Nonribosomal peptide synthetases and their biotechnological potential in Penicillium rubens

Pro-inflammatory properties of aureocin A53

Aureocin A53 is a peptide bacteriocin produced by an opportunistic pathogen Staphylococcus aureus strain A53. The spatial structure of aureocin, unlike its amino acid sequence, is similar to the bacteriocin BacSp222, which was recently found to have the ability to induce the inflammatory response in the host cells. The presented research aimed to verify such properties also for aureocin A53. We demonstrated that the synthetic aureocin has slight cytotoxic activity towards murine monocytic-macrophage cells. This molecule was also able to activate murine P388.D1 and RAW 264.7 cells to IFN-γ-dependent production of nitric oxide and to activate production of the pro-inflammatory cytokine - TNF. We also proved that the observed pro-inflammatory activity of the studied bacteriocin is related to the stimulation of the TLR2/TLR6 heterodimer and, consequently, activation of the NF-κB transcription factor. To sum up, A53 is the second bacteriocin described in the literature, showing the pro-inflammatory activity against murine macrophage-like cells.

The Transcription Factors AcuK and AcuM Influence Siderophore Biosynthesis of Aspergillus fumigatus

The mold Aspergillus fumigatus employs two high-affinity uptake systems, reductive iron assimilation (RIA) and siderophore-mediated iron acquisition (SIA), for the acquisition of the essential trace element iron. SIA has previously been shown to be crucial for virulence in mammalian hosts. Here, we show that a lack of AcuK or AcuM, transcription factors required for the activation of gluconeogenesis, decreases the production of both extra- and intracellular siderophores in A. fumigatus. The lack of AcuM or AcuK did not affect the expression of genes involved in RIA and SIA, suggesting that these regulators do not directly regulate iron homeostasis genes, but indirectly affect siderophore production through their influence on metabolism. Consistent with this, acetate supplementation reversed the intracellular siderophore production defect of ΔacuM and ΔacuK. Moreover, ΔacuM and ΔacuK displayed a similar growth defect under iron limitation and iron sufficiency, which suggests they have a general role in carbon metabolism apart from gluconeogenesis. In agreement with a potential role of the glyoxylate cycle in adaptation to iron starvation, transcript levels of the malate synthase-encoding acuE were found to be upregulated by iron limitation that is partially dependent on AcuK and AcuM. Together, these data demonstrate the influence of iron availability on carbon metabolism.

Whole-genome sequencing and comparative genomic analyses of the medicinal fungus Sanguinoderma infundibulare in Ganodermataceae

Sanguinoderma infundibulare is a newly discovered species of Ganodermataceae known to have high medicinal and ecological values. In this study, the whole-genome sequencing and comparative genomic analyses were conducted to further understand Ganodermataceae's genomic structural and functional characteristics. Using the Illumina NovaSeq and PacBio Sequel platforms, 88 scaffolds were assembled to obtain a 48.99-Mb high-quality genome of S. infundibulare. A total of 14,146 protein-coding genes were annotated in the whole genome, with 98.6% of complete benchmarking universal single-copy orthologs (BUSCO) scores. Comparative genomic analyses were conducted among S. infundibulare, Sanguinoderma rugosum, Ganoderma lucidum, and Ganoderma sinense to determine their intergeneric differences. The 4 species were found to share 4,011 orthogroups, and 24 specific gene families were detected in the genus Sanguinoderma. The gene families associated with carbohydrate esterase in S. infundibulare were significantly abundant, which was reported to be involved in hemicellulose degradation. One specific gene family in Sanguinoderma was annotated with siroheme synthase, which may be related to the typical characteristics of fresh pore surface changing to blood red when bruised. This study enriched the available genome data for the genus Sanguinoderma, elucidated the differences between Ganoderma and Sanguinoderma, and provided insights into the characteristics of the genome structure and function of S. infundibulare.

Diversity and Mechanisms of Action of Plant, Animal, and Human Antimicrobial Peptides

Antimicrobial peptides (AMPs) are usually made up of fewer than 100 amino acid residues. They are found in many living organisms and are an important factor in those organisms' innate immune systems. AMPs can be extracted from various living sources, including bacteria, plants, animals, and even humans. They are usually cationic peptides with an amphiphilic structure, which allows them to easily bind and interact with the cellular membranes of viruses, bacteria, fungi, and other pathogens. They can act against both Gram-negative and Gram-positive pathogens and have various modes of action against them. Some attack the pathogens' membranes, while others target their intracellular organelles, as well as their nucleic acids, proteins, and metabolic pathways. A crucial area of AMP use is related to their ability to help with emerging antibiotic resistance: some AMPs are active against resistant strains and are susceptible to peptide engineering. This review considers AMPs from three key sources-plants, animals, and humans-as well as their modes of action and some AMP sequences.

Reconciliation and evolution of Penicillium rubens genome-scale metabolic networks-What about specialised metabolism?

In recent years, genome sequencing of filamentous fungi has revealed a high proportion of specialised metabolites with growing pharmaceutical interest. However, detecting such metabolites through in silico genome analysis does not necessarily guarantee their expression under laboratory conditions. However, one plausible strategy for enabling their production lies in modifying the growth conditions. Devising a comprehensive experimental design testing in different culture environments is time-consuming and expensive. Therefore, using in silico modelling as a preliminary step, such as Genome-Scale Metabolic Network (GSMN), represents a promising approach to predicting and understanding the observed specialised metabolite production in a given organism. To address these questions, we reconstructed a new high-quality GSMN for the Penicillium rubens Wisconsin 54-1255 strain, a commonly used model organism. Our reconstruction, iPrub22, adheres to current convention standards and quality criteria, incorporating updated functional annotations, orthology searches with different GSMN templates, data from previous reconstructions, and manual curation steps targeting primary and specialised metabolites. With a MEMOTE score of 74% and a metabolic coverage of 45%, iPrub22 includes 5,192 unique metabolites interconnected by 5,919 reactions, of which 5,033 are supported by at least one genomic sequence. Of the metabolites present in iPrub22, 13% are categorised as belonging to specialised metabolism. While our high-quality GSMN provides a valuable resource for investigating known phenotypes expressed in P. rubens, our analysis identifies bottlenecks related, in particular, to the definition of what is a specialised metabolite, which requires consensus within the scientific community. It also points out the necessity of accessible, standardised and exhaustive databases of specialised metabolites. These questions must be addressed to fully unlock the potential of natural product production in P. rubens and other filamentous fungi. Our work represents a foundational step towards the objective of rationalising the production of natural products through GSMN modelling.

Training Neural Network Models Using Molecular Dynamics Simulation Results to Efficiently Predict Cyclic Hexapeptide Structural Ensembles

Cyclic peptides have emerged as a promising class of therapeutics. However, their de novo design remains challenging, and many cyclic peptide drugs are simply natural products or their derivatives. Most cyclic peptides, including the current cyclic peptide drugs, adopt multiple conformations in water. The ability to characterize cyclic peptide structural ensembles would greatly aid their rational design. In a previous pioneering study, our group demonstrated that using molecular dynamics results to train machine learning models can efficiently predict structural ensembles of cyclic pentapeptides. Using this method, which was termed StrEAMM (Structural Ensembles Achieved by Molecular Dynamics and Machine Learning), linear regression models were able to predict the structural ensembles for an independent test set with R² = 0.94 between the predicted populations for specific structures and the observed populations in molecular dynamics simulations for cyclic pentapeptides. An underlying assumption in these StrEAMM models is that cyclic peptide structural preferences are predominantly influenced by neighboring interactions, namely, interactions between (1,2) and (1,3) residues. Here we demonstrate that for larger cyclic peptides such as cyclic hexapeptides, linear regression models including only (1,2) and (1,3) interactions fail to produce satisfactory predictions (R² = 0.47); further inclusion of (1,4) interactions leads to moderate improvements (R² = 0.75). We show that when using convolutional neural networks and graph neural networks to incorporate complex nonlinear interaction patterns, we can achieve R² = 0.97 and R² = 0.91 for cyclic pentapeptides and hexapeptides, respectively.

BacSp222 bacteriocin as a novel ligand for TLR2/TLR6 heterodimer

OBJECTIVE AND DESIGN

BacSp222 bacteriocin is a bactericidal and proinflammatory peptide stimulating immune cells to produce selected cytokines and NO in NF-ĸB dependent manner. This study aims to identify the receptor which mediates this activity.

METHODS

We applied fluorescently labeled BacSp222 and a confocal microscopy imaging to analyze the direct interaction of the bacteriocin with the cells. Reporter HEK-Blue cells overexpressing human toll-like receptors (TLR2, TLR4, TLR5 or TLR2/TLR1 and TLR2/TLR6 heterodimers) were stimulated with BacSp222, and then the activity of NF-ĸB-dependent secreted embryonic alkaline phosphatase (SEAP) was measured. In turn, formylated peptide receptor (FPR) or TLR2 antagonists were used to verify bacteriocin-stimulated TNF production by murine monocyte-macrophage cell lines.

RESULTS

BacSp222 undergoes internalization into cells without disturbing the cell membrane. FPR antagonists do not affect TNF produced by BacSp222-stimulated murine macrophage-like cells. In contrast, BacSp222 stimulates NF-ĸB activation in HEK-Blue overexpressing TLR2 or TLR2/TLR6 heterodimer, but not TLR2/TLR1, TLR4 or TLR5 receptors. Moreover, TLR2-specific antagonists inhibit NF-ĸB signaling in BacSp222-stimulated HEK-Blue TLR2/TLR6 cells and reduce TNF release by BacSp222-treated RAW 264.7 and P388.D1.

CONCLUSIONS

BacSp222 is a novel ligand for TLR2/TLR6 heterodimer. By binding TLR complex the bacteriocin undergoes internalization, inducing proinflammatory signaling that employs MyD88 and NF-ĸB pathways.

Emulating nonribosomal peptides with ribosomal biosynthetic strategies

Peptide natural products are important lead structures for human drugs and many nonribosomal peptides possess antibiotic activity. This makes them interesting targets for engineering approaches to generate peptide analogues with, for example, increased bioactivities. Nonribosomal peptides are produced by huge mega-enzyme complexes in an assembly-line like manner, and hence, these biosynthetic pathways are challenging to engineer. In the past decade, more and more structural features thought to be unique to nonribosomal peptides were found in ribosomally synthesised and posttranslationally modified peptides as well. These streamlined ribosomal pathways with modifying enzymes that are often promiscuous and with gene-encoded precursor proteins that can be modified easily, offer several advantages to produce designer peptides. This review aims to provide an overview of recent progress in this emerging research area by comparing structural features common to both nonribosomal and ribosomally synthesised and posttranslationally modified peptides in the first part and highlighting synthetic biology strategies for emulating nonribosomal peptides by ribosomal pathway engineering in the second part.

Transcriptional Activation of Biosynthetic Gene Clusters in Filamentous Fungi

Filamentous fungi are highly productive cell factories, many of which are industrial producers of enzymes, organic acids, and secondary metabolites. The increasing number of sequenced fungal genomes revealed a vast and unexplored biosynthetic potential in the form of transcriptionally silent secondary metabolite biosynthetic gene clusters (BGCs). Various strategies have been carried out to explore and mine this untapped source of bioactive molecules, and with the advent of synthetic biology, novel applications, and tools have been developed for filamentous fungi. Here we summarize approaches aiming for the expression of endogenous or exogenous natural product BGCs, including synthetic transcription factors, assembly of artificial transcription units, gene cluster refactoring, fungal shuttle vectors, and platform strains.

Penicillium chrysogenum, a Vintage Model with a Cutting-Edge Profile in Biotechnology

The discovery of penicillin entailed a decisive breakthrough in medicine. No other medical advance has ever had the same impact in the clinical practise. The fungus Penicillium chrysogenum (reclassified as P. rubens) has been used for industrial production of penicillin ever since the forties of the past century; industrial biotechnology developed hand in hand with it, and currently P. chrysogenum is a thoroughly studied model for secondary metabolite production and regulation. In addition to its role as penicillin producer, recent synthetic biology advances have put P. chrysogenum on the path to become a cell factory for the production of metabolites with biotechnological interest. In this review, we tell the history of P. chrysogenum, from the discovery of penicillin and the first isolation of strains with high production capacity to the most recent research advances with the fungus. We will describe how classical strain improvement programs achieved the goal of increasing production and how the development of different molecular tools allowed further improvements. The discovery of the penicillin gene cluster, the origin of the penicillin genes, the regulation of penicillin production, and a compilation of other P. chrysogenum secondary metabolites will also be covered and updated in this work.

Biosynthetic process and strain improvement approaches for industrial penicillin production

Penicillins and cephalosporins are the most important class of beta (β) lactam antibiotics, accounting for 65% total antibiotic market. Penicillins are produced by Penicillium rubens (popularly known as P. chrysogenum) were used to synthesize the active pharmaceutical intermediate (API), 6-aminopenicillinic acid (6-APA) employed in semisynthetic antibiotic production. The wild strains produce a negligible amount of penicillin (Pen). High antibiotic titre-producing P. chrysogenum strains are necessitating for industrial Pen production to meet global demand at lower prices. Classical strain improvement (CSI) approaches such as random mutagenesis, medium engineering, and fermentation are the cornerstones for high-titer Pen production. Since, Sir Alexander Fleming Discovery of Pen, great efforts are expanded to develop at a commercial scale antibiotics producing strains. Breakthroughs in genetic engineering, heterologous expression and CRISPR/Cas9 genome editing tools opened a new window for Pen production at a commercial scale to assure health crisis. The current state of knowledge, limitations of CSI and genetic engineering approaches to Pen production are discussed in this review.

Genome mining for drug discovery: progress at the front end

Microbial genome mining for drug discovery and development has been accelerating in recent years, driven by technical advancements in genome sequencing, bioinformatics, metabolomics/metabologenomics, and synthetic biology. Microbial genome mining is a multistep process that starts with the sequencing of microbes that encode multiple secondary metabolites and identifying new and novel secondary metabolite biosynthetic gene clusters (BGCs) to pursue. The initial steps in the process are critical for the overall success, and they encompass the most innovative new technologies to revitalize natural product discovery. As microbial genome mining has matured in recent years, unvalidated conjectures about what microbes to pursue, how to identify legitimate secondary metabolite BGCs, and how to sequence DNA to satisfactory levels of completion have been identified. The solutions to correct the misconceptions around these topics are beginning to be implemented.