities in soil under long-term organic and conventional farming practice, and control soil. The disease-suppressive potential of organic field was already established. A comparative analysis of the disease suppressiveness contributed by the fungal component of soil from conventional and organic farms was assessed using dual culture assays. The quantification of biocontrol markers and total fungi was done; the characterization of fungal community was carried out using ITS-based amplicon sequencing. Soil from organic field exhibited higher disease-suppressive potential than that from conventional farming, against the pathogens selected for the study. Higher levels of hydrolytic enzymes such as chitinase and cellulase, and siderophore production were observed in soil from the organic field compared to the conventional field. Differences in community composition were observed under conventional and organic farming, with soil from organic field exhibiting specific enrichment of key biocontrol fungal genera. The fungal alpha diversity was lower in soil from the organic field compared to the conventional field. Our results highlight the role of fungi in contributing to general disease-suppressive ability of the soil against phytopathogens. The identification of fungal taxa specifically associated with organic farming can aid in understanding the mechanism of disease suppression under such a practice, and can be exploited to induce general disease suppressiveness in otherwise conducive soil.

The Use of Synthetic Microbial Communities to Improve Plant Health

Despite the numerous benefits plants receive from probiotics, maintaining consistent results across applications is still a challenge. Cultivation-independent methods associated with reduced sequencing costs have considerably improved the overall understanding of microbial ecology in the plant environment. As a result, now, it is possible to engineer a consortium of microbes aiming for improved plant health. Such synthetic microbial communities (SynComs) contain carefully chosen microbial species to produce the desired microbiome function. Microbial biofilm formation, production of secondary metabolites, and ability to induce plant resistance are some of the microbial traits to consider when designing SynComs. Plant-associated microbial communities are not assembled randomly. Ecological theories suggest that these communities have a defined phylogenetic organization structured by general community assembly rules. Using machine learning, we can study these rules and target microbial functions that generate desired plant phenotypes. Well-structured assemblages are more likely to lead to a stable SynCom that thrives under environmental stressors as compared with the classical selection of single microbial activities or taxonomy. However, ensuring microbial colonization and long-term plant phenotype stability is still one of the challenges to overcome with SynComs, as the synthetic community may change over time with microbial horizontal gene transfer and retained mutations. Here, we explored the advances made in SynCom research regarding plant health, focusing on bacteria, as they are the most dominant microbial form compared with other members of the microbiome and the most commonly found in SynCom studies.

The Golden Goal of Soil Management: Disease-Suppressive Soils

Disease-suppressive soils encompass specific plant-pathogen-microbial interactions and represent a rare example of an agroecosystem where soil conditions and microbiome together prevent the pathogen from causing disease. Such soils have the potential to serve as a model for characterizing soil pathogen-related aspects of soil health, but the mechanisms driving the establishment of suppressive soils vary and are often poorly characterized. Yet, they can serve as a resource for identifying markers for beneficial activities of soil microorganisms concerning pathogen prevention. Many recent studies have focused on the nature of disease-suppressive soils, but it has remained difficult to predict where and when they will occur. This review outlines current knowledge on the distribution of these soils, soil manipulations leading to pathogen suppression, and markers including bacterial and fungal diversity, enzymes, and secondary metabolites. The importance to consider soil legacy in research on the principles that define suppressive soils is also highlighted. The goal is to extend the context in which we understand, study, and use disease-suppressive soils by evaluating the relationships in which they occur and function. Finally, we suggest that disease-suppressive soils are critical not only for the development of indicators of soil health, but also for the exploration of general ecological principles about the surrounding landscape, effects of deeper layers of the soil profile, little studied soil organisms, and their interactions for future use in modern agriculture.

Small Spatial Scale Drivers of Secondary Metabolite Biosynthetic Diversity in Environmental Microbiomes

In the search for novel drug candidates, diverse environmental microbiomes have been surveyed for their secondary metabolite biosynthesis potential, yet little is known about the biosynthetic diversity encoded by divergent microbiomes from different ecosystems, and the environmental parameters driving this diversity. Here, we used targeted amplicon sequencing of adenylation (AD) and ketosynthase (KS) domains along with 16S sequencing to delineate the unique biosynthetic potential of microbiomes from three separate habitats (soil, water, and sediments) exhibiting unique small spatial scale physicochemical gradients. The estimated richness of AD domains was highest in marine sediments with 656 ± 58 operational biosynthetic units (OBUs), while the KS domain richness was highest in soil microbiomes with 388 ± 67 OBUs. Microbiomes with rich and diverse bacterial communities displayed the highest PK potential across all ecosystems, and on a small spatial scale, pH and salinity were significantly, positively correlated to KS domain richness in soil and aquatic systems, respectively. Integrating our findings, we were able to predict the KS domain richness with a RMSE of 31 OBUs and a R² of 0.91, and by the use of publicly available information on bacterial richness and diversity, we identified grassland biomes as being particularly promising sites for the discovery of novel polyketides. Furthermore, a focus on acidobacterial taxa is likely to be fruitful, as these were responsible for most of the variation in biosynthetic diversity. Overall, our results highlight the importance of sampling diverse environments with high taxonomic diversity in the pursuit for novel secondary metabolites. IMPORTANCE To counteract the antibiotic resistance crisis, novel anti-infective agents need to be discovered and brought to market. Microbial secondary metabolites have been important sources of inspiration for small-molecule therapeutics. However, the isolation of novel antibiotics is difficult, and the risk of rediscovery is high. With the overarching purpose of identifying promising microbiomes for discovery of novel bioactivity, we mapped out the most significant drivers of biosynthetic diversity across divergent microbiomes. We found the biosynthetic potential to be unique to individual ecosystems, and to depend on bacterial taxonomic diversity. Within systems, and on small spatial scales, pH and salinity correlated positively to the biosynthetic richness of the microbiomes, Acidobacteria representing the taxa most highly associated with biosynthetic diversity. Ultimately, understanding the key drivers of the biosynthesis potential of environmental microbiomes will allow us to focus bioprospecting efforts and facilitate the discovery of novel therapeutics.

A Comprehensive Insight of Current and Future Challenges in Large-Scale Soil Microbiome Analyses

In the last decade, various large-scale projects describing soil microbial diversity across large geographical gradients have been undertaken. However, many questions remain unanswered about the best ways to conduct these studies. In this review, we present an overview of the experience gathered during these projects, and of the challenges that future projects will face, such as standardization of protocols and results, considering the temporal variation of microbiomes, and the legal constraints limiting such studies. We also present the arguments for and against the exhaustive description of soil microbiomes. Finally, we look at future developments of soil microbiome studies, notably emphasizing the important role of cultivation techniques.

Disentangling the genetic basis of rhizosphere microbiome assembly in tomato

Microbiomes play a pivotal role in plant growth and health, but the genetic factors involved in microbiome assembly remain largely elusive. Here, we map the molecular features of the rhizosphere microbiome as quantitative traits of a diverse hybrid population of wild and domesticated tomato. Gene content analysis of prioritized tomato quantitative trait loci suggests a genetic basis for differential recruitment of various rhizobacterial lineages, including a Streptomyces-associated 6.31 Mbp region harboring tomato domestication sweeps and encoding, among others, the iron regulator FIT and the water channel aquaporin SlTIP2.3. Within metagenome-assembled genomes of root-associated Streptomyces and Cellvibrio, we identify bacterial genes involved in metabolism of plant polysaccharides, iron, sulfur, trehalose, and vitamins, whose genetic variation associates with specific tomato QTLs. By integrating 'microbiomics' and quantitative plant genetics, we pinpoint putative plant and reciprocal rhizobacterial traits underlying microbiome assembly, thereby providing a first step towards plant-microbiome breeding programs.

Exploring the roles of microbes in facilitating plant adaptation to climate change

Plants benefit from their close association with soil microbes which assist in their response to abiotic and biotic stressors. Yet much of what we know about plant stress responses is based on studies where the microbial partners were uncontrolled and unknown. Under climate change, the soil microbial community will also be sensitive to and respond to abiotic and biotic stressors. Thus, facilitating plant adaptation to climate change will require a systems-based approach that accounts for the multi-dimensional nature of plant-microbe-environment interactions. In this perspective, we highlight some of the key factors influencing plant-microbe interactions under stress as well as new tools to facilitate the controlled study of their molecular complexity, such as fabricated ecosystems and synthetic communities. When paired with genomic and biochemical methods, these tools provide researchers with more precision, reproducibility, and manipulability for exploring plant-microbe-environment interactions under a changing climate.

The natural product biosynthesis potential of the microbiomes of Earth – Bioprospecting for novel anti-microbial agents in the meta-omics era

As we stand on the brink of the post-antibiotic era, we are in dire need of novel antimicrobial compounds. Microorganisms produce a wealth of so-called secondary metabolites and have been our most prolific source of antibiotics so far. However, rediscovery of known antibiotics from well-studied cultured microorganisms, and the fact that the majority of microorganisms in the environment are out of reach by means of conventional cultivation techniques, have led to the exploration of the biosynthetic potential in natural microbial communities by novel approaches. In this mini review we discuss how sequence-based analyses have exposed an unprecedented wealth of potential for secondary metabolite production in soil, marine, and host-associated microbiomes, with a focus on the biosynthesis of non-ribosomal peptides and polyketides. Furthermore, we discuss how the complexity of natural microbiomes and the lack of standardized methodology has complicated comparisons across biomes. Yet, as even the most commonly sampled microbiomes hold promise of providing novel classes of natural products, we lastly discuss the development of approaches applied in the translation of the immense biosynthetic diversity of natural microbiomes to the procurement of novel antibiotics.

Evaluation of Disease Suppressiveness of Soils in Croplands by Co-Cultivation of Pathogenic Fusarium oxysporum and Indigenous Soil Microorganisms

An evaluation of suppressiveness against soil-borne diseases is important for their control. We herein assessed disease suppression against F. oxysporum f. sp. spinaciae using the Fusarium co-cultivation method in 75 soils collected from croplands around the country. The suppressive effects of soil microbes against F. oxysporum growth were examined by simultaneously culturing soil suspensions and F. oxysporum f. sp. spinaciae on a culture medium. The growth degree of F. oxysporum on the medium varied among the 75 soils tested, and 14 soils showing different degrees of growth were selected to investigate the incidence of spinach wilt by cultivating spinach inoculated with the pathogenic F. oxysporum strain. A correlation (r=0.831, P<0.001) was observed between the disease incidence of spinach wilt and the growth degree of F. oxysporum using the co-cultivation method in the 14 selected soils. No correlations were noted between chemical and biological parameters (including pH and the population density of microbes, except for the growth degree of F. oxysporum) and the growth degree of F. oxysporum and incidence of spinach wilt, indicating that it was not possible to predict the degree of growth or disease incidence based on specific chemical and biological characteristics or their combination. The present results suggest that an evaluation of the growth degree of F. oxysporum by the Fusarium co-cultivation will be useful for diagnosing the disease suppressiveness of soil against pathogenic F. oxysporum in croplands.

Pan-genome analysis identifies intersecting roles for Pseudomonas specialized metabolites in potato pathogen inhibition

Agricultural soil harbors a diverse microbiome that can form beneficial relationships with plants, including the inhibition of plant pathogens. Pseudomonas spp. are one of the most abundant bacterial genera in the soil and rhizosphere and play important roles in promoting plant health. However, the genetic determinants of this beneficial activity are only partially understood. Here, we genetically and phenotypically characterize the Pseudomonas fluorescens population in a commercial potato field, where we identify strong correlations between specialized metabolite biosynthesis and antagonism of the potato pathogens Streptomyces scabies and Phytophthora infestans. Genetic and chemical analyses identified hydrogen cyanide and cyclic lipopeptides as key specialized metabolites associated with S. scabies inhibition, which was supported by in planta biocontrol experiments. We show that a single potato field contains a hugely diverse and dynamic population of Pseudomonas bacteria, whose capacity to produce specialized metabolites is shaped both by plant colonization and defined environmental inputs.

Potato scab and blight are two major diseases which can cause heavy crop losses. They are caused, respectively, by the bacterium Streptomyces scabies and an oomycete (a fungus-like organism) known as Phytophthora infestans.

Fighting these disease-causing microorganisms can involve crop management techniques – for example, ensuring that a field is well irrigated helps to keep S. scabies at bay. Harnessing biological control agents can also offer ways to control disease while respecting the environment. Biocontrol bacteria, such as Pseudomonas, can produce compounds that keep S. scabies and P. infestans in check. However, the identity of these molecules and how irrigation can influence Pseudomonas population remains unknown.

To examine these questions, Pacheco-Moreno et al. sampled and isolated hundreds of Pseudomonas strains from a commercial potato field, closely examining the genomes of 69 of these. Comparing the genetic information of strains based on whether they could control the growth of S. scabies revealed that compounds known as cyclic lipopeptides are key to controlling the growth of S. scabies and P. infestans. Whether the field was irrigated also had a large impact on the strains forming the Pseudomonas population.

Working out how Pseudomonas bacteria block disease could speed up the search for biological control agents. The approach developed by Pacheco-Moreno et al. could help to predict which strains might be most effective based on their genetic features. Similar experiments could also work for other combinations of plants and diseases.

Needles in haystacks: reevaluating old paradigms for the discovery of bacterial secondary metabolites

Covering: up to 2021Natural products research is in the midst of a renaissance ushered in by a modern understanding of microbiology and the technological explosions of genomics and metabolomics. As the exploration of uncharted chemical space expands into high-throughput discovery campaigns, it has become increasingly clear how design elements influence success: (bio)geography, habitat, community dynamics, culturing/induction methods, screening methods, dereplication, and more. We explore critical considerations and assumptions in natural products discovery. We revisit previous estimates of chemical rediscovery and discuss their relatedness to study design and producer taxonomy. Through frequency analyses of biosynthetic gene clusters in publicly available genomic data, we highlight phylogenetic biases that influence rediscovery rates. Through selected examples of how study design at each level determines discovery outcomes, we discuss the challenges and opportunities for the future of high-throughput natural product discovery.

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.

Transporter Gene-mediated Typing for Detection and Genome Mining of Lipopeptide-producing Pseudomonas

Pseudomonas lipopeptides (LPs) are involved in diverse ecological functions and have biotechnological application potential associated with their antimicrobial and/or antiproliferative activities. They are synthesized by multimodular nonribosomal peptide synthetases which, together with transport and regulatory proteins, are encoded by large biosynthetic gene clusters (BGCs). These secondary metabolites are classified in distinct families based on the sequence and length of the oligopeptide and size of the macrocycle, if present. The phylogeny of PleB, the MacB-like transporter that is part of a dedicated ATP-dependent tripartite efflux system driving export of Pseudomonas LPs, revealed a strong correlation with LP chemical diversity. As each LP BGC carries its cognate pleB, PleB is suitable as a diagnostic sequence for genome mining, allowing assignment of the putative metabolite to a particular LP family. In addition, pleB proved to be a suitable target gene for an alternative PCR method for detecting LP-producing Pseudomonas sp. and did not rely on amplification of catalytic domains of the biosynthetic enzymes. Combined with amplicon sequencing, this approach enabled typing of Pseudomonas strains as potential producers of a LP belonging to one of the known LP families, underscoring its value for strain prioritization. This finding was validated by chemical characterization of known LPs from three different families secreted by novel producers isolated from the rice or maize rhizosphere, namely, the type strains of Pseudomonas fulva (putisolvin), Pseudomonas zeae (tensin), and Pseudomonas xantholysinigenes (xantholysin). In addition, a new member of the Bananamide family, prosekin, was discovered in the type strain of Pseudomonas prosekii, which is an Antarctic isolate.

IMPORTANCEPseudomonas spp. are ubiquitous bacteria able to thrive in a wide range of ecological niches, and lipopeptides often support their lifestyle but also their interaction with other micro- and macro-organisms. Therefore, the production of lipopeptides is widespread among Pseudomonas strains. Consequently, Pseudomonas lipopeptide research not only affects chemists and microbiologists but also touches a much broader audience, including biochemists, ecologists, and plant biologists. In this study, we present a reliable transporter gene-guided approach for the detection and/or typing of Pseudomonas lipopeptide producers. Indeed, it allows us to readily assess the lipopeptide diversity among sets of Pseudomonas isolates and differentiate strains likely to produce known lipopeptides from producers of potentially novel lipopeptides. This work provides a valuable tool that can also be integrated in a genome mining strategy and adapted for the typing of other specialized metabolites.

Disentangling soil microbiome functions by perturbation

Soil biota contribute to diverse soil ecosystem services such as greenhouse gas mitigation, carbon sequestration, pollutant degradation, plant disease suppression and nutrient acquisition for plant growth. Here, we provide detailed insight into different perturbation approaches to disentangle soil microbiome functions and to reveal the underlying mechanisms. By applying perturbation, one can generate compositional and functional shifts of complex microbial communities in a controlled way. Perturbations can reduce microbial diversity, diminish the abundance of specific microbial taxa and thereby disturb the interactions within the microbial consortia and with their eukaryotic hosts. Four different microbiome perturbation approaches, namely selective heat, specific biocides, dilution-to-extinction and genome editing are the focus of this mini-review. We also discuss the potential of perturbation approaches to reveal the tipping point at which specific soil functions are lost and to link this change to key microbial taxa involved in specific microbiome-associated phenotypes.

Ultra-resolution Metagenomics: When Enough Is Not Enough

Technological advances in community sequencing have steadily increased the taxonomic resolution at which microbes can be delineated. In high-resolution metagenomics, bacterial strains can now be resolved, enhancing medical microbiology and the description of microbial evolution in vivo. In the Hildebrand lab, we are researching novel approaches to further increase the phylogenetic resolution of metagenomics. I propose that ultra-resolution metagenomics will be the next qualitative level of community sequencing, classified by the accurate resolution of ultra-rare genetic events, such as subclonal mutations present in all populations of evolving cells. This will be used to quantify evolutionary processes at ecologically relevant scales, monitor the progress of infections within a patient, and accurately track pathogens in food and infection chains. However, to develop this next metagenomic generation, we first need to understand the currently imposed limits of sequencing technologies, metagenomic strain delineation, and genome reconstructions.

A Community Effort: Combining Functional Amplicon Sequencing and Metagenomics Reveals Potential Biosynthetic Gene Clusters Associated with Protective Phenotypes in Rhizosphere Microbiomes

Soil-dwelling microorganisms associated with plant roots carry out essential processes that promote plant growth and productivity. In addition to these beneficial functions, the rhizosphere microbiome also serves as the first line of defense against many plant pathogens. While many rhizobacteria are capable of producing antifungal natural products, fungal pathogens, such as those belonging to the genus Fusarium, continue to be a major threat to agricultural crops worldwide. In this issue, Tracanna and coworkers (V. Tracanna, A. Ossowicki, M. L. C. Petrus, S. Overduin, et al., mSystems 6:e01116-20, 2021, https://doi.org/10.1128/mSystems.01116-20) implement a targeted amplicon sequencing approach to identify conserved domains and specific metabolic pathways shared among soil samples with antagonistic activities against Fusarium culmorum. They also introduce dom2BGC, an open-source annotation platform that builds co-occurrence networks of natural product-associated domains across samples and aids in putative gene cluster reconstruction. When coupled with metagenomics, functional amplicon sequencing and the dom2BGC pipeline can aid in identifying mechanisms and potential metabolites associated with particular microbiome-associated phenotypes.