Microbial Biotechnology最新文献

This study investigated temporal dynamics in reactor performance and microbial community structure during anaerobic digestion of sewage sludge when the temperature was changed from 37°C to 55°C, followed by an increase in organic loading rate (OLR). Performance instability was observed immediately following the temperature increase and in the end of the study when the OLR was 11.1 ± 0.3 kgVS m⁻³d⁻¹. The specific methane production peaked at 0.31 ± 0.06 Nm³ kg⁻¹ volatile solids (VS) during thermophilic operation and when the OLR was 3.5 ± 0.9 kgVS m⁻³d⁻¹. Using metagenomic sequencing, 304 species-representative genome bins (SGB) were assembled. Network analysis revealed that 186 SGB were associated with thermophilic conditions and several new species putatively involved in key reactor functions were identified. When reactor function initially stabilised, two hydrogenotrophic and one aceticlastic methanogen (Methanothermobacter spp. and Methanosarcina thermophila), the hydrolytic Coprothermobacter proteolyticus, and putative syntrophic propionate oxidisers (e.g., Pelotomaculaceae) had high relative abundance. During the peak in specific gas production, the community was dominated by one hydrogenotrophic Methanothermobacter species coexisting with syntrophic acetate oxidising bacteria (Thermacetogenium phaeum and other species). Finally, when the reaction function deteriorated due to high OLR, new hydrolytic taxa emerged and the same aceticlastic methanogen as seen during the initial acclimatisation phase returned.

This study investigated temporal dynamics in reactor performance and microbial community structure during anaerobic digestion of sewage sludge when the temperature was changed from 37°C to 55°C, followed by an increase in organic loading rate (OLR). Performance instability was observed immediately following the temperature increase and in the end of the study when the OLR was 11.1 ± 0.3 kgVS m⁻³d⁻¹. The specific methane production peaked at 0.31 ± 0.06 Nm³ kg⁻¹ volatile solids (VS) during thermophilic operation and when the OLR was 3.5 ± 0.9 kgVS m⁻³d⁻¹. Using metagenomic sequencing, 304 species-representative genome bins (SGB) were assembled. Network analysis revealed that 186 SGB were associated with thermophilic conditions and several new species putatively involved in key reactor functions were identified. When reactor function initially stabilised, two hydrogenotrophic and one aceticlastic methanogen (Methanothermobacter spp. and Methanosarcina thermophila), the hydrolytic Coprothermobacter proteolyticus, and putative syntrophic propionate oxidisers (e.g., Pelotomaculaceae) had high relative abundance. During the peak in specific gas production, the community was dominated by one hydrogenotrophic Methanothermobacter species coexisting with syntrophic acetate oxidising bacteria (Thermacetogenium phaeum and other species). Finally, when the reaction function deteriorated due to high OLR, new hydrolytic taxa emerged and the same aceticlastic methanogen as seen during the initial acclimatisation phase returned.

Microorganism culturing is essential in microbiological research, with the selection of suitable culture media being critical for successful microbial growth. Traditionally, this selection has relied on empirical knowledge or trial and error, often resulting in inefficiency. In this study, we analysed nutrient compositions from the MediaDive database to construct a dataset of 2369 media types. Leveraging this dataset and microbial 16S rRNA sequences, we developed 45 binary classification models using the XGBoost algorithm. These models demonstrated strong predictive performance, achieving accuracies ranging from 76% to 99.3%, with the top-performing models for J386, J50 and J66 media reaching 99.3%, 98.9% and 98.8%, respectively. The models effectively predicted growth conditions for various human gut microbes, confirming their practical utility. This research improves the efficiency of microbial cultivation and highlights the potential of machine learning to optimise culture media selection and advance microbiological studies.

Microorganism culturing is essential in microbiological research, with the selection of suitable culture media being critical for successful microbial growth. Traditionally, this selection has relied on empirical knowledge or trial and error, often resulting in inefficiency. In this study, we analysed nutrient compositions from the MediaDive database to construct a dataset of 2369 media types. Leveraging this dataset and microbial 16S rRNA sequences, we developed 45 binary classification models using the XGBoost algorithm. These models demonstrated strong predictive performance, achieving accuracies ranging from 76% to 99.3%, with the top-performing models for J386, J50 and J66 media reaching 99.3%, 98.9% and 98.8%, respectively. The models effectively predicted growth conditions for various human gut microbes, confirming their practical utility. This research improves the efficiency of microbial cultivation and highlights the potential of machine learning to optimise culture media selection and advance microbiological studies.

The cytochrome P450 monooxygenase enzymes (CYPs) of the CYP102 family are versatile, self-sufficient biocatalysts. The archetypal example is CYP102A1 (P450_BM3) from the bacterium Bacillus (Priestia) megaterium, and variants of this enzyme can oxidise many substrates with high activity and selectivity. However, this enzyme has relatively low thermal stability. Here, we identify and characterise a CYP102 family enzyme from the moderately thermophilic bacterium Thermosporothrix hazakensis. We were able to produce this enzyme using Escherichia coli and demonstrate the in vivo oxidation of fatty acids. However, the activity of the isolated holoenzyme was low, so we generated a peroxygenase variant by introducing the E278Q and T279E mutations into the heme domain (‘HazakQE’). This isolated variant was able to catalyse the oxidation of a range of substrates using hydrogen peroxide as the oxidant. The product distributions arising from fatty acid oxidation using the holoprotein monooxygenase and heme domain peroxygenase variants of this enzyme were broadly similar to those obtained with P450_BM3. For fatty acids, the oxidation occurred predominantly at the ω-1 through to ω-3 positions. Styrene was epoxidised and tetralone hydroxylated at the benzylic carbon. The oxidation of 1-methoxynaphthalene generated the dimeric Russig's blue, enabling colorimetric assays of the enzyme activity. Although the HazakQE heme peroxygenase was more thermostable than the mesophilic CYP199A4 enzyme from Rhodopseudomonas palustris, it was not more resistant to heating than the heme domain of P450_BM3. These peroxygenase variants offer a simple platform for metabolite identification and biocatalysts for oxidation reactions, which could be enhanced through protein engineering.

Microbial and biochemical research has historically focused on pathogenic agents due to their clear association with disease. This is a perspective that has saved countless lives but encourages a skewed, threat-centered view of microbes and biogenic compounds. Emerging evidence shows that exposure to diverse environmental microbiomes and natural biochemical products is also salutogenic—promoting health and resilience. Here we introduce the ‘Database of Salutogenic Potential’, a prototype relational repository cataloguing environmental microbes and biochemical compounds linked to health benefits. Drawing from more than 200 articles, we identified 124 potentially salutogenic microbial taxa, 14 biochemical compounds and 63 associated benefits. By creating a structured and open platform, we aim to shift the balance between pathogen-centric and salutogenic perspectives, potentially enabling future applications in public health, urban planning and ecosystem restoration. While the current iteration of the database primarily centers on human health outcomes, it is designed to expand into ecosystem health domains, embedding salutogenic thinking into One Health frameworks. We present this as a first step, not a ready-to-use tool, and invite collaborative refinement from the scientific community.

Microbial and biochemical research has historically focused on pathogenic agents due to their clear association with disease. This is a perspective that has saved countless lives but encourages a skewed, threat-centered view of microbes and biogenic compounds. Emerging evidence shows that exposure to diverse environmental microbiomes and natural biochemical products is also salutogenic—promoting health and resilience. Here we introduce the ‘Database of Salutogenic Potential’, a prototype relational repository cataloguing environmental microbes and biochemical compounds linked to health benefits. Drawing from more than 200 articles, we identified 124 potentially salutogenic microbial taxa, 14 biochemical compounds and 63 associated benefits. By creating a structured and open platform, we aim to shift the balance between pathogen-centric and salutogenic perspectives, potentially enabling future applications in public health, urban planning and ecosystem restoration. While the current iteration of the database primarily centers on human health outcomes, it is designed to expand into ecosystem health domains, embedding salutogenic thinking into One Health frameworks. We present this as a first step, not a ready-to-use tool, and invite collaborative refinement from the scientific community.

Historically, art and science have often been viewed as distinct disciplines, each with its own methodologies and modes of expression. However, a closer examination reveals a rich and complex web of interplay between the two, where scientific inquiry and artistic creativity converge to explore and interpret the natural world. In this article, we dig into the flourishing field of microbial art, with a particular focus on the utilisation of extremophilic microorganisms – organisms that thrive in conditions once deemed uninhabitable – as both objects and subjects in contemporary artistic practices. Tracing the lineage from early intersections between these two fields to modern pioneers, we highlight how microorganisms have transitioned from subjects of scientific study to integral components of artistic creation. Through case studies, we illustrated how the unique properties of extremophiles – such as their pigmentation, resilience, and metabolic capabilities – offer novel avenues for artistic exploration. Furthermore, we emphasised the reciprocal benefits of interdisciplinary collaborations between artists and scientists. In an era marked by environmental challenges and the proliferation of misinformation, the fusion of art and science emerges as a compelling strategy to promote public understanding and appreciation of complex scientific phenomena, serving also as potent tools for science communication and outreach.

Biogas inocula with distinct taxonomic compositions often converge to similar communities when fed the same substrate, indicating strong substrate-driven deterministic assembly. Nevertheless, stochastic processes have also been suggested as a critical element for microbial assembly in biogas systems. To date, assembly processes have mainly been investigated with undefined, non-sterile substrates, making it difficult to exclude the influence of external microorganisms. The aim of the present study was to investigate whether three taxonomically distinct anaerobic digestion (AD) communities would converge when exposed to uniform growth conditions during semi-continuous operation with a sterilised defined medium. The inocula originated from mesophilic processes using different substrates (food waste, sludge, and manure) and total ammonia levels (0.5–7.2 g/L). The medium was formulated to support all four main metabolic steps of AD: hydrolysis, fermentation, anaerobic oxidation, and methanogenesis. Taxonomic, phylogenetic, and functional analyses conducted via 16S and metagenomic sequencing showed that the substrate had no deterministic effect on microbial community taxonomic composition. Instead, the final community structure was dictated primarily by the initial inoculum, regardless of changes in substrate composition or ammonia levels. Despite taxonomic divergence, broad-level functionality and operational performance remained similar between communities.

Host defence peptides (HDPs) represent a valuable class of antimicrobial agents with the potential to address the growing threat of antimicrobial resistance (AMR). Here, we have studied recombinant constructs based on a combination of HDPs fused to the GFP protein and multidomain proteins combining three or four HDPs in a single polypeptide, referred to as first and second generation antimicrobials, respectively. These recombinant peptides were tested against Gram-positive and Gram-negative bacteria associated with healthcare infections. In addition, in silico studies provided insight into the antimicrobial structure–activity relationships of these biomolecules. For the first generation of antimicrobials, amphipathicity mainly explains the average antimicrobial activity against the Gram-positive strains. In the case of the Gram-negative bacteria, it depends on the quantity and the exposed area of the Ser and Thr amino acids. For the second generation of antimicrobials, the order of domains is crucial to act against Gram-positive strains, preferably by positioning the most bioactive domain against the Gram-positive pathogen at the ends.