Structural characterization of a soil viral auxiliary metabolic gene product - a functional chitosanase

Genomic insights into redox-driven microbial processes for carbon decomposition in thawing Arctic soils and permafrost

Climate change is rapidly transforming Arctic landscapes where increasing soil temperatures speed up permafrost thaw. This exposes large carbon stocks to microbial decomposition, possibly worsening climate change by releasing more greenhouse gases. Understanding how microbes break down soil carbon, especially under the anaerobic conditions of thawing permafrost, is important to determine future changes. Here, we studied the microbial community dynamics and soil carbon decomposition potential in permafrost and active layer soils under anaerobic laboratory conditions that simulated an Arctic summer thaw. The microbial and viral compositions in the samples were analyzed based on metagenomes, metagenome-assembled genomes, and metagenomic viral contigs (mVCs). Following the thawing of permafrost, there was a notable shift in microbial community structure, with fermentative Firmicutes and Bacteroidota taking over from Actinobacteria and Proteobacteria over the 60-day incubation period. The increase in iron and sulfate-reducing microbes had a significant role in limiting methane production from thawed permafrost, underscoring the competition within microbial communities. We explored the growth strategies of microbial communities and found that slow growth was the major strategy in both the active layer and permafrost. Our findings challenge the assumption that fast-growing microbes mainly respond to environmental changes like permafrost thaw. Instead, they indicate a common strategy of slow growth among microbial communities, likely due to the thermodynamic constraints of soil substrates and electron acceptors, and the need for microbes to adjust to post-thaw conditions. The mVCs harbored a wide range of auxiliary metabolic genes that may support cell protection from ice formation in virus-infected cells.

IMPORTANCE

As the Arctic warms, thawing permafrost unlocks carbon, potentially accelerating climate change by releasing greenhouse gases. Our research delves into the underlying biogeochemical processes likely mediated by the soil microbial community in response to the wet and anaerobic conditions, akin to an Arctic summer thaw. We observed a significant shift in the microbial community post-thaw, with fermentative bacteria like Firmicutes and Bacteroidota taking over and switching to different fermentation pathways. The dominance of iron and sulfate-reducing bacteria likely constrained methane production in the thawing permafrost. Slow-growing microbes outweighed fast-growing ones, even after thaw, upending the expectation that rapid microbial responses to dominate after permafrost thaws. This research highlights the nuanced and complex interactions within Arctic soil microbial communities and underscores the challenges in predicting microbial response to environmental change.

Advances in phage-host interaction prediction: in silico method enhances the development of phage therapies

Phages can specifically recognize and kill bacteria, which lead to important application value of bacteriophage in bacterial identification and typing, livestock aquaculture and treatment of human bacterial infection. Considering the variety of human-infected bacteria and the continuous discovery of numerous pathogenic bacteria, screening suitable therapeutic phages that are capable of infecting pathogens from massive phage databases has been a principal step in phage therapy design. Experimental methods to identify phage-host interaction (PHI) are time-consuming and expensive; high-throughput computational method to predict PHI is therefore a potential substitute. Here, we systemically review bioinformatic methods for predicting PHI, introduce reference databases and in silico models applied in these methods and highlight the strengths and challenges of current tools. Finally, we discuss the application scope and future research direction of computational prediction methods, which contribute to the performance improvement of prediction models and the development of personalized phage therapy.

Crystal structure of the GH-46 subclass III chitosanase from Bacillus circulans MH-K1 in complex with chitotetraose

BACKGROUND

Chitosanases (EC 3.2.1.132) hydrolyze chitosan which is a polymer of glucosamine (GlcN) linked by β - 1,4 bonds, and show cleavage specificity against partially acetylated chitosan containing N-acetylglucosamine (GlcNAc) residues. Chitosanases' structural underpinnings for cleavage specificity and the conformational switch from open to closed structures are still a mystery.

METHODS

The GH-46 subclass III chitosanase from Bacillus circulans MH-K1 (MH-K1 chitosanase), which also catalyzes the hydrolysis of GlcN-GlcNAc bonds in addition to GlcN-GlcN, has had its chitotetraose [(GlcN)4]-complexed crystal structure solved at 1.35 Å resolution.

RESULTS

The MH-K1 chitosanase's (GlcN)4-bound structure has numerous structural similarities to other GH-46 chitosanases in terms of substrate binding and catalytic processes. However, subsite -1, which is absolutely specific for GlcN, seems to characterize the structure of a subclass III chitosanase due to its distinctive length and angle of a flexible loop. According to a comparison of the (GlcN)4-bound and apo-form structures, the particular binding of a GlcN residue at subsite -2 through Asp77 causes the backbone helix to kink, which causes the upper- and lower-domains to approach closely when binding a substrate.

CONCLUSIONS

Although GH-46 chitosanases vary in the finer details of the subsites defining cleavage specificity, they share similar structural characteristics in substrate-binding, catalytic processes, and potentially in conformational change.

GENERAL SIGNIFICANCE

The precise binding of a GlcN residue to the -2 subsite is essential for the conformational shift that occurs in all GH-46 chitosanases, as shown by the crystal structures of the apo- and substrate-bound forms of MH-K1 chitosanase.

Exploring virus-host-environment interactions in a chemotrophic-based underground estuary

BACKGROUND

Viruses play important roles in modulating microbial communities and influencing global biogeochemistry. There is now growing interest in characterising their ecological roles across diverse biomes. However, little is known about viral ecology in low-nutrient, chemotrophic-based environments. In such ecosystems, virus-driven manipulation of nutrient cycles might have profound impacts across trophic levels. In particular, anchialine environments, which are low-energy underground estuaries sustained by chemotrophic processes, represent ideal model systems to study novel virus-host-environment interactions.

RESULTS

Here, we employ metagenomic sequencing to investigate the viral community in Bundera Sinkhole, an anchialine ecosystem rich in endemic species supported by microbial chemosynthesis. We find that the viruses are highly novel, with less than 2% representing described viruses, and are hugely abundant, making up as much as 12% of microbial intracellular DNA. These highly abundant viruses largely infect important prokaryotic taxa that drive key metabolic processes in the sinkhole. Further, the abundance of viral auxiliary metabolic genes (AMGs) involved in nucleotide and protein synthesis was strongly correlated with declines in environmental phosphate and sulphate concentrations. These AMGs encoded key enzymes needed to produce sulphur-containing amino acids, and phosphorus metabolic enzymes involved in purine and pyrimidine nucleotide synthesis. We hypothesise that this correlation is either due to selection of these AMGs under low phosphate and sulphate concentrations, highlighting the dynamic interactions between viruses, their hosts, and the environment; or, that these AMGs are driving increased viral nucleotide and protein synthesis via manipulation of host phosphorus and sulphur metabolism, consequently driving nutrient depletion in the surrounding water.

CONCLUSION

This study represents the first metagenomic investigation of viruses in anchialine ecosystems, and provides new hypotheses and insights into virus-host-environment interactions in such 'dark', low-energy environments. This is particularly important since anchialine ecosystems are characterised by diverse endemic species, both in their microbial and faunal assemblages, which are primarily supported by microbial chemosynthesis. Thus, virus-host-environment interactions could have profound effects cascading through all trophic levels.

Zea mays genotype influences microbial and viral rhizobiome community structure

Plant genotype is recognized to contribute to variations in microbial community structure in the rhizosphere, soil adherent to roots. However, the extent to which the viral community varies has remained poorly understood and has the potential to contribute to variation in soil microbial communities. Here we cultivated replicates of two Zea mays genotypes, parviglumis and B73, in a greenhouse and harvested the rhizobiome (rhizoplane and rhizosphere) to identify the abundance of cells and viruses as well as rhizobiome microbial and viral community using 16S rRNA gene amplicon sequencing and genome resolved metagenomics. Our results demonstrated that viruses exceeded microbial abundance in the rhizobiome of parviglumis and B73 with a significant variation in both the microbial and viral community between the two genotypes. Of the viral contigs identified only 4.5% (n = 7) of total viral contigs were shared between the two genotypes, demonstrating that plants even at the level of genotype can significantly alter the surrounding soil viral community. An auxiliary metabolic gene associated with glycoside hydrolase (GH5) degradation was identified in one viral metagenome-assembled genome (vOTU) identified in the B73 rhizobiome infecting Propionibacteriaceae (Actinobacteriota) further demonstrating the viral contribution in metabolic potential for carbohydrate degradation and carbon cycling in the rhizosphere. This variation demonstrates the potential of plant genotype to contribute to microbial and viral heterogeneity in soil systems and harbors genes capable of contributing to carbon cycling in the rhizosphere.

Genomic Analysis and Taxonomic Characterization of Seven Bacteriophage Genomes Metagenomic-Assembled from the Dishui Lake

Viruses in aquatic ecosystems exhibit remarkable abundance and diversity. However, scattered studies have been conducted to mine uncultured viruses and identify them taxonomically in lake water. Here, whole genomes (29-173 kbp) of seven uncultured dsDNA bacteriophages were discovered in Dishui Lake, the largest artificial lake in Shanghai. We analyzed their genomic signatures and found a series of viral auxiliary metabolic genes closely associated with protein synthesis and host metabolism. Dishui Lake phages shared more genes with uncultivated environmental viruses than with reference viruses based on the gene-sharing network classification. Phylogeny of proteomes and comparative genomics delineated three new genera within two known viral families of Kyanoviridae and Autographiviridae, and four new families in Caudoviricetes for these seven novel phages. Their potential hosts appeared to be from the dominant bacterial phyla in Dishui Lake. Altogether, our study provides initial insights into the composition and diversity of bacteriophage communities in Dishui Lake, contributing valuable knowledge to the ongoing research on the roles played by viruses in freshwater ecosystems.

ViWrap: A modular pipeline to identify, bin, classify, and predict viral-host relationships for viruses from metagenomes

Viruses are increasingly being recognized as important components of human and environmental microbiomes. However, viruses in microbiomes remain difficult to study because of the difficulty in culturing them and the lack of sufficient model systems. As a result, computational methods for identifying and analyzing uncultivated viral genomes from metagenomes have attracted significant attention. Such bioinformatics approaches facilitate the screening of viruses from enormous sequencing datasets originating from various environments. Though many tools and databases have been developed for advancing the study of viruses from metagenomes, there is a lack of integrated tools enabling a comprehensive workflow and analyses platform encompassing all the diverse segments of virus studies. Here, we developed ViWrap, a modular pipeline written in Python. ViWrap combines the power of multiple tools into a single platform to enable various steps of virus analysis, including identification, annotation, genome binning, species- and genus-level clustering, assignment of taxonomy, prediction of hosts, characterization of genome quality, comprehensive summaries, and intuitive visualization of results. Overall, ViWrap enables a standardized and reproducible pipeline for both extensive and stringent characterization of viruses from metagenomes, viromes, and microbial genomes. Our approach has flexibility in using various options for diverse applications and scenarios, and its modular structure can be easily amended with additional functions as necessary. ViWrap is designed to be easily and widely used to study viruses in human and environmental systems. ViWrap is publicly available via GitHub (https://github.com/AnantharamanLab/ViWrap). A detailed description of the software, its usage, and interpretation of results can be found on the website.

A Computational Biology Study on the Structure and Dynamics Determinants of Thermal Stability of the Chitosanase from Aspergillus fumigatus

Environmentally friendly and efficient biodegradation with chitosanase for degrading chitosan to oligosaccharide has been gaining more importance. Here, we studied a chitosanase from Aspergillus fumigatus with potential for production, but does not have the ideal thermal stability. The structure predicted by the Alphafold2 model, especially the binding site and two catalytic residues, has been found to have a high similarity with the experimental structure of the chitosanase V-CSN from the same family. The effects of temperature on structure and function were studied by dynamic simulation and the results showed that the binding site had high flexibility. After heating up from 300 K to 350 K, the RMSD and RMSF of the binding site increased significantly, in particular, the downward shift of loop6 closed the binding site, resulting in the spatial hindrance of binding. The time proportions of important hydrogen bonds at the binding site decreased sharply, indicating that serious disruption of hydrogen bonds should be the main interaction factor for conformational changes. The residues contributing energetically to binding were also revealed to be in the highly flexible region, which inevitably leads to the decrease in the activity stability at high temperature. These findings provide directions for the modification of thermal stability and perspectives on the research of proteins without experimental structures.

ViWrap: A modular pipeline to identify, bin, classify, and predict viral-host relationships for viruses from metagenomes

Viruses are increasingly being recognized as important components of human and environmental microbiomes. However, viruses in microbiomes remain difficult to study because of difficulty in culturing them and the lack of sufficient model systems. As a result, computational methods for identifying and analyzing uncultivated viral genomes from metagenomes have attracted significant attention. Such bioinformatics approaches facilitate screening of viruses from enormous sequencing datasets originating from various environments. Though many tools and databases have been developed for advancing the study of viruses from metagenomes, there is a lack of integrated tools enabling a comprehensive workflow and analyses platform encompassing all the diverse segments of virus studies. Here, we developed ViWrap, a modular pipeline written in Python. ViWrap combines the power of multiple tools into a single platform to enable various steps of virus analysis including identification, annotation, genome binning, species- and genus-level clustering, assignment of taxonomy, prediction of hosts, characterization of genome quality, comprehensive summaries, and intuitive visualization of results. Overall, ViWrap enables a standardized and reproducible pipeline for both extensive and stringent characterization of viruses from metagenomes, viromes, and microbial genomes. Our approach has flexibility in using various options for diverse applications and scenarios, and its modular structure can be easily amended with additional functions as necessary. ViWrap is designed to be easily and widely used to study viruses in human and environmental systems. ViWrap is publicly available via GitHub (https://github.com/AnantharamanLab/ViWrap). A detailed description of the software, its usage, and interpretation of results can be found on the website.