Microbial Biotechnology最新文献

Mycobacterium abscessus (MABS) displays differential subspecies susceptibility to macrolides. Thus, identifying MABS's subspecies (M. abscessus, M. bolletii and M. massiliense) is a clinical necessity for guiding treatment decisions. We aimed to assess the potential of Machine Learning (ML)-based classifiers coupled to Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) MS to identify MABS subspecies. Two spectral databases were created by using 40 confirmed MABS strains. Spectra were obtained by using MALDI-TOF MS from strains cultivated on solid (Columbia Blood Agar, CBA) or liquid (MGIT®) media for 1 to 13 days. Each database was divided into a dataset for ML-based pipeline development and a dataset to assess the performance. An in-house programme was developed to identify discriminant peaks specific to each subspecies. The peak-based approach successfully distinguished M. massiliense from the other subspecies for strains grown on CBA. The ML approach achieved 100% accuracy for subspecies identification on CBA, falling to 77.5% on MGIT®. This study validates the usefulness of ML, in particular the Random Forest algorithm, to discriminate MABS subspecies by MALDI-TOF MS. However, identification in MGIT®, a medium largely used in mycobacteriology laboratories, is not yet reliable and should be a development priority.

Previous studies have reported the functional role, biochemical features and synthesis pathway of podophyllotoxin (PTOX) in plants. In this study, we employed combined morphological and molecular techniques to identify an endophytic fungus and extract PTOX derivatives. Based on the analysis of ITS sequences and the phylogenetic tree, the isolate was classified as Penicillium herquei HGN12.1C, with a sequence identity of 98.58%. Morphologically, the HGN12.1C strain exhibits white colonies, short-branched mycelia and densely packed hyphae. Using PacBio sequencing at an average read depth of 195×, we obtained a high-quality genome for the HGN12.1C strain, which is 34.9 Mb in size, containing eight chromosomes, one mitochondrial genome and a GC content of 46.5%. Genome analysis revealed 10 genes potentially involved in PTOX biosynthesis. These genes include VdtD, Pinoresinollariciresinol reductase (PLR), Secoisolariciresinol dehydrogenase (SDH), CYP719A23, CYP71BE54, O-methyltransferase 1 (OMT1), O-methyltransferase 3 (OMT3), 2-ODD, CYP71CU and CYP82D61. Notably, the VdtD gene in fungi shares functional similarities with the DIR gene found in plants. Additionally, we identified peltatin, a PTOX derivative, in the HGN12.1C extract. Docking analysis suggests a potential role for the 2-ODD enzyme in converting yatein to deoxypodophyllotoxin. These findings offer invaluable insights into the synthesis mechanism of PTOX in fungi, shedding light on the relationship between host plants and endophytes.

Feedstock variability represents a challenge in lignocellulosic biorefineries, as it can influence both lignocellulose deconstruction and microbial conversion processes for biofuels and biochemicals production. The impact of feedstock variability on microbial performance remains underexplored, and predictive tools for microbial behaviour are needed to mitigate risks in biorefinery scale-up. Here, twelve batches of corn stover were deconstructed via deacetylation, mechanical refining, and enzymatic hydrolysis to generate lignin-rich and sugar streams. These batches and their derived streams were characterised to identify their chemical components, and the streams were used as substrates for producing muconate and butyrate by engineered Pseudomonas putida and wildtype Clostridium tyrobutyricum, respectively. Bacterial performance (growth, product titers, yields, and productivities) differed among the batches, but no strong correlations were identified between feedstock composition and performance. To provide metabolic insights into the origin of these differences, we evaluated the effect of twenty-three isolated chemical components on these microbes, including three components in relevant bioprocess settings in bioreactors, and we found that growth-inhibitory concentrations were outside the ranges observed in the streams. Overall, this study generates a foundational dataset on P. putida and C. tyrobutyricum performance to enable future predictive models and underscores their resilience in effectively converting fluctuating lignocellulose-derived streams into bioproducts.

In recent years, microbiomes and their potential applications for human, animal or plant health, food production and environmental management came into the spotlight of major national and international policies and strategies. This has been accompanied by substantial R&D investments in both public and private sectors, with an increasing number of products entering the market. Despite widespread agreement on the potential of microbiomes and their uses across disciplines, stakeholders and countries, there is no consensus on what defines a microbiome application. This often results in non-comprehensive communication or insufficient documentation making commercialisation and acceptance of the novel products challenging. To showcase the complexity of this issue we discuss two selected, well-established applications and propose criteria defining a microbiome application and their conditions of use for clear communication, facilitating suitable regulatory frameworks and building trust among stakeholders.

Expressing plant metabolic pathways in microbial platforms is an efficient, cost-effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour-intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost-effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data-driven machine learning framework designed to extract ‘yeastizing’ rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design-build-test cycle.

Next-generation DNA sequencing has shown that the great plate count anomaly, that is, the difference between bacteria present in the environment and those that can be obtained in culture from that environment, is even greater and more persisting than initially thought. This hampers fundamental understanding of bacterial physiology and biotechnological application of the unculture majority. With big sequence data as foundation, artificial intelligence (AI) may be a game changer in bacterial isolation efforts and provide directions for the cultivation media and conditions that are most promising and as such be used to canalize limited human and financial resources. This opinion paper discusses how AI is or can be used to improve the success of bacterial isolation.

Many strains from the Bacillus subtilis species complex exert strong plant growth-promoting activities. However, their efficacy in relevant conditions is variable, due in part to their inability to establish a strong interaction with roots in stressful environmental conditions. Adaptative laboratory evolution (ALE) is a powerful tool to generate novel strains with traits of interest. Many Bacillus evolved isolates, stemming from ALE performed with plants, possess a stronger root colonization capacity. An in-depth analysis of these isolates also allowed the identification of key features influencing the interaction with plant roots. However, many variables can influence the outcome of these assays, and thus, caution should be taken when designing ALE destined to generate better root colonizers.

Many strains from the Bacillus subtilis species complex exert strong plant growth-promoting activities. However, their efficacy in relevant conditions is variable, due in part to their inability to establish a strong interaction with roots in stressful environmental conditions. Adaptative laboratory evolution (ALE) is a powerful tool to generate novel strains with traits of interest. Many Bacillus evolved isolates, stemming from ALE performed with plants, possess a stronger root colonization capacity. An in-depth analysis of these isolates also allowed the identification of key features influencing the interaction with plant roots. However, many variables can influence the outcome of these assays, and thus, caution should be taken when designing ALE destined to generate better root colonizers.

To date, there are no real physiological mechanisms for iron excretion in eukaryote, and no physiological “actuator” that can control all the three fundamental biologic processes of absorption, storage, and excretion. Here, we observed that the accumulation of anthraquinones by Thermomyces dupontii under cold stress can achieve this process. Through mutation analysis, we found that mutant ΔAn deficiency in anthraquinones accumulated ferrous and total free iron due to adopting a rare lifestyle with no endocytosis but accumulation of membrane-derived vesicles. Anthraquinone complement indicated that the vesicles in ΔAn could coat the extrinsic anthraquinone-induced granules to prevent contact with the fungal interiors. Detailed chemical investigation on ΔAn led to characterization of a rare oxygen-free ergosterene with unstable nature in air as the major membrane steroid in ΔAn, suggesting hypoxia inner in ΔAn cells, consistent with dramatically low oxygen-consuming rates in ΔAn. A series of physiological and metabolic analyses indicated anthraquinones were involved in exporting ferrous and promoting formation of oxygen-containing metabolites, including ergosterols for endocytosis and iron chelators for iron storage. Moreover, we found that both the anticancer agent mitoxantrone with well-known-cardiotoxicity side effect and the major terpenoid-derived polycyclic aromatics from Danshen for treating cardiovascular disease showed potent ferrous transporting capabilities in human cancer cells. Our findings provide a novel insight into the underlying mechanisms of polycyclic aromatics in nature and pharmacology, and offer a new strategy for developing potential therapeutics and agents for membrane transport, iron homestasis, and anticold.

The exploration of novel hosts with the ability to assimilate formic acid, a C1 substrate that can be produced from renewable electrons and CO₂, is of great relevance for developing novel and sustainable biomanufacturing platforms. Formatotrophs can use formic acid or formate as a carbon and/or reducing power source. Formatotrophy has typically been studied in neutrophilic microorganisms because formic acid toxicity increases in acidic environments below the pKa of 3.75 (25°C). Because of this toxicity challenge, utilization of formic acid as either a carbon or energy source has been largely unexplored in thermoacidophiles, species that possess the ability to produce a variety of metabolites and enzymes of high biotechnological relevance. Here we investigate the capacity of several thermoacidophilic archaea species from the Sulfolobales order to tolerate and metabolize formic acid. Metallosphaera prunae, Sulfolobus metallicus and Sulfolobus acidocaldarium were found to metabolize and grow with 1–2 mM of formic acid in batch cultivations. Formic acid was co-utilized by this species alongside physiological electron donors, including ferrous iron. To enhance formic acid utilization while maintaining aqueous concentrations below the toxicity threshold, we developed a bioreactor culturing method based on a sequential formic acid feeding strategy. By dosing small amounts of formic acid sequentially and feeding H₂ as co-substrate, M. prunae could utilize a total of 16.3 mM of formic acid and grow to higher cell densities than when H₂ was supplied as a sole electron donor. These results demonstrate the viability of culturing thermoacidophilic species with formic acid as an auxiliary substrate in bioreactors to obtain higher cell densities than those yielded by conventional autotrophic conditions. Our work underscores the significance of formic acid metabolism in extreme habitats and holds promise for biotechnological applications in the realm of sustainable energy production and environmental remediation.