Metabolomic profiles of the liquid state fermentation in co-culture of A. oryzae and Z. rouxii

Comparative pangenome analysis of Aspergillus flavus and Aspergillus oryzae reveals their phylogenetic, genomic, and metabolic homogeneity

Aspergillus flavus and Aspergillus oryzae are closely related fungal species with contrasting roles in food safety and fermentation. To comprehensively investigate their phylogenetic, genomic, and metabolic characteristics, we conducted an extensive comparative pangenome analysis using complete, dereplicated genome sets for both species. Phylogenetic analyses, employing both the entirety of the identified single-copy orthologous genes and six housekeeping genes commonly used for fungal classification, did not reveal clear differentiation between A. flavus and A. oryzae genomes. Upon analyzing the aflatoxin biosynthesis gene clusters within the genomes, we observed that non-aflatoxin-producing strains were dispersed throughout the phylogenetic tree, encompassing both A. flavus and A. oryzae strains. This suggests that aflatoxin production is not a distinguishing trait between the two species. Furthermore, A. oryzae and A. flavus strains displayed remarkably similar genomic attributes, including genome sizes, gene contents, and G + C contents, as well as metabolic features and pathways. The profiles of CAZyme genes and secondary metabolite biosynthesis gene clusters within the genomes of both species further highlight their similarity. Collectively, these findings challenge the conventional differentiation of A. flavus and A. oryzae as distinct species and highlight their phylogenetic, genomic, and metabolic homogeneity, potentially indicating that they may indeed belong to the same species.

Computation-aided studies related to the induction of specialized metabolite biosynthesis in microbial co-cultures: An introductory overview

Co-cultivation is an effective method of inducing the production of specialized metabolites (SMs) in microbial strains. By mimicking the ecological interactions that take place in natural environment, this approach enables to trigger the biosynthesis of molecules which are not formed under monoculture conditions. Importantly, microbial co-cultivation may lead to the discovery of novel chemical entities of pharmaceutical interest. The experimental efforts aimed at the induction of SMs are greatly facilitated by computational techniques. The aim of this overview is to highlight the relevance of computational methods for the investigation of SM induction via microbial co-cultivation. The concepts related to the induction of SMs in microbial co-cultures are briefly introduced by addressing four areas associated with the SM induction workflows, namely the detection of SMs formed exclusively under co-culture conditions, the annotation of induced SMs, the identification of SM producer strains, and the optimization of fermentation conditions. The computational infrastructure associated with these areas, including the tools of multivariate data analysis, molecular networking, genome mining and mathematical optimization, is discussed in relation to the experimental results described in recent literature. The perspective on the future developments in the field, mainly in relation to the microbiome-related research, is also provided.

Transcriptomics Reveals the Effect of Strain Interactions on the Growth of A. Oryzae and Z. Rouxii

The microbial community structure in traditional fermented foods is quite complex, making the relationship between strains unclear. In this regard, the co-culture system can simulate microbial interactions during food fermentation and reveal the morphological changes, metabolic processes, and gene expression of microbial communities. The present study sought to investigate the effects of microbial interactions on the growth of Aspergillus oryzae and Zygosaccharomyces rouxii through omics. After co-cultivation, the pH value and dry weight were consistent with the pure culture of Z. rouxii. Additionally, the consumption of reducing sugar decreased, and the enzymatic activity increased compared with the pure culture of fungus. The analysis of volatile organic compounds (VOCs) and transcriptomics showed that co-culture significantly promoted the effect on Z. rouxii. A total of 6 different VOCs and 2202 differentially expressed genes were identified in the pure and co-culture of Z. rouxii. The differentially expressed genes were mainly related to the endonucleolytic cleavage of rRNA, ribosome biogenesis in eukaryotes, and RNA polymerase metabolic pathways. The study results will provide insights into the effect of microbial interactions on the growth of A. oryzae and Z. rouxii.

Aspergillus co-cultures: A recent insight into their secondary metabolites and microbial interactions

There is an urgent need for novel antibiotics to combat emerging resistant microbial strains. One of the most pressing resources is Aspergillus microbial cocultures. The genome of Aspergillus species comprises a far larger number of novel gene clusters than previously expected, and novel strategies and approaches are essential to exploit this potential source of new drugs and pharmacological agents. This is the first review consulting recent developments and chemical diversity of Aspergillus cocultures and highlighting its untapped richness. The analyzed data revealed that cocultivation of several Aspergillus species with other microorganisms, including bacteria, plants, and fungi, is a source of novel bioactive natural products. Various vital chemical skeleton leads were newly produced or augmented in Aspergillus cocultures, among which were taxol, cytochalasans, notamides, pentapeptides, silibinin, and allianthrones. The possibility of mycotoxin production or complete elimination in cocultivations was detected, which pave the way for better decontamination strategies. Most cocultures revealed a remarkable improvement in their antimicrobial or cytotoxic behavior due to their produced chemical patterns; for instance, weldone and asperterrin whose antitumor and antibacterial activities, respectively, were superior. Microbial cocultivation elicited the upregulation or production of specific metabolites whose importance and significance are yet to be revealed. With more than 155 compounds isolated from Aspergillus cocultures in the last 10 years, showing overproduction, reduction, or complete suppression under the optimized coculture circumstances, this study filled a gap for medicinal chemists searching for new lead sources or bioactive molecules as anticancer agents or antimicrobials.

Metabolomic profiles of the liquid state fermentation in co-culture of Eurotium amstelodami and Bacillus licheniformis

As an important source of new drug molecules, secondary metabolites (SMs) produced by microorganisms possess important biological activities, such as antibacterial, anti-inflammatory, and hypoglycemic effects. However, the true potential of microbial synthesis of SMs has not been fully elucidated as the SM gene clusters remain silent under laboratory culture conditions. Herein, we evaluated the inhibitory effect of Staphylococcus aureus by co-culture of Eurotium amstelodami and three Bacillus species, including Bacillus licheniformis, Bacillus subtilis, and Bacillus amyloliquefaciens. In addition, a non-target approach based on ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC-TOF-MS) was used to detect differences in extracellular and intracellular metabolites. Notably, the co-culture of E. amstelodami and Bacillus spices significantly improved the inhibitory effect against S. aureus, with the combination of E. amstelodami and B. licheniformis showing best performance. Metabolomics data further revealed that the abundant SMs, such as Nummularine B, Lucidenic acid E2, Elatoside G, Aspergillic acid, 4-Hydroxycyclohexylcarboxylic acid, Copaene, and Pipecolic acid were significantly enhanced in co-culture. Intracellularly, the differential metabolites were involved in the metabolism of amino acids, nucleic acids, and glycerophospholipid. Overall, this work demonstrates that the co-culture strategy is beneficial for inducing biosynthesis of active metabolites in E. amstelodami and B. licheniformis.

Application of Metabolomics in Fungal Research

Metabolomics is an essential method to study the dynamic changes of metabolic networks and products using modern analytical techniques, as well as reveal the life phenomena and their inherent laws. Currently, more and more attention has been paid to the development of metabolic histochemistry in the fungus field. This paper reviews the application of metabolomics in fungal research from five aspects: identification, response to stress, metabolite discovery, metabolism engineering, and fungal interactions with plants.

Characteristics of the microbiota and metabolic profile of high-temperature Daqu with different grades

The superior grade Daqu (S_Daqu) and normal grade Daqu (N_Daqu) have obvious differences in flavor, fracture surface, appearance, etc., which can be accurately grouped by well-trained panel based on their sensory properties. However, the differences in microbial community diversity and metabolites between the S_Daqu and N_Daqu were still unclear. The culture-dependent method, the third generation Pacific Biosciences (PacBio) single-molecule, real-time (SMRT) sequencing technology, and nuclear magnetic resonance (NMR) were combined to show the characteristics in microorganisms and metabolites. Results showed that the fungal counts were higher in N_Daqu while the richness of bacterial communities was higher in S_Daqu (P < 0.05). Lentibacillus, Burkholderia, Saccharopolyspora, Thermoascus, and Rasamsonia were the dominant genera of S_Daqu while Staphylococcus, Scopulibacillus, and Chromocleista were the dominant genera in N_Daqu. The content of differential acids, amino acids, and alcohols including fumarate, glucuronate, glycine, 4-carboxyglutamate, and myo-inositol in S_Daqu was higher than that in N_Daqu by ¹H NMR coupled with multivariate statistical analysis. The network analysis regarding microbes and metabolites suggested that Saccharopolyspora showed a strong positive correlation with 4-carboxyglutamate while Thermoascus and Chromocleista were highly negatively correlated with alanine and isobutyrate, respectively. Linear Discriminant Analysis (LDA) Effect Size (LEfSe) revealed that Macrococcus and Caulobacter were regarded as bacterial biomarkers in the S_Daqu while Chromocleista was the key fungal genera in N_Daqu. Functionality prediction indicated that the bacteria in S_Daqu were largely involved in more metabolic activities including biosynthesis, degradation, detoxification, and generation of precursor metabolite and energy.