MCF influence growth and developmental phenotypes in receiver species
Aspergillus metabolites promote Bacillus growth and biofilm formation. Late-log phase Aspergillus culture extracts significantly promoted Bacillus growth phenotypes. Higher growth indices, including cell turbidity (36-48 h), viability (36 h, p < 0.01), and biomass (12 h and 36 h, p < 0.01) were observed in the MCF-1 treated groups as compared to the controls (Fig. 1a-c). Furthermore, early onset of significantly higher biofilm formation was recorded for MCF-treated Bacillus cultures (24-36 h, p < 0.01) compared to the controls (Fig. 1d).
Bacillus metabolites suppressed Aspergillus growth and conidiation. Analysis of the MCF-2 (Bd → Ar) results revealed that late-log phase metabolite extracts from Bacillus culture displayed fungistatic effects on Aspergillus (Fig. 1e and 1f). Following the MCF-2, a significantly lower mycelial growth was observed for 120 h (p < 0.01) and 168 h incubated Aspergillus cultures as compared to the controls. Further, we recorded a significantly lower conidia density in MCF-2 cross-fed Aspergillus cultures at 168 h (p < 0.01) compared to the control. The inhibitory effects of Bacillus metabolites on Aspergillus conidiation were transient the higher conidia density was recorded for 216 h (p < 0.01) incubated Aspergillus cultures following the MCF-2, as compared to the controls.
MCF modulate endogenous metabolites secreted by receiver species
Aspergillus metabolites reduced the secretion of cyclic lipopeptides (CLPs) in Bacillus. We examined the time-correlated exometabolomes of Bacillus subjected to MCF-1 (Ad → Br) treatment with Aspergillus culture extracts. MVA based on LC-MS datasets displayed a clear disparity between the metabolite profiles of the cross-fed Bacillus cultures and the control sets. The unsupervised principal component analysis (PCA) score plot showed an overall variability of 26.14% (PC1 = 16.50%; PC2 = 9.64%) with the datasets segregated temporally between the cross-fed and control groups during the initial growth stages (up to 12 h). However, the datasets representing later stages (24-48 h) of growth were clustered together (Fig. 2a). The supervised partial least squared–discriminant analysis (PLS-DA) score plot also highlighted temporal segregation between the cross-fed treated and control sets across PLS 1 (Fig. 2b). PLS-DA showed an overall variance of 21.25% (PLS1 = 9.55%; PLS2 = 11.90%) among the datasets and indicated 27 significantly discriminant metabolites based on their variable importance projection (VIP) at > 0.7 and p < 0.05. From the significantly discriminant variables between the MCF-1 treated and control sets, we characterized 17 metabolites of bacterial origin, mostly CLPs, and three metabolites of Aspergillus origin re-extracted from Bacillus cultures, and 8 non-identified (N.I) entities (Supplementary Table 1). The PLS-DA model was evaluated with reliable goodness-of-fit parameters, including R2X (0.302), R2Y (0.987), and Q2 (0.885).
Cross-fed Aspergillus metabolites that were re-extracted and characterized from Bacillus cultures include oxylipins 9,12,13-trihydroxyoctadec-10-enoic acid (9,12,13-TriHOME) and 12,13-dihydroxy-9-octadecenoic acid (12,13-DiHOME). In addition, sphingofungin B and a non-identified (N.I. 1) compound of fungal origin were also detected from Bacillus cultures. After 12 h of incubation, we recorded a rapid depletion of the cross-fed Aspergillus metabolites from Bacillus cultures (Fig. 2c). Considering the endogenous metabolites of Bacillus origin, CLPs constituted the largest proportion of the detected compounds, including the iturins, fengycins, and surfactins. Notably, the cross-fed Bacillus cultures displayed a lower relative abundance of most CLPs as compared to the control cultures (Fig. 2c). However, significantly higher levels of linear surfactins, including B-C16 (m/z 1068), A-C15 (m/z 1054), B-C15 (m/z 1040), B-C14 (m/z 1026), and B-C13 (m/z 1012) were recorded for cross-fed Bacillus. Further, a hybrid PK-NRP compound, dihydrobacillaene, was also characterized from Bacillus cultures with its lower relative abundance in cross-fed samples compared to the controls. Non-identified metabolites of Bacillus origin including N.I. 2, 3, and 4 were significantly lower in cross-fed cultures as compared to the controls. In contrast, N.I. 7 was relatively higher in cross-fed cultures, however the remaining metabolites displayed a similar abundance among both the cross-fed and control Bacillus cultures.
Bacillus metabolites rewired oxylipin production in Aspergillus. The unsupervised PCA score plot indicated a clear segregation between the metabolite profiles of Aspergillus subjected to MCF-2 (Bd → Ar) and control groups, with an overall variance of 26.00% (PC1 = 16.00%; PC2 = 10.00%) (Fig. 3a). Similar patterns were evident in the PLS-DA score plot with the datasets of cross-fed samples clustered separately from the controls across PLS1 (Fig. 3b). PLS-DA showed an overall variance of 25.20% (PLS1 = 12.70%; PLS2 = 12.50%) between the cross-fed and control samples with goodness-of-fit parameters of R2X (0.306), R2Y (0.999), and Q2Y (0.931). Based on the PLS-DA model, we selected 23 significantly discriminant metabolites (VIP > 0.7, p < 0.05) which contributed most to the observed variance in metabolite profiles (Supplementary Table 2). Cross-fed Aspergillus cultures (MCF-2) displayed 13 metabolites of Bacillus origin including 1 iturin and 12 surfactin (cyclic and linear). Notably, the cyclic surfactins including B-C16 (m/z 1050), A-C15 (m/z 1036), B-C15 (m/z 1022), B-C14 (m/z 1008), and B-C13 (m/z 994) were significantly depleted after 120 h of incubation in cross-fed Aspergillus cultures (Fig. 3c). However, a higher temporal abundance of linear surfactins including B-C16 (m/z 1068), A-C15 (m/z 1054), B-C15 (m/z 1040), B-C14 (m/z 1026), and B-C13 (m/z 1012) was evident for MCF-2 treated Aspergillus cultures. We did not detect other CLPs (except iturin A-C15) from Aspergillus broth upon re-extraction following MCF-2 treatment. Iturin concentration remained roughly same throughout incubation (except at 168 h) in cross-fed Aspergillus cultures. We noted marked disparity in the endogenous metabolite levels between the cross-fed (MCF-2) and control Aspergillus cultures. Endogenous metabolites including a polyketide (citreoisocoumarin), a sesquiterpenoid (asperaculin A), an alkaloid (sphingofungin B) and five oxylipins namely 9,12,13-TriHOME, 5,8-dihydroxyoctadeca-9,12-dienoic acid (5,8-DiHODE), 9-hydroperoxy-11,12-octadecadienoic acid (9-HpODE), 12,13-DiHOME, and 13-hydroxyoctadecadienoic acid (13-HODE) were observed significantly discriminant. Compared to the control, significantly higher relative abundance of citreoisocoumarin and linoleate oxylipins (5,8-DiHODE and 9-HpODE) coupled with lower levels of asperculin A and oleate oxylipins (9,12,13-TriHOME and 12,13-DiHOME) were evident for cross-fed Aspergillus cultures. The relative concentrations of sphingofungin B, 13-HODE, and two non-identified (N.I. 1 and N.I. 2) metabolites of Aspergillus origin observed roughly similar for both the cross-fed and control cultures.
Metabolite determinants of Bacillus-Aspergillus interactions
Oxylipin 12,13-DiHOME promotes Bacillus growth and surfactin production. To investigate how oxylipins influence Bacillus growth, we selected 12,13-DiHOME from Aspergillus extracts based on the following two criteria: (1) it was the only oleate oxylipin (other than 9,12,13-TriHOME) that was re-extracted following the MCF-1 (Ad → Br) from Bacillus cultures, and (2) it is the only di-hydroxy oleate derivative biosynthesized with fatty acid diol synthases (FADS). Reportedly, oleate oxylipins biosynthesized with FADS activity influence bacterial physiology, flagellar motility, and biofilm formation .
Bacillus cross-fed with standard oxylipin (12,13-DiHOME) displayed significantly higher growth indices (cell turbidity, viability, and dry weight) than the control sets (Fig. 4a-c). Unlike MCF-1, we observed a transient increase (≤ 12 h) in biofilm formation for the cross-fed Bacillus. Biofilm formations were significantly higher in control Bacillus cultures between 24-48 h (p<0.01) as compared to the oxylipin treated cultures (Fig. 4d). Being a cyclical phenomenon, both the oxylipin treated and control samples displayed lower biofilm formation during the later stages of incubation. Considering the metabolomes, MVA (PCA and PLS-DA) highlighted a significant variance between the oxylipin treated and control Bacillus cultures (Supplementary fig. 1a and b). Based on the orthogonal projection to latent structures -discriminant analysis (OPLS-DA), we selected the endogenous metabolites as the biomarkers signifying high variance and correlations within the datasets representing oxylipin 12,13-DiHOME treated and control Bacillus cultures (Fig. 4e). Following the fast depletion of 12,13-DiHOME during initial growth stages, oxylipin treated Bacillus cultures showed higher relative abundance of cyclic and linear surfactins coupled with lower levels of iturins, dihydrobacillaene, and most fengycins except A-C14 derivative (Supplementary fig. 1c).
Cyclic surfactin A-C15 suppressed growth and metabolism in Aspergillus. Based on the metabolite profiling of the Bacillus extracts cross-fed to Aspergillus cultures in MCF-2, we concluded that surfactins could be the major determinants of Bacillus-Aspergillus interactions. Considering cyclic surfactin A-C15 as the representative of Bacillus CLPs re-extracted primarily from the cross-fed Aspergillus cultures, we tested its effects on the ecological fitness of fungal partner.
Notably, the mycelial weights for the surfactin treated Aspergillus cultures remain temporally unvaried and significantly lower compared to the control sets between 120-216 h (Fig. 5a). Moreover, the treated sets also showed significantly lower conidia density compared to the respective controls, p<0.01 (Fig. 5b). MVA (PCA and PLS-DA) highlighted a marked disparity in the metabolite profiles of the surfactin treated and control Aspergillus cultures (Supplementary fig. 2a and b). The OPLS-DA derived S-plot highlighted the metabolite biomarkers which demarcated the observed variance between the surfactin treated and control Aspergillus cultures (Fig. 5c). In corroboration with MCF-2, cyclic surfactin A-C15 (m/z, 1036) concentration was decreased while that of its linear derivative (m/z, 1054) increased temporally in treated Aspergillus cultures. Unlike MCF-2, the endogenous metabolomes for surfactin treated Aspergillus cultures were characterized with lower relative abundance of most oxylipins (5,8-DiHODE, 9,12,13-TriHOME, 12,13-DiHOME, and 13-HODE) except 9-HpODE as compared to the control. Further, we observed lower levels of citreoisocoumarin and asperculin A coupled with significantly higher abundance of sphingofungin B for surfactin treated cultures as compared with control cultures (Supplementary fig. 2c).
Bivariate correlations recapitulate metabolite mediated interactions. Pearson’s correlation networks inferred how the communalities in the metabolomic data, including both the cross-fed metabolites from donor species and the perturbations in endogenous metabolites, influence phenotypes in receiver species. Cross-fed metabolites are either consumed or transformed, and hence are depleted or enriched, respectively, by receiver species. If the depletion of the cross-fed metabolites was concomitant with higher phenotypes, we assumed their positive effects on the fitness of receiver species despite a negative correlation value. However, structural transformation of the cross-fed metabolites resulting in higher abundance of the derivative compounds succeeded by diminished phenotypes would correspond to have negative effect on the receiver’s fitness despite positive statistical correlations. In contrast, any variation in the endogenous metabolite levels would establish a direct correlation with phenotypes in receiver species. For the endogenous metabolites, positive correlations would be inferred to be phenotype promoting and vice-versa.
In MCF-1 (Ad → Br), Aspergillus derived oleate oxylipins (9,12,13-TriHOME and 12,13-DiHOME) and an alkaloid (sphingofungin) displayed weak negative correlations (0 > r ≥ - 0.4) with Bacillus biomass and biofilm (Fig. 6a). However, strong negative (r ≤ - 0.4) correlations were evident between 12,13-DiHOME, sphingofungin, and a non-identified metabolite (b.a.n.1) of Aspergillus origin and Bacillus viability. All cross-fed metabolites displayed strong negative correlations with Bacillus culture turbidity. Consumption-driven depletion of cross-fed Aspergillus metabolites promoted higher growth phenotypes in Bacillus. This was evident by the fast depletion of 12,13-DiHOME, where the strong negative correlations were concomitant with higher growth and biofilm phenotypes in Bacillus (Fig. 6b). Considering the endogenous metabolites of Bacillus origin, most CLPs which are temporally synthesized and secreted during growth displayed positive correlations (0 < r ≤ 0.4 or r ≥ 0.4) with Bacillus phenotypes in MCF-1 (Fig. 6a). The only exception being dihydrobacillaene which showed strong negative correlations with all Bacillus phenotypes. Like MCF-1, treating Bacillus with 12,13-DiHOME also influenced endogenous metabolites (CLPs) which showed positive correlations (except dihydrobacillaene) with growth phenotypes (Fig. 6b).
Cross-feeding Bacillus extracts inhibited the mycelial growth and conidiation in Aspergillus following MCF-2 (Bd → Ar). We noted strong negative correlations between the cross-fed cyclic surfactins and the Aspergillus phenotypes (Fig. 6c). However, the linearized derivatives of cyclic surfactins displayed weak positive (0 < r ≤ 0.4) correlations with Aspergillus phenotypes. Hydrolytic transformation of cyclic surfactins to linear derivatives did not promote Aspergillus fitness significantly. Cross-feeding cyclic surfactin A-C15 standard also suggested the negative effects of Bacillus CLPs on Aspergillus fitness (Fig. 6d). However, unlike MCF-2 we observed a negative correlation between the linear surfactin (A-C15) levels and Aspergillus phenotypes, i.e., conidiation (r ≤ - 0.4) and mycelial growth (0 > r ≥ - 0.4). Considering the influence if endogenous metabolites of Aspergillus origin following MCF-2, mycelial growth was positively correlated (r ≥ 0.4) with asperculin A and all oxylipins except 12,13-DiHOME (Fig. 6c). For Aspergillus cross-fed with standard surfactin A-C15, perturbation in endogenous metabolite levels also influenced fungal growth and conidiation (except sphingofungin and 9-HpODE) positively (r ≥ 0.4) which broadly verified the observations of MCF-2 experiment (Fig. 6d).