Pollen Streptomyces Produce Antibiotic That Inhibits the Honey Bee Pathogen Paenibacillus larvae

Humans use natural products to treat disease; similarly, some insects use natural products produced by Actinobacteria to combat infectious pathogens. Honey bees, Apis mellifera, are ecologically and economically important for their critical role as plant pollinators and are host to diverse and potentially virulent pathogens that threaten hive health. Here, we provide evidence that Actinobacteria that can suppress pathogenic microbes are associated with A. mellifera. We show through culture-dependent approaches that Actinobacteria in the genus Streptomyces are commonly isolated from foraging bees, and especially common in pollen stores. One strain, isolated from pollen stores, exhibited pronounced inhibitory activity against Paenibacillus larvae, the causative agent of American foulbrood. Bioassay-guided HPLC fractionation, followed by NMR and mass spectrometry, identified the known macrocyclic polyene lactam, piceamycin that was responsible for this activity. Further, we show that in its purified form, piceamycin has potent inhibitory activity toward P. larvae. Our results suggest that honey bees may use pollen-derived Actinobacteria and their associated small molecules to mediate colony health. Given the importance of honey bees to modern agriculture and their heightened susceptibility to disease, the discovery and development of antibiotic compounds from hives could serve as an important strategy in supporting disease management within apiaries.National Institute for Health/[U19 AI142720]/NIH/Estados UnidosNational Institute of Food and Agriculture/[WISO1321]/NIFA/Estados UnidosUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Estructuras Microscópicas (CIEMIC)UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biología Celular y Molecular (CIBCM

Large-Scale Bioinformatics Analysis of Bacillus Genomes Uncovers Conserved Roles of Natural Products in Bacterial Physiology

ABSTRACT Bacteria possess an amazing capacity to synthesize a diverse range of structurally complex, bioactive natural products known as specialized (or secondary) metabolites. Many of these specialized metabolites are used as clinical therapeutics, while others have important ecological roles in microbial communities. The biosynthetic gene clusters (BGCs) that generate these metabolites can be identified in bacterial genome sequences using their highly conserved genetic features. We analyzed an unprecedented 1,566 bacterial genomes from Bacillus species and identified nearly 20,000 BGCs. By comparing these BGCs to one another as well as a curated set of known specialized metabolite BGCs, we discovered that the majority of Bacillus natural products are comprised of a small set of highly conserved, well-distributed, known natural product compounds. Most of these metabolites have important roles influencing the physiology and development of Bacillus species. We identified, in addition to these characterized compounds, many unique, weakly conserved BGCs scattered across the genus that are predicted to encode unknown natural products. Many of these “singleton” BGCs appear to have been acquired via horizontal gene transfer. Based on this large-scale characterization of metabolite production in the Bacilli , we go on to connect the alkylpyrones, natural products that are highly conserved but previously biologically uncharacterized, to a role in Bacillus physiology: inhibiting spore development. IMPORTANCE Bacilli are capable of producing a diverse array of specialized metabolites, many of which have gained attention for their roles as signals that affect bacterial physiology and development. Up to this point, however, the Bacillus genus’s metabolic capacity has been underexplored. We undertook a deep genomic analysis of 1,566 Bacillus genomes to understand the full spectrum of metabolites that this bacterial group can make. We discovered that the majority of the specialized metabolites produced by Bacillus species are highly conserved, known compounds with important signaling roles in the physiology and development of this bacterium. Additionally, there is significant unique biosynthetic machinery distributed across the genus that might lead to new, unknown metabolites with diverse biological functions. Inspired by the findings of our genomic analysis, we speculate that the highly conserved alkylpyrones might have an important biological activity within this genus. We go on to validate this prediction by demonstrating that these natural products are developmental signals in Bacillus and act by inhibiting sporulation

The Genome Sequence of the Leaf-Cutter Ant Atta cephalotes Reveals Insights into Its Obligate Symbiotic Lifestyle

Leaf-cutter ants are one of the most important herbivorous insects in the Neotropics, harvesting vast quantities of fresh leaf material. The ants use leaves to cultivate a fungus that serves as the colony's primary food source. This obligate ant-fungus mutualism is one of the few occurrences of farming by non-humans and likely facilitated the formation of their massive colonies. Mature leaf-cutter ant colonies contain millions of workers ranging in size from small garden tenders to large soldiers, resulting in one of the most complex polymorphic caste systems within ants. To begin uncovering the genomic underpinnings of this system, we sequenced the genome of Atta cephalotes using 454 pyrosequencing. One prediction from this ant's lifestyle is that it has undergone genetic modifications that reflect its obligate dependence on the fungus for nutrients. Analysis of this genome sequence is consistent with this hypothesis, as we find evidence for reductions in genes related to nutrient acquisition. These include extensive reductions in serine proteases (which are likely unnecessary because proteolysis is not a primary mechanism used to process nutrients obtained from the fungus), a loss of genes involved in arginine biosynthesis (suggesting that this amino acid is obtained from the fungus), and the absence of a hexamerin (which sequesters amino acids during larval development in other insects). Following recent reports of genome sequences from other insects that engage in symbioses with beneficial microbes, the A. cephalotes genome provides new insights into the symbiotic lifestyle of this ant and advances our understanding of host–microbe symbioses

Unique Honey Bee (<i>Apis mellifera</i>) Hive Component-Based Communities as Detected by a Hybrid of Phospholipid Fatty-Acid and Fatty-Acid Methyl Ester Analyses

<div><p>Microbial communities (microbiomes) are associated with almost all metazoans, including the honey bee <i>Apis mellifera</i>. Honey bees are social insects, maintaining complex hive systems composed of a variety of integral components including bees, comb, propolis, honey, and stored pollen. Given that the different components within hives can be physically separated and are nutritionally variable, we hypothesize that unique microbial communities may occur within the different microenvironments of honey bee colonies. To explore this hypothesis and to provide further insights into the microbiome of honey bees, we use a hybrid of fatty acid methyl ester (FAME) and phospholipid-derived fatty acid (PLFA) analysis to produce broad, lipid-based microbial community profiles of stored pollen, adults, pupae, honey, empty comb, and propolis for 11 honey bee hives. Averaging component lipid profiles by hive, we show that, in decreasing order, lipid markers representing fungi, Gram-negative bacteria, and Gram-positive bacteria have the highest relative abundances within honey bee colonies. Our lipid profiles reveal the presence of viable microbial communities in each of the six hive components sampled, with overall microbial community richness varying from lowest to highest in honey, comb, pupae, pollen, adults and propolis, respectively. Finally, microbial community lipid profiles were more similar when compared by component than by hive, location, or sampling year. Specifically, we found that individual hive components typically exhibited several dominant lipids and that these dominant lipids differ between components. Principal component and two-way clustering analyses both support significant grouping of lipids by hive component. Our findings indicate that in addition to the microbial communities present in individual workers, honey bee hives have resident microbial communities associated with different colony components.</p></div

Lipid richness for honey bees and their hive components.

<p>Average number of individual lipids detected from each hive component. Error bars represent standard error of the mean. Letters represent Tukey-Kramer HSD pairwise comparisons, with those groups not possessing overlap in letters being significantly different. Those groups sharing letters do not significantly differ.</p

P-Values from Significant Tukey-Kramer HSD Pairwise Comparisons of Lipid Profiles By Component.

<p>*—Comparison Not Valid;</p><p>NS—Not Significant</p><p>P-Values from Significant Tukey-Kramer HSD Pairwise Comparisons of Lipid Profiles By Component.</p

Rarefaction and lipid accumulation curves for honey bees and their hive components.

<p><b>A.)</b> Observed and estimated curves resulting from community analyses of adults, honey, and pollen using <i>Mao Tau</i> and <i>Chao2</i> methods. <b>B.)</b> Observed and estimated curves from comb, pupae, and propolis community analyses. Dashed lines represent corresponding confidence intervals.</p

P-values from Tukey-Kramer HSD Pairwise Comparisons of Total Number of Lipids Detected in Each Component.

<p>NS—Not Significant</p><p>P-values from Tukey-Kramer HSD Pairwise Comparisons of Total Number of Lipids Detected in Each Component.</p

Principal component analysis of lipid profile for honey bees and their hive components.

<p>Score plot shows variation in PLFA-FAME profiles by hive components. Lines drawn delineate sample aggregates. Inlay displays one propolis sample that skewed the plot. Main plot is redrawn without that data point. When produced by sample year, individual hive or location, no clustering is readily apparent.</p