Trachymyrmex septentrionalis ants promote fungus garden hygiene using Trichoderma-derived metabolite cues
Edited by Caroline Harwood, University of Washington, Seattle, WA; received November 15, 2022; accepted May 4, 2023
Significance
An extended defense response may exist in any relationship where one partner benefits from defending a mutualistic partner. Such a response is observed in the fungus-growing ant symbiosis, where ants must identify and remove pathogens of their symbiotic fungus gardens. Here, we describe how metabolites from the common fungus garden inhabitant Trichoderma induce Trachymyrmex septentrionalis ant weeding behavior. Ants removed fungus garden pieces inoculated with Trichoderma spores or peptaibol-rich Trichoderma extracts, and peptaibols as a class cued ant defensive behavior, allowing T. septentrionalis to identify acute Trichoderma infections of their fungus gardens. Extended defense responses mediated by chemical cues may be underappreciated mechanisms that structure symbiotic interactions.
Abstract
Fungus-growing ants depend on a fungal mutualist that can fall prey to fungal pathogens. This mutualist is cultivated by these ants in structures called fungus gardens. Ants exhibit weeding behaviors that keep their fungus gardens healthy by physically removing compromised pieces. However, how ants detect diseases of their fungus gardens is unknown. Here, we applied the logic of Koch’s postulates using environmental fungal community gene sequencing, fungal isolation, and laboratory infection experiments to establish that Trichoderma spp. can act as previously unrecognized pathogens of Trachymyrmex septentrionalis fungus gardens. Our environmental data showed that Trichoderma are the most abundant noncultivar fungi in wild T. septentrionalis fungus gardens. We further determined that metabolites produced by Trichoderma induce an ant weeding response that mirrors their response to live Trichoderma. Combining ant behavioral experiments with bioactivity-guided fractionation and statistical prioritization of metabolites in Trichoderma extracts demonstrated that T. septentrionalis ants weed in response to peptaibols, a specific class of secondary metabolites known to be produced by Trichoderma fungi. Similar assays conducted using purified peptaibols, including the two previously undescribed peptaibols trichokindins VIII and IX, suggested that weeding is likely induced by peptaibols as a class rather than by a single peptaibol metabolite. In addition to their presence in laboratory experiments, we detected peptaibols in wild fungus gardens. Our combination of environmental data and laboratory infection experiments strongly support that peptaibols act as chemical cues of Trichoderma pathogenesis in T. septentrionalis fungus gardens.
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The transition to agriculture in humans ~10,000 y ago is often cited as the key innovation that led to large and complex human civilizations (1, 2). Yet, insects have practiced farming on a much longer timescale. For example, fungus-growing ants have farmed specific “cultivar” fungi (Agaricales: mainly Agaricaceae) for ~50 My (3). Fungus-growing ants include over 250 known species, the most complex of which, Atta leaf-cutting ants, create colonies that rival large cities in population size (4). Fungus-growing ants obligately rely on their cultivar fungus to digest otherwise inaccessible plant nutrients. In underground fungus gardens, the cultivar fungus breaks down recalcitrant organic material provided by the ants and in return produces specialized structures that the ants consume, making the cultivar fungus a valuable resource for the ants (3, 5).
Valuable crop resources require maintenance and protection. In ant fungus gardens, Escovopsis fungi are well known as specialized parasites, especially in the tropics (6, 7). Infection of the fungus garden by Escovopsis decreases colony fitness and can lead to colony collapse (6–9). However, Escovopsis does not regularly parasitize fungus gardens cultivated by Trachymyrmex septentrionalis, the northernmost fungus-growing ant, a finding based on a single culture-based study that detected Trichoderma and several other microfungi but not Escovopsis in T. septentrionalis fungus gardens and that did not test its infectiveness (10). Many other fungi have also been isolated from ant fungus gardens, although the culture-based methods used and the often nonsystematic sampling obscures their ecological distribution and symbiotic role (6, 7, 10–15). Beyond Escovopsis, only Trichoderma and Syncephalastrum have been shown to exhibit some degree of pathogenesis toward Atta ant fungus gardens [but not toward T. septentrionalis; (6, 16, 17)]. More work is needed to fully understand the diversity and ecology of these and other potential fungus garden pathogens and the mechanisms by which ants respond to protect their fungus gardens.
Ants have developed numerous chemical and behavioral mechanisms to avoid infection of their fungus gardens and prevent colony collapse (7). Chemical defenses include the application of antimicrobials from ant metapleural gland and fecal secretions (18–21), and from antibiotic-producing Pseudonocardia bacteria that the ants host on their cuticles (22, 23). Ant behavioral defenses include grooming their own bodies and those of their nestmates (24), task partitioning between different members of the colony (25–27), and preprocessing of foraged material before its incorporation into the fungus garden (28, 29). Fungus garden grooming (removal of pathogen spores by moving fungus garden hyphae through ant mouthparts) and especially weeding (removal of infected fungus garden fragments) represent important ant behavioral responses to fungal pathogens that have invaded the fungus garden (17, 27, 30, 31). Although these defensive responses have been described in detail, how fungus-growing ants detect threats to their fungus gardens remains poorly understood (32).
Insects are well-known to communicate using chemical cues. For example, Mastotermes darwiniensis termite soldiers respond to the cuticular hydrocarbon p-benzoquinone with increased mandible openings, indicating excitement (33). In another example, diverse ant species destroy diseased pupae in response to cuticular hydrocarbons emitted during fungal infection (34). Although the mechanism by which fungus-growing ants detect pathogen infections remains unknown, they do detect and respond to chemical cues that promote other aspects of fungus-garden health. For example, Acromyrmex lundii ants use carbon dioxide as a spatial cue to position their fungus gardens at optimum soil depth (35). Based on unfavorable CO2 levels, ants will relocate their gardens, a remarkable demonstration of their sensitivity to small molecule cues. Pathogenic fungi also produce metabolites that can affect fungus-growing ant health and behavior such as shearanine D produced by Escovopsis fungus garden pathogens, which reduces ant movement, inhibits Pseudonocardia growth, and directly causes ant death (36, 37). Thus, chemical communication mechanistically underpins diverse symbiotic interactions in ant fungus gardens.
In this study, we sought to identify the chemical cues that induce hygienic weeding behavior during infections of ant fungus gardens. We established that Trichoderma fungi are common in T. septentrionalis ant fungus gardens and that T. septentrionalis ants weed their fungus gardens in response to treatments with live Trichoderma spores, Trichoderma chemical extracts and fractions, and Trichoderma-derived pure compounds. Our results suggest that peptaibol metabolites are produced by Trichoderma fungi during fungus garden infection and cue ant weeding behaviors that promote fungus garden hygiene. This study fills the gap between the well-studied hygienic behavioral responses of fungus-growing ants and the hitherto unknown chemical cues that induce them. Such chemical cues are likely widespread in other agricultural systems where they are used by hosts to detect and prevent pathogen infections.
Results
Trichoderma spp. Are Common Natural Inhabitants of T. septentrionalis Fungus Gardens.
We used internal transcribed spacer region 2 (ITS2) community amplicon sequencing to investigate microfungal communities in field-sampled and apparently healthy T. septentrionalis fungus gardens from across the Eastern USA (SI Appendix, Fig. S1 and Table S1). Reads classified as Trichoderma, a common genus of mycoparasites that also includes some saprophytes and plant mutualists (38), were both the most abundant and prevalent noncultivar reads in field-sampled T. septentrionalis fungus gardens, with a median relative abundance of 1.2% and a maximum of 68.6% in the most extreme case (Fig. 1A). Other noncultivar fungi in these fungus garden samples were only rarely abundant (Fig. 1A and SI Appendix, Fig. S2), and no reads in this dataset matched the common tropical fungus garden pathogen Escovopsis. Only four samples out of 83 were dominated by a noncultivar fungus; two of these were dominated by Meyerozyma, one by Trichoderma, and one by an unclassified member of the family Stephanosporaceae (Basidiomycota). Although the sampled fungus gardens did not visually appear to be diseased at the time of their collection, our ITS sequencing results suggest that Trichoderma spp. may be a low-level but constant threat to T. septentrionalis fungus gardens in situ.
Fig. 1.

In a parallel analysis, we also generated environmental metabolomes from 53 field-sampled T. septentrionalis fungus gardens, 18 of which were the same as those sampled for our ITS dataset. Using untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking (40), we identified chemical evidence for the presence of Trichoderma spp. in T. septentrionalis fungus gardens. After searching our network of specialized metabolites from these freshly collected fungus gardens (SI Appendix, Fig. S3) for metabolites produced by potential pathogens, we identified one cluster that contained a feature whose molecular weight and fragmentation pattern were consistent with the peptaibol trichodermide D (Fig. 1B and SI Appendix, Fig. S4) along with a suite of related peptaibols, most of which were originally isolated from Trichoderma virens CMB-TN16 (39). A related series of peptaibol features were detected in three fungus gardens collected from North Carolina, as shown by the nodes in the network that were closely related to known peptaibol features (Fig. 1B). Given that peptaibols are characteristic of mycoparasitic members of the Hypocreales and especially prevalent in Trichoderma (41, 42), our detection of peptaibols from these samples further supports that Trichoderma is present and metabolically active in field-sampled T. septentrionalis fungus gardens.
Trichoderma spp. Can Infect T. septentrionalis Fungus Gardens.
To experimentally test our hypothesis that some Trichoderma spp. can infect T. septentrionalis fungus gardens, we performed infections using lab-acclimated T. septentrionalis colonies. Three different Trichoderma strains (JKS001879, JKS001884, and JKS001921; most closely related to T. koningiopsis, T. virens, and T. simmonsii, respectively; SI Appendix, Table S2 and Fig. S5) were used for these infection experiments. These strains were all isolated from T. septentrionalis colonies that had naturally become diseased after the removal of ants in our laboratory. By 4 d post-treatment, all Trichoderma-treated fungus gardens without ants became visibly infected with these Trichoderma spp. (confirmed using full length ITS sequencing). However, those with ants and the mock-inoculated control fungus gardens (both with and without ants) remained uninfected (Fig. 2A and SI Appendix, Fig. S6). Ants weeded their fungus gardens in response to the application of all three Trichoderma strains (SI Appendix, Fig. S6), which presumably helped to maintain fungus garden health. In addition, peptaibols were produced by all three Trichoderma strains, as determined using untargeted metabolomics of the infected fungus gardens (SI Appendix, Fig. S7). These experiments demonstrate the ability of three different Trichoderma spp. to infect T. septentrionalis fungus gardens and further link Trichoderma infection with the presence of peptaibols.
Fig. 2.

We conducted an additional time-course experiment to further characterize Trichoderma infections of ant fungus gardens. By day 4 post-inoculation, Trichoderma sp. JKS001884 was visible in Trichoderma-treated fungus gardens in subcolonies that lacked ants, and in the waste piles created by the ants in the subcolonies that included them. All uninoculated negative controls lacked visible signs of disease throughout the time-course (e.g., based on hyphal growth morphologically consistent with Trichoderma; SI Appendix, Fig. S8). These visual observations were verified using community ITS2 gene sequencing (Fig. 2B), in which Trichoderma ITS reads were detected 2 and 4 d post-inoculation in the Trichoderma-treated fungus gardens in subcolonies that lacked ants, and in the waste generated by ants following Trichoderma treatments (waste was sampled only at day 4 post-treatment). All uninoculated fungus gardens (with and without ants) and Trichoderma-treated fungus gardens in subcolonies that included ants lacked Trichoderma ITS reads, except for one untreated fungus garden lacking ants that contained mostly Trichoderma reads by day 4 post-treatment, likely due to a bloom of Trichoderma that was naturally present in the subcolony and whose suppression was released by ant removal. Trichoderma may have persisted in this uninoculated fungus garden for several months despite ants being fed only sterile corn meal throughout that time, allowing Trichoderma to bloom in this replicate once ants were removed. Day 4 waste samples from uninoculated fungus gardens tended by ants also contained low abundances of noncultivar fungi (including Trichoderma) in control treatments. Molecular networking confirmed that peptaibol abundance was associated with the presence and abundance of Trichoderma during these infections (Fig. 2C and SI Appendix, Figs. S9 and S10), mainly in the waste produced by ants following Trichoderma treatment and in Trichoderma-treated fungus gardens lacking ants. Peptaibol abundance also increased over time following infection in these samples (Fig. 2C and SI Appendix, Fig. S11). These results confirmed the ability of Trichoderma spp. to infect T. septentrionalis fungus gardens and linked the presence of peptaibols with these Trichoderma spp.
Trichoderma Metabolites Promote Ant Weeding Behavior.
To identify the underlying mechanisms by which Trichoderma inoculation induced waste production by the ants, we exposed T. septentrionalis fungus gardens to extracts of Trichoderma sp. JKS001884. Colonies were tested multiple times, including both intracolony and intercolony replicates (SI Appendix, Table S4). In all tests, ant waste production was greater in extract-treated fungus gardens (mean weeded mass of 395 mg ± 40.9) compared to the negative controls treated only with DMSO (91.7 mg ± 19.4) or left untreated (41.9 mg ± 14.2; Fig. 3A and SI Appendix, Fig. S12). These results suggest that ant waste production was induced by metabolites from the Trichoderma extracts and that ant responses were not solely due to the physical presence of Trichoderma cells.
Fig. 3.

To identify the metabolites responsible for this bioactivity, we evaluated semi-purified fractions of our Trichoderma extract for their ability to induce ant behavioral responses. Fractions B, D, and E induced the greatest amount of ant waste production (255 mg ± 87.0, 241 mg ± 85.1, and 338 mg ± 97.1, respectively; Fig. 3B and SI Appendix, Fig. S13), although further analyses determined that fraction B was chemically dissimilar to fractions D and E (Fig. 3 C–F and SI Appendix, Figs. S15–S17) and was instead highly similar to fraction A (Fig. 3 C–F), one of the least bioactive fractions (Fig. 3B). Given that such early fractions often contain pan-assay interference compounds (43, 44), we prioritized fractions D and E for further analysis.
Comparative metabolomics was used to prioritize and identify metabolites that were highly abundant in fractions D and E. These fractions grouped together along non-metric multidimensional scaling (NMDS) axis 1, distinct from all other fractions (Fig. 3C), demonstrating their high chemical similarity, as also determined using Spearman’s correlation (Fig. 3E). Comparisons of total ion chromatograms (TICs; Fig. 3D and SI Appendix, Fig. S18) indicated considerable overlap of peaks in fractions D and E especially between 7 and 8 min, retention times at which numerous peptaibols elute. In addition, a large number of features that cooccurred in fractions D and E had molecular weights above 1,000 Da, consistent with peptaibol metabolites (Fig. 3F). This motivated further chemical analysis to identify features that may underpin the ant behaviors induced by fractions D and E.
Metabolomic and Statistical Analyses Reveal Peptaibols from Trichoderma Induce Ant Waste Production.
Based on our prioritization of fractions D and E (Fig. 3), we generated a heat map to identify features shared between fractions D and E and dereplicated these features using NP Atlas (45) (Fig. 4A, full heatmap in SI Appendix, Fig. S16). Fractions D and E exclusively shared 118 features (SI Appendix, Fig. S15), although an additional suite of features was highly enriched in fractions D and E but present in lower abundances in other fractions. Based on their molecular weights, retention times, and fragmentation patterns, many of these shared features were consistent with the structure of peptaibols. Three peptaibol-like features were exceptionally abundant in fractions D and E (Fig. 4C and SI Appendix, Table S8): [M + Na]+ peaks m/z 1197.7557 and 1183.7406, and [M + H]+ peak m/z 1452.8756. Together, the ion abundances of these three features represented a combined 35.5% and 75.5% of total metabolite abundance in fractions D and E, respectively. Further exploration of the accurate masses and fragmentation patterns of these features confirmed that all three likely represent peptaibols, two of which have masses consistent with the peptaibols trichodermides B/C and D/E, although several other peptaibols have similar masses.
Fig. 4.

These results prompted further ant weeding assays using a small library of purified peptaibols (SI Appendix, Fig. S19) to determine if specific, individual peptaibols induce ant behavior and if this behavior is a result of collective and/or nonspecific peptaibol metabolites. We tested six peptaibols isolated from Trichoderma arundinaceum and one purchased peptaibol to evaluate their ability to induce ant waste production. Although these purified peptaibols varied in their bioactivity, all induced ant waste production, with some replicates having higher levels of bioactivity than the extract (SI Appendix, Fig. S14). Two of these peptaibol metabolites, 1 and 2 (Fig. 4B), are previously undescribed compounds given the trivial names trichokindins VIII and IX, respectively. Mass spectrometric analysis confirmed that both metabolites were present in our Trichoderma extract and in the bioactive fractions D and E (SI Appendix, Figs. S20 and S21). Full characterization of 1 and 2 (SI Appendix, Figs. S22–S40) indicated that these previously undescribed compounds have a classical peptaibol structure, being composed entirely of amino acids, including characteristic α-aminoisobutyric acid (Aib) moieties. Because each isolated peptaibol induced ant weeding, this behavior is likely characteristic of the peptaibol class, in general, and may not be specific to individual peptaibols.
Our results strongly suggest that ant waste production is induced by Trichoderma-derived peptaibol metabolites; however, we cannot discount that other fungal secondary metabolites were present in our Trichoderma extracts (e.g., in fraction B) that may also induce waste production. Using comparative metabolomics, we identified a feature suggestive of the fungal metabolite roselipin 1A (46), although this feature had similar abundances across fractions D, E, and F. Because fraction F did not induce substantial ant waste production, this feature did not likely cause the observed ant weeding behavior. Features with masses matching two other common fungal metabolites, gliovirin (47) and heptelidic acid (48, 49), exhibited similar patterns of abundance in both inactive and bioactive fractions, and thus were also unlikely to induce the observed ant weeding behavior. Thus, the unique correlation between peptaibol-enriched fractions and increased ant waste production underscores the relationship between Trichoderma-derived peptaibols and ant waste production.
Discussion
Our data show that Trichoderma spp. are common in wild T. septentrionalis fungus gardens sampled from across a broad geographic range (Fig. 1A), which suggests that at least some Trichoderma spp. may naturally cause fungus garden disease. Supporting this hypothesis, our isolation of Trichoderma spp. from diseased gardens, experimental infection of healthy gardens, and detection of Trichoderma during experimental infections using ITS2 amplicon sequencing all provide experimental evidence that Trichoderma spp. can be opportunistic pathogens of T. septentrionalis fungus gardens (Fig. 2 A and B) and fully satisfy the experimental aspects of Koch’s postulates for disease causality, which include the isolation of a pathogen from a diseased host, experimental infection of a naive host using that isolate, and reisolation of that disease-causing isolate (50–52). The ecological aspects of Koch’s postulates (detection of the pathogen in diseased but not healthy hosts) are partially fulfilled in this study by our detection of Trichoderma in environmental fungus gardens, even though these were not visually diseased at the time of collection, a difficult to detect event due to acute disease leading to rapid colony collapse and our detecting colonies to collect based on the presence of active ants, likely indicative of colony health. We also note that fungus garden diseases can be present but not visually apparent (e.g., on day 2 of our infection experiments; Fig. 2), making it challenging to definitively link Trichoderma presence to disease in the field, and that a focus on pathogen presence/absence without consideration of pathogen load, microbiome composition, or environmental conditions is a noted weakness of Koch’s postulates (50, 53, 54). Although the species identity, ecological source, and relationship to disease of the low levels of Trichoderma present in T. septentrionalis fungus gardens remains unclear, our results indicate the consistent presence of these potential disease-causing agents that could at least in some cases necessitate defensive responses by the ants. Together, our ecological and experimental data support our conclusion that, at least under some conditions, Trichoderma spp. can infect T. septentrionalis fungus gardens.
Metabolomics analyses of lab-reared fungus gardens inoculated with T. septentrionalis-isolated Trichoderma spp. revealed the presence of peptaibols in infected gardens (Fig. 2C and SI Appendix, Figs. S7, S9–S11). Wild fungus gardens contained similar peptaibols, indicating their ecological relevance, consistent with peptaibol-producing Trichoderma being an opportunistic pathogen of T. septentrionalis fungus gardens (Fig. 1B). In our laboratory experiments, two of the Trichoderma fractions with the highest abundance of peptaibols, fractions D and E, induced some of the strongest T. septentrionalis weeding responses (Fig. 3), and purified peptaibols also induced a weeding response similar to that of the Trichoderma extract (SI Appendix, Fig. S14). Given that the Trichoderma fractions and purified peptaibols were derived from different strains and represent a diversity in peptaibol composition, the similarities in the observed ant behavioral activity are thus likely to be unrelated to specific peptaibols but rather generally attributable to the peptaibol class of metabolites. Furthermore, the presence of peptaibols in environmental fungus gardens lends credence to their ecological relevance and together with the experimental data parallels the logic of Koch’s postulates, suggesting that peptaibols are likely produced during Trichoderma infections of ant fungus gardens and induce ant defensive behaviors in response.
Peptaibols are produced by fungi in the order Hypocreales, especially by members of the mycoparasitic family Hypocreaceae, which contains both Trichoderma and Escovopsis, a specialized ant fungus garden pathogen (41, 42). Peptaibols have been hypothesized to be important for mycoparasitism (55, 56), which we show here can include infections of ant fungus gardens. Interestingly, the genes needed to synthesize peptaibols are encoded within the genome of Escovopsis (57), and Escovopsis has been shown to induce a strong ant weeding response in tropical leaf-cutting fungus-growing ants (17), similar to the T. septentrionalis weeding behaviors that we observed in response to Trichoderma and its peptaibols. We therefore hypothesize that peptaibol-induced weeding behaviors are conserved among diverse fungus-growing ants and may reflect an ancient means of pathogen detection and defense. Future work should test if ant weeding intensity is directly correlated with pathogen load, virulence, peptaibol production, or other contributing environmental factors, and also compare the behavioral responses of diverse fungus-growing ant species to diverse fungal pathogens with varying levels of virulence and specialization toward ant fungus gardens, e.g., as in ref. 58.
This study demonstrates how T. septentrionalis ants protect their cultivar mutualist from opportunistic Trichoderma pathogens by sensing and responding to peptaibols as specific molecular cues that induce an ant weeding response. These cues included two previously undescribed bioactive peptaibol metabolites that we identified in this study. Future research will investigate whether ants directly sense peptaibols or indirectly respond to an intermediate signal produced by the cultivar in response to peptaibols, in addition to characterizing other potential signaling molecules that are unlikely to be present in our Trichoderma extracts (e.g., volatile compounds). In contrast to the canonical logic of host immune responses, in which hosts directly respond to infections, T. septentrionalis responses to peptaibol signaling molecules comprise an extended defense response whereby T. septentrionalis ants respond to infections of their cultivar mutualist. Such extended defense responses may be a widespread but poorly recognized mechanism that increases host health indirectly by preventing harm to their beneficial symbionts.
Materials and Methods
Colony Collections.
Colonies of T. septentrionalis were collected during the summers of 2014 to 2017 from state parks and forests throughout the eastern USA (SI Appendix, Table S1) and transferred to the Klassen laboratory as described elsewhere (59, 60). Fungus garden samples were frozen directly in the field in either dimethyl sulfoxide-ethylenediamine tetraacetic acid-saturated salt solution (DESS) (59) for mycobiome sequencing (dataset “Environmental ITS2”; SI Appendix, Table S1) or without added preservative for metabolomic analysis (dataset “Environmental LC-MS/MS”; SI Appendix, Table S1). Due to the prospective nature of these collections, only a subset of colonies was used for both analyses. Three additional colonies were collected from New Jersey during the summer of 2014 and used to isolate the Trichoderma strains used in this study (dataset “Trichoderma isolations”; SI Appendix, Table S1). Two more colonies were collected during the summer of 2018 from New Jersey and used for laboratory infection experiments (dataset “Trichoderma/Time-course infection”; SI Appendix, Table S1). Colonies were collected from North Carolina in 2019 for preliminary chemical extract experiments (dataset “2019 extract tests”; SI Appendix, Table S1). Further chemical extract testing was performed with additional colonies collected from New Jersey in 2020 (dataset “2020 extract tests”; SI Appendix, Table S1). All collections were performed under appropriate permits (SI Appendix).
Trichoderma Isolations.
Fungal pathogen strains JKS001879, JKS001884, and JKS001921 (SI Appendix, Table S2) were isolated from pieces of recently collected fungus gardens with their ants removed. Noncultivar fungi that overgrew these unprotected fungus gardens were collected using tweezers and plated on Potato Dextrose Agar (PDA, Difco) + antibiotics (ABX, 50 mg/L penicillin and 50 mg/L streptomycin; both Fisher Scientific) and grown at 25 °C. Fresh hyphal growth from the edge of each colony was subcultured several times to obtain morphologically and microscopically pure cultures. These strains were then identified by Sanger sequencing of several marker genes including the full ITS region, translation elongation factor 1-α (TEF1), and the RNA polymerase II subunit RPB2. DNA was extracted (see below) and PCR amplified using primers ITS1/ITS4, EF1/EF2, or fRPB2-5f/fRPB2-7cr (SI Appendix, Table S3). The ITS region was amplified using thermocycling conditions: 3 min at 95 °C, 30 cycles of 30 s at 95 °C, 45 s at 50 °C, and 45 s at 72 °C, with a final extension for 2 min at 72 °C (modified from ref. 61). The TEF gene was amplified following (62). The RPB2 gene was amplified using thermocycling conditions: 3 min at 95 °C, 15 cycles of 45 s at 95 °C, 1 min at 60 °C and decreasing by 0.5 °C each cycle, and 1 min at 72 °C, followed by 30 cycles of 95 °C for 45 s, 54 °C for 1 min, and 72 °C for 1 min, with a final extension at 72 °C for 5 min [modified from refs. (62, 63)]. Amplified products were purified using Agencourt AMPure XP beads (Beckman Coulter) following the manufacturer’s instructions for PCR purification. Purified PCR products were then sequenced at Eurofins Genomics (Louisville, KY), and resulting data were analyzed using Geneious Prime v. 2019.1.3 to generate consensus sequences that were then processed with MIST (64) (http://mmit.china-cctc.org/index.php accessed: February 22, 2022) in the order ITS, TEF1, and then RPB2. This protocol was also used to sequence the full ITS genes of the pathogens that bloomed in the Trichoderma infection experiment (described below) to confirm that each matched the inoculated strain.
Trichoderma Assays.
Spore isolation.
Trichoderma strains JKS001879, JKS001884, and JKS001921 were grown on PDA+ABX plates at 25 °C for ~1 wk until green colored growth covered the plate, indicating sporulation. Spores were isolated by flooding each plate with up to 5 mL PBS and gently agitating with a sterile loop to suspend the spores. Avoiding the remaining hyphae, suspensions were collected from each plate and diluted with PBS until a phase separation between the heavy particulates and floating hyphae could be visualized after vortexing. The center phase, enriched with spores, was collected and visualized using 1,000x oil immersion light microscopy to verify the presence of spores and general absence of hyphae. Spore concentrations were measured using the optical density at 600 nm (OD600), and spore suspensions were diluted to OD600 0.2 and stored at 4 °C.
Trichoderma infection.
Subcolonies of T. septentrionalis colony JKH000285 were created using small portions of fungus garden (~20 cm3) in small (7.5 × 7.5 × 3 cm) plaster-lined plastic boxes, manipulating each garden as little as possible. Spore suspensions were warmed to room temperature and 500 μL of either Trichoderma sp. JKS001879, JKS001884, or JKS001921 spore suspension or PBS as a negative control were dripped onto fungus gardens, either with or without eight worker ants present, mirroring previous work that describes other fungus garden pathogens (6, 16). Although treatments lacking ants represent an extreme perturbation that is unlikely to occur naturally, they provide a unique experimental means to differentiate the relative contributions of ants and fungus gardens to colony defense. Pictures were taken at 0, 1, 3, and 4 d post-treatment (SI Appendix, Fig. S6, Data, Materials, and Software Availability). Fungus garden samples were frozen at −80 °C in DESS or without buffer for DNA sequencing and metabolomic analysis, respectively, 17 d post-treatment.
Time-course infection.
Trichoderma sp. JKS001884 was chosen for further investigation because it grew the fastest and produced the most spores in the initial infection experiment. Subcolonies of T. septentrionalis colony JKH000292 were created as described above, and treated with Trichoderma sp. JKS001884 (500 µL of spores suspended in 1X PBS, OD600 0.2) or 500 µL PBS alongside no-treatment controls, both with and without 12 worker ants present and with parallel replicates. Treatments were applied by spraying each fungus garden from ~2” above using an atomizer (Teleflex MAD300). Four ants and ~1/3 of the fungus garden were frozen at −80 °C in DESS or without buffer dry for DNA and metabolomic analysis, respectively, at each time point (days 0, 2, and 4). Waste from +ants subcolonies was also sampled at day 4 post-treatment. Pictures were taken at each sampling time point (SI Appendix, Fig. S8, Data, Materials, and Software Availability).
Trichoderma extract experiments.
Ant weeding behavioral responses to Trichoderma extracts (extraction procedures described below) were assessed qualitatively in 2019 (August 2 to September 30) using video analysis of ant subcolonies created as described above from three different T. septentrionalis colonies and with 10 worker ants each. Weeding severity was determined by visually comparing the amount of waste removed from subcolony fungus gardens and discarded around the edges of the box, and thus the extent of fungus garden disturbance in response to treatment. Treatment with Trichoderma crude extract (10 mg/mL) induced more weeding compared to DMSO and NT controls (Movie S1). During the 2020 season (July 16 to September 24) waste generated by ant weeding was quantified by weighing the mass of waste produced by ants in response to various Trichoderma extract/compound treatments. Subcolonies were created as described above using 10 worker ants per subcolony, except side chambers were omitted due to the short duration of each experiment and Plaster of Paris (50 g) was poured into each box 8 to 48 h before each experiment to minimize variation in humidity. Immediately prior to each experiment, the plaster was saturated with deionized water to create controlled, high humidity conditions for each box. Each box was weighed before and after adding fungus gardens to calculate fungus garden mass. Two hundred microliters of each crude extract (10 mg/mL), fraction (1 mg/mL), pure compound (0.25 mg/mL), or solvent-only control (SI Appendix, Table S4) was dripped onto the fungus garden surface. Fractions and pure compounds were diluted to approximate their concentrations in extracts of pure Trichoderma cultures. A still image of each treated fungus garden was taken before adding ants, ants were added, and then timelapse photos were taken every 5 s for 24 h to document ant behaviors. After 24 h, ants were removed and a still image was taken before and after the waste created by the ants was collected into preweighed 2 mL tubes. Tubes were capped to prevent dehydration and then weighed again to calculate the total waste mass. Timelapse photography for each experiment was converted into movies using FFMPEG (http://ffmpeg.org) with the command:
ffmpeg -r 30 -f image2 -pattern_type glob -i ‘*.JPG’ -s 4000x3000 -c:v mjpeg -q:v 10. /output_timelapse.ffmpeg.30fps.q10.mov
Movie S1.
Preliminary Trichoderma extract bioassay performed Aug. 2, 2019. This experiment tested crude Trichoderma extract (MB0895 10mg/mL in 1% DMSO) and negative controls (1% DMSO and NT) in three replicates on subcolonies of JKH000365, JKH000377, and JKH000380. Ten ants were included in each box. This experiment was video recorded for 8.5 h (as much as the SD card could record) and then sped to 500x the original speed. Side waste/food boxes were connected to the main fungus garden boxes for this experiment that contained sterile cornmeal in a plastic weigh boat. The boxes in the video from left to right and top to bottom are: JKH365-MB0895 waste/food, JKH377-MB0895 waste/food, JKH380-MB0895 waste/food, JKH380-NT fungus garden, JKH380-NT waste/food, JKH365-MB0895 fungus garden, JKH377-MB0895 fungus garden, JKH380-MB0895 fungus garden, JKH377-NT fungus garden, JKH377-NT waste/food, JKH365-DMSO fungus garden, JKH377-DMSO fungus garden, JKH380-DMSO fungus garden, JKH360-NT fungus garden, JKH360-NT waste/food, JKH365-DMSO waste/food, JKH377-DMSO waste/food, JKH380-waste/food.
Surprisingly, our initial experiments conducted early in the 2020 season did not recapitulate the previous induction of ant weeding behavior in response to crude Trichoderma extracts seen in 2019. As the season progressed (late August through September), colonies began responding to the treatments, and thus only experiments where the Trichoderma extract weeding response exceeded that of the negative controls were included in the final dataset (trials 9 to 16, and the replicate using colony JKH000396 in trial 17; SI Appendix, Table S4). We suspect this variability in response is due to seasonal and intercolony variability in T. septentrionalis activity, although further testing is necessary to confirm this. Ant weeding was then compared between treatments by averaging waste production per treatment across colony replicates.
DNA Extraction and Sequencing.
DNA extraction.
DNA was extracted from approximately 0.05 g of fungus garden stored in DESS or fresh hyphae from Trichoderma culture plates as described in ref. 59, except that the fungus garden samples used to generate the environmental ITS2 dataset were first washed thrice with sterile 1X PBS to remove PCR inhibitors, and DNA was precipitated for 1 h at room temperature. All other samples were extracted using a modification of ref. 59 wherein the extraction volume was halved (to 250 µL), 80% ice cold ethanol was used to wash DNA pellets, DNA pellets were air dried on a 37 °C heat block, DNA was incubated and gently agitated in 100 µL nuclease-free water for ≥1 h at 37 °C to resuspend the DNA pellet and then quantified using the Qubit dsDNA high-sensitivity assay protocol and a Qubit 3.0 fluorimeter (Invitrogen). Samples in the environmental ITS2 dataset were cleaned by excising 25 to 30 μL of each PCR product from 1% agarose gels using a sterile scalpel and the QIAGEN QIAquick Gel Extraction Kit following the manufacturer’s instructions.
Fungal ITS2 community amplicon sequencing.
Before fungal community sequencing, DNA samples were first prescreened for amplification using primers fITS7 and ITS4 targeting the ITS2 region of the fungal rRNA gene (SI Appendix, Table S3). Then, 3 μL (6 ng on average) of template DNA was added to 5 μL 5× GoTaq Green Reaction Mix Buffer (Promega), 0.625 units of GoTaq DNA Polymerase (Promega), 0.2 mM each dNTP, 0.15 μM of each primer, 0.464 μg/μL bovine serum albumin (BSA, New England BioLabs Inc.), and 1.5 mM MgCl2, to which nuclease-free water was added to a volume of 25 μL. Thermocycling conditions were 3 min at 95 °C, 30 cycles of 30 s at 95 °C, 45 s at 50 °C, and 45 s at 72 °C, followed by a 2-min final extension at 72 °C. Gel electrophoresis was used to confirm the expected band size of 300 to 500 bp. DNA extracts that failed to amplify were diluted 10-fold and rescreened, continuing to a maximum dilution factor of 1:50.
DNA extracts that successfully amplified during prescreening and their corresponding negative control extracts were prepared for ITS2 community amplicon sequencing. Then, 6 μL (12 ng on average) of DNA from each extract was added to 10 μmol of each Illumina-barcoded version of fITS7 and ITS4 primers, 5 μL of 10x AccuPrime buffer (Invitrogen), 0.4 mM MgSO4, 0.16 μg/μL BSA (New England BioLabs Inc.), 50 μM each dNTP, 0.2 μM of nonbarcoded primers fITS7 and ITS4, and 1.25 units of AccuPrime polymerase. Nuclease-free water was added to reach a final volume of 50 μL per reaction. A PCR negative control using 6 μL nuclease-free water as template was included for each 96-well plate processed. This PCR master mix was split into triplicates (16.7 μL each reaction) using an epMotion 5075 liquid handling robot (Eppendorf). Thermocycler conditions were 2 min at 95 °C, 30 cycles of 95 °C for 15 s, 55 °C for 1 min, and 68 °C for 1 min, followed by final extension at 68 °C for 5 min before an indefinite hold at 4 °C. Triplicate PCRs were then repooled using the epMotion 5075, and DNA concentrations were quantified using a QIAxcel Advanced capillary electrophoresis system (QIAgen). An equal mass of DNA (up to a maximum volume of 12 μL) was pooled into a single library, which was cleaned using Mag-Bind RXNPure plus beads (OMEGA) in a 1:0.8 ratio of sequencing library to bead volume. Cleaned libraries were adjusted to 1.1 ng/μL ± 0.1 ng/μL using a Qubit dsDNA high-sensitivity assay and Qubit 3.0 fluorometer. Sequencing was performed using Illumina Miseq V2 2 × 250 bp reads.
ITS2 Community Amplicon Sequence Analysis.
For the Environmental ITS2 dataset, (NCBI accession: PRJNA763335, SI Appendix, Dataset S1) forward reads from 90 samples were processed using Trimmomatic v0.39 (65) with options SLIDINGWINDOW 5:20 and MINLEN:125 and then processed in R v.3.6.3 using the DADA2 v1.16.0 (66) ITS workflow (https://benjjneb.github.io/dada2/ITS_workflow.html, accessed May 26, 2021) except using only forward reads. All negative controls produced 0 reads, so decontamination methods were not necessary for this dataset. Following DADA2, amplicon sequence variants (ASVs) were inputted into ITSx v1.1.3 (67) to extract the ITS2 region. ASVs without an ITSx-detected ITS2 region were filtered (n = 6), and ASVs with identical ITS2 regions (n = 41) were merged using the Phyloseq v1.26.1 (68) merge_taxa() command. Remaining ASVs were then taxonomically classified using the UNITE database (69) general FASTA release for Fungi 2 v.8.2 (https://doi.org/10.15156/BIO/786369). Read sets were rarefied to 12,531 reads, which removed 7 samples and 211 ASVs. ASVs not classified at the phylum level (n = 20) were removed using Phyloseq’s subset_taxa() command and ASVs that were not present at ≥1% abundance in at least one sample (n = 381) were assigned as “Other” using the metagMisc v.0.04 (https://github.com/vmikk/metagMisc) command phyloseq_filter_sample_wise_abund_trim(). The remaining 35 ASVs were assigned to 10 taxa: “Cultivar fungus,” Meyerozyma, Trichoderma, unclassified Stephanosporaceae, Lecanicillium, Penicillium, Oberwinklerozyma, Cladosporium, Xylaria, and Scleroderma. Cultivar fungus was manually defined as all taxa classified as genus Leucocoprinus, Leucoagaricus, or unclassified Agaricaceae confirmed as being best BLAST (70) matches to a higher attine cultivar fungus. For all ITS2 community analyses, ASVs were not classified past rank genus because the ITS2 region is too short to delineate species for many fungi, including Trichoderma.
For the time-course infection dataset (NCBI accession: PRJNA743045, SI Appendix, Dataset S2), sequencing resulted in 46 ITS2 community amplicon readsets including four negative controls. The number of reads per sample ranged from 6 to 23,953. These data were analyzed in the same way as the environmental ITS dataset except that after ITSx treatment and taxonomy assignment, the prevalence protocol for decontam v1.12.0 (71) was used with a default threshold of 0.1 to determine if any ASVs were contaminant sequences. No contaminants were detected so negative controls were removed from further processing. This dataset was rarefied to 4,099 reads, which removed three ASVs and two samples. Two ASVs were removed that were unclassified past the Kingdom level, which left 31 unique ASVs. ASVs were then filtered to remove very rare taxa (ASVs present at <1% abundance across all samples). This resulted in 14 unique ASVs that belonged to five taxa: Cultivar fungus, Trichoderma, Candida, Vanrija, and Penicillium.
Extraction and Fractionation of Trichoderma Strain JKS001884.
All solvents were of high performance liquid chromatography (HPLC) grade and purchased from Sigma Aldrich. Agar plates were cut into small pieces and extracted with 2:1 ethyl acetate:methanol (EtOAC:MeOH) three times and sonicated for 60 s. Solvent was collected after each extraction, filtered under vacuum, and dried using rotary evaporation.
Fractionation of Trichoderma strain JKS001884 was performed twice. Initial fractionation of a portion of MB1081 (1.48 g) began by dissolving it in a minimum amount of 50% aqueous MeOH, which was then loaded onto a Discovery® DSC-18 SPE cartridge (10 g/50 mL). The column was conditioned and equilibrated with 150 mL portions of water, MeOH, and 10% aqueous MeOH prior to sample addition. Using a stepwise gradient, the sample was eluted under negative pressure using (A) 10% aqueous MeOH, (B) 25% aqueous MeOH, (C) 50% aqueous MeOH, (D) 75% aqueous MeOH, and 100% MeOH (E) that were eluted using 150, 150, 250, 300, and 300 mL portions, respectively, followed by a 100% acetonitrile (ACN) fraction (F), an organic wash with dichloromethane (DCM)/acetone/MeOH (G), and a final aqueous wash (H). The eight fractions (MB1081A-H) were dried under reduced pressure. For the second fractionation, crude extract MB1084 (413.0 mg) was dissolved in a minimum amount of 50% aqueous MeOH and then loaded onto a Discovery® DSC-18 SPE cartridge (10 g/50 mL). Column conditions and fractionation were as described above for fractions A–E, except the sample was eluted with 135 mL of each solvent and no 100% ACN fraction was collected. An organic wash of 1:1:1:1 EtOAc:DCM:acetone:MeOH was collected (MB1084F), along with a final aqueous wash (MB1084G). The seven fractions (MB1084A-G) were dried under reduced pressure. All fractions were then evaluated using LC-MS/MS and in ant behavior assays.
Molecular Networking of Fungus Garden Samples.
Fungus garden samples from both field-collected and lab-acclimated gardens were extracted with 2:1 DCM:MeOH three times. Samples were sonicated, manually macerated with a metal spatula, and incubated in solvent for 15 min at room temperature, after which solvent was filtered, combined, and dried under nitrogen (see ref. 72 for details). Following LC-MS/MS data acquisition, molecular networking and feature-based molecular networking were performed (SI Appendix).
Metabolomics and Statistical Analyses of Trichoderma Extracts and Fractions.
Untargeted MS data acquisition.
MS data were acquired using a Waters Synapt G2-Si coupled to an Acquity UPLC system with an Acquity UPLC HSS T3 VanGuard precolumn (2.1 × 5 mm, 1.8 μM) and an Acquity UPLC HSS T3 column (2.1 × 150 mm, 1.8 μM) with a flow rate of 0.45 mL/min. Samples were prepared in a 1:1 mixture of MeOH/water and injected three times for technical replication, using a gradient elution with mobile phases A (water with 0.1% formic acid) and B (ACN with 0.1% formic acid) using the following conditions: 0.5 min hold at 95% A and 5% B, 3.5 min ramp to 60% B, 4 min ramp to 100% B, 1 min hold at 100% B, 0.2 min ramp back to 5% B and a reequilibration hold at 5% B for 1.8 min. Spectrometric data were acquired using MSE data-independent acquisition (DIA) with continuous MS survey scanning ranging from m/z 50 to 2,000 in positive-resolution mode. Data were acquired using the following parameters: 2 kV capillary voltage, 100 °C source temperature, 20 V sampling cone, 2 V collision energy, 800 L/h desolvation gas flow, and 80 V source offset. Real-time mass correction used a lockspray of 400 pg/μL leucine enkephalin solution (1:1 MeOH:water solution with 0.1% formic acid).
MS data preprocessing.
MS data were processed using Progenesis QI (Nonlinear Dynamics, Milford, MA) to create a peak list for statistical analyses. An injection of the crude extract was selected as the alignment reference since all fractions share features with the crude extract. Peak picking parameters included fragment sensitivity of 0.2% of the base peak and adducts included M+H, M+2H, 2M+2H, 3M+3H, and M+Na. Export included compound ID, m/z, retention time, and raw abundance.
Metabolomics data processing, filtering, and statistical analyses.
The peak list and fragment database were exported from Progenesis and analyzed with MPACT (73). Data were filtered using solvent blank, mispicked peak, reproducibility, and in-source fragment filters (SI Appendix, Fig. S41). Blank filtering using MeOH blanks was applied based on a relative group parsing threshold of 0.05. A minimum reproducibility threshold of 0.5 median coefficient of variation among technical replicates was applied. The presence or absence of features in a group of samples was determined using a relative abundance threshold of 0.05 compared to the sample group in which a feature was most abundant. This threshold was applied during blank filtering to remove features whose abundance in solvent blanks was greater than 5% of their abundance in experimental samples. A 0.95 Spearman correlation threshold was used for identifying and removing in-source ion clusters. A correction for mispicked peaks was applied with a ringing mass window of 0.5 atomic mass unit (AMU), isotope mass window of 0.01 AMU, retention time window of 0.005 min, and a maximum isotopic mass shift of 4 AMU.
Analysis of peptaibol abundance.
The Progenesis peak list was used to determine the percent abundance of each feature relative to the total ion abundance for each fraction (Fig. 4C). The percent abundance of each feature was obtained by averaging across technical replicates and then dividing by the average total ion abundance for each fraction, with heat map coloration ranging from 0 to 50%, established based on the most abundant feature with m/z 1,197.7557, which constituted 47% of fraction E.
Isolation and Characterization of Trichokindins VIII (1) and IX (2).
Two strains of Trichoderma, including T. arundinaceum (MSX 70741) and T. albolutescens (MSX 57715), were fermented, extracted, and fractionated to obtain pure compounds used in this study, including the previously undescribed compounds, trichokindins VIII (1) and IX (2) (SI Appendix).
Data, Materials, and Software Availability
Sanger sequencing data generated in this study to identify Trichoderma isolates can be accessed from the National Center for Biotechnology Information (NCBI) GenBank (https://www.ncbi.nlm.nih.gov/genbank/) using accession numbers OM967104–OM967106 (ITS) (74–76), ON113306–ON113308 (RPB2) (77–79), and ON364341–ON364343 (TEF1) (80–82). Fungal community sequencing data were deposited in NCBI under BioProject PRJNA763335 (83) and PRJNA743045 (84) for the wild fungus gardens and laboratory Trichoderma infections, respectively. Metabolomic data sets used in this work were deposited in the Mass Spectrometry Interactive Virtual Environment repository MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) under accession numbers MSV000082295 (environmental LC-MS/MS) (85), MSV000088621 (Trichoderma infection) (86), and MSV000083723 (time-course JKS001884 infection) (87). All image and video data from Trichoderma infections and extract behavioral bioassays can be found at https://doi.org/10.7910/DVN/MAYHMQ (88). Code and additional metadata files used for ITS2 amplicon sequencing analysis and extract tests weeding quantification are available at https://github.com/kek12e/ms_peptaibol (89).
Acknowledgments
Funding for this work was received from NSF grants IOS-1656475 (to J.L.K. and M.J.B.) and IOS-1656481 (to P.C.D.). A.M.C.-R. and P.C.D. were supported by the Gordon and Betty Moore Foundation through grant GBMF7622, the U.S. NIH for the Center (P41 GM103484 and R01 GM107550) and Federal subaward DE-SC0021340. The isolation of peptaibols from strains MSX70741 and MSX57715 was funded, in part, by the National Cancer Institute under grant P01 CA125066 (to N.H.O.). J.J.J.v.d.H. is grateful for funding from the Netherlands eScience Center with an Accelerating Scientific Discoveries Grant (ASDI.2017.030). We thank Drs. Jeremy Balsbaugh and Jennifer Liddle from the UConn Proteomics and Metabolomics Facility for assistance in acquiring LC-MS/MS data, Dr. Kendra Maas from the UConn Microbial Analysis, Resources and Services facility for assistance with amplicon library preparation and sequencing, and Dr. Kim Diver for creating the map of ant colony collection sites. Further thanks are due to Evan Fox and Mariam Zedan for assistance with extractions and to members of the Klassen lab and state park and forest staff for assistance with fieldwork.
Author Contributions
K.E.K., S.P.P., A.M.C.-R., P.C.D., J.L.K., and M.J.B. designed research; K.E.K., S.P.P., A.M.C.-R., J.R.-C., C.E.E., H.A.R., and M.E.A. performed research; K.E.K., S.P.P., A.M.C.-R., J.R.-C., R.M.S., C.E.E., H.A.R., C.J.P., M.E., J.J.J.v.d.H., N.H.O., P.C.D., J.L.K., and M.J.B. analyzed data; K.E.K., S.P.P., A.M.C.-R., J.R.-C., J.L.K., and M.J.B. wrote the paper; and all authors edited the paper.
Competing interests
K.E.K., S.P.P., A.M.C.-R., J.R.-C., R.M.S., C.E.E., M.E., M.E.A., J.L.K., and M.J.B. declare no competing interest. N.H.O., C.J.P., and H.A.R. are members of the Scientific Advisory Board of Clue Genetics, Inc. N.H.O. is also a member of the Scientific Advisory Board of Mycosynthetix, Inc. J.J.J.v.d.H. is a member of the Scientific Advisory Board of NAICONS Srl. P.C.D. is a scientific co-founder and advisor to Ometa and Enveda with prior approval by UC-San Diego and an advisor to Cybele.
Supporting Information
Appendix 01 (PDF)
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Dataset S01 (XLSX)
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Dataset S02 (XLSX)
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Movie S1.
Preliminary Trichoderma extract bioassay performed Aug. 2, 2019. This experiment tested crude Trichoderma extract (MB0895 10mg/mL in 1% DMSO) and negative controls (1% DMSO and NT) in three replicates on subcolonies of JKH000365, JKH000377, and JKH000380. Ten ants were included in each box. This experiment was video recorded for 8.5 h (as much as the SD card could record) and then sped to 500x the original speed. Side waste/food boxes were connected to the main fungus garden boxes for this experiment that contained sterile cornmeal in a plastic weigh boat. The boxes in the video from left to right and top to bottom are: JKH365-MB0895 waste/food, JKH377-MB0895 waste/food, JKH380-MB0895 waste/food, JKH380-NT fungus garden, JKH380-NT waste/food, JKH365-MB0895 fungus garden, JKH377-MB0895 fungus garden, JKH380-MB0895 fungus garden, JKH377-NT fungus garden, JKH377-NT waste/food, JKH365-DMSO fungus garden, JKH377-DMSO fungus garden, JKH380-DMSO fungus garden, JKH360-NT fungus garden, JKH360-NT waste/food, JKH365-DMSO waste/food, JKH377-DMSO waste/food, JKH380-waste/food.
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Copyright © 2023 the Author(s). Published by PNAS. This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Data, Materials, and Software Availability
Sanger sequencing data generated in this study to identify Trichoderma isolates can be accessed from the National Center for Biotechnology Information (NCBI) GenBank (https://www.ncbi.nlm.nih.gov/genbank/) using accession numbers OM967104–OM967106 (ITS) (74–76), ON113306–ON113308 (RPB2) (77–79), and ON364341–ON364343 (TEF1) (80–82). Fungal community sequencing data were deposited in NCBI under BioProject PRJNA763335 (83) and PRJNA743045 (84) for the wild fungus gardens and laboratory Trichoderma infections, respectively. Metabolomic data sets used in this work were deposited in the Mass Spectrometry Interactive Virtual Environment repository MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) under accession numbers MSV000082295 (environmental LC-MS/MS) (85), MSV000088621 (Trichoderma infection) (86), and MSV000083723 (time-course JKS001884 infection) (87). All image and video data from Trichoderma infections and extract behavioral bioassays can be found at https://doi.org/10.7910/DVN/MAYHMQ (88). Code and additional metadata files used for ITS2 amplicon sequencing analysis and extract tests weeding quantification are available at https://github.com/kek12e/ms_peptaibol (89).
Submission history
Received: November 15, 2022
Accepted: May 4, 2023
Published online: June 15, 2023
Published in issue: June 20, 2023
Keywords
Acknowledgments
Funding for this work was received from NSF grants IOS-1656475 (to J.L.K. and M.J.B.) and IOS-1656481 (to P.C.D.). A.M.C.-R. and P.C.D. were supported by the Gordon and Betty Moore Foundation through grant GBMF7622, the U.S. NIH for the Center (P41 GM103484 and R01 GM107550) and Federal subaward DE-SC0021340. The isolation of peptaibols from strains MSX70741 and MSX57715 was funded, in part, by the National Cancer Institute under grant P01 CA125066 (to N.H.O.). J.J.J.v.d.H. is grateful for funding from the Netherlands eScience Center with an Accelerating Scientific Discoveries Grant (ASDI.2017.030). We thank Drs. Jeremy Balsbaugh and Jennifer Liddle from the UConn Proteomics and Metabolomics Facility for assistance in acquiring LC-MS/MS data, Dr. Kendra Maas from the UConn Microbial Analysis, Resources and Services facility for assistance with amplicon library preparation and sequencing, and Dr. Kim Diver for creating the map of ant colony collection sites. Further thanks are due to Evan Fox and Mariam Zedan for assistance with extractions and to members of the Klassen lab and state park and forest staff for assistance with fieldwork.
Author Contributions
K.E.K., S.P.P., A.M.C.-R., P.C.D., J.L.K., and M.J.B. designed research; K.E.K., S.P.P., A.M.C.-R., J.R.-C., C.E.E., H.A.R., and M.E.A. performed research; K.E.K., S.P.P., A.M.C.-R., J.R.-C., R.M.S., C.E.E., H.A.R., C.J.P., M.E., J.J.J.v.d.H., N.H.O., P.C.D., J.L.K., and M.J.B. analyzed data; K.E.K., S.P.P., A.M.C.-R., J.R.-C., J.L.K., and M.J.B. wrote the paper; and all authors edited the paper.
Competing interests
K.E.K., S.P.P., A.M.C.-R., J.R.-C., R.M.S., C.E.E., M.E., M.E.A., J.L.K., and M.J.B. declare no competing interest. N.H.O., C.J.P., and H.A.R. are members of the Scientific Advisory Board of Clue Genetics, Inc. N.H.O. is also a member of the Scientific Advisory Board of Mycosynthetix, Inc. J.J.J.v.d.H. is a member of the Scientific Advisory Board of NAICONS Srl. P.C.D. is a scientific co-founder and advisor to Ometa and Enveda with prior approval by UC-San Diego and an advisor to Cybele.
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This article is a PNAS Direct Submission.
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Trachymyrmex septentrionalis ants promote fungus garden hygiene using Trichoderma-derived metabolite cues, Proc. Natl. Acad. Sci. U.S.A.
120 (25) e2219373120,
https://doi.org/10.1073/pnas.2219373120
(2023).
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