A metagenomic survey of soil microbial communities along a rehabilitation chronosequence after iron ore mining

Dissecting the ecological risks of sulfadiazine degradation intermediates under different advanced oxidation systems: From toxicity to the fate of antibiotic resistance genes

The incomplete degradation of antibiotics in water can produce intermediates that carry environmental risks and thus warrant concerns. In this study, the degradation of high concentrations of antibiotic sulfadiazine (SDZ) by advanced oxidation processes that leverage different reactive oxide species was systematically evaluated in terms of the influence of different degradation intermediates on the propagation of antibiotic resistance genes (ARGs). The ozone, persulfate, and photocatalytic oxidation systems for SDZ degradation are dominated by ozone, direct electron transfer, and singlet oxygen, hole, and superoxide radicals, respectively. These processes produce 15 intermediates via six degradation pathways. Notably, it was determined that three specific intermediates produced by the ozone and persulfate systems were more toxic than SDZ. In contrast, the photocatalytic system did not produce any intermediates with toxicity exceeding that of SDZ. Microcosm experiments combined with metagenomics confirmed significant changes in microbiota community structure after treatment with SDZ and its intermediates, including significant changes in the abundance of Flavobacterium, Dungenella, Archangium, and Comamonas. This treatment also led to the emergence of sulfonamide ARGs. The total abundance of sulfonamide ARGs was found to be positively correlated with residual SDZ concentration, with the lowest total abundance observed in the photocatalytic system. Additionally, the correlation analysis unveiled microbiota carrying sulfonamide ARGs.

The role of plants in ironstone evolution: iron and aluminium cycling in the rhizosphere

The Carajás plateaus in Brazil host endemic epilithic vegetation ("campo rupestre") on top of ironstone duricrusts, known as canga. This capping rock is primarily composed of iron(III) oxide minerals and forms a physically resistant horizon. Field observations reveal an intimate interaction between canga's surface and two native sedges (Rhynchospora barbata and Bulbostylis cangae). These observations suggest that certain plants contribute to the biogeochemical cycling of iron. Iron dissolution features at the root-rock interface were characterised using synchrotron-based techniques, Raman spectroscopy and scanning electron microscopy. These microscale characterisations indicate that iron is preferentially leached in the rhizosphere, enriching the comparatively insoluble aluminium around root channels. Oxalic acid and other exudates were detected in active root channels, signifying ligand-controlled iron oxide dissolution, likely driven by the plants' requirements for goethite-associated nutrients such as phosphorus. The excess iron not uptaken by the plant can reprecipitate in and around roots, line root channels and cement detrital fragments in the soil crust at the base of the plants. The reprecipitation of iron is significant as it provides a continuously forming cement, which makes canga horizons a 'self-healing' cover and contributes to them being the world's most stable continuously exposed land surfaces. Aluminium hydroxide precipitates ("gibbsite cutans") were also detected, coating some of the root cavities, often in alternating layers with goethite. This alternating pattern may correspond with oscillating oxygen concentrations in the rhizosphere. Microbial lineages known to contain iron-reducing bacteria were identified in the sedge rhizospheric microbiome and likely contribute to the reductive dissolution of iron(III) oxides within canga. Drying or percolation of oxygenated water to these anaerobic niches have led to iron mineralisation of biofilms, detected in many root channels. This study sheds light on plants' direct and indirect involvement in canga evolution, with possible implications for revegetation and surface restoration of iron mine sites.

Genetic diversity of Actinidia spp. shapes the oomycete pattern associated with Kiwifruit Vine Decline Syndrome (KVDS)

Kiwifruit Vine Decline Syndrome (KVDS) is an important soil-borne disease for the Italian kiwifruit industry, causing €300,000 in economic losses in 2020 alone. So far, the organisms recognized as involved in the aetiology of KVDS mainly belong to the Oomycota. As no effective management strategies exist, a promising approach to overcoming KVDS is the use of resistant species as rootstocks or for inclusion in breeding programs. Several Actinidia genotypes showing different level of resistance to KVDS were grown in disease-promoting soils. A metabarcoding approach was set up to identify KVDS-associated oomycetes and investigate whether the main species involved may vary according to plant genotype. Our results clearly showed significant differences between the genotypes in terms of oomycetes present in both plant rhizosphere and endosphere, which were strongly correlated with the symptoms displayed. We found out that the resistance of Actinidia macrosperma to KVDS is related to its ability to shape the pathobiome, particularly as far as the endosphere is concerned. In our conditions, Phytophthora sp. was predominantly found in sensitive genotypes, whilst Globisporangium intermedium was mainly detected in asymptomatic plants, suggesting that the latter species could compete with the recruitment of Phytophthora sp. in plants with different levels of resistance, consequently, explaining the onset of symptoms and the resistance condition.

Acquiring Iron-Reducing Enrichment Cultures: Environments, Methods and Quality Assessments

Lateritic duricrusts cover iron ore deposits and form spatially restricted, unique canga ecosystems endangered by mining. Iron cycling, i.e., the dissolution and subsequent precipitation of iron, is able to restitute canga duricrusts, generating new habitats for endangered biota in post-mining landscapes. As iron-reducing bacteria can accelerate this iron cycling, we aim to retrieve microbial enrichment cultures suitable to mediate the large-scale restoration of cangas. For that, we collected water and sediment samples from the Carajás National Forest and cultivated the iron-reducing microorganisms therein using a specific medium. We measured the potential to reduce iron using ferrozine assays, growth rate and metabolic activity. Six out of seven enrichment cultures effectively reduced iron, showing that different environments harbor iron-reducing bacteria. The most promising enrichment cultures were obtained from environments with repeated flooding and drying cycles, i.e., periodically inundated grasslands and a plateau of an iron mining waste pile characterized by frequent soaking. Selected enrichment cultures contained iron-reducing and fermenting bacteria, such as Serratia and Enterobacter. We found higher iron-reducing potential in enrichment cultures with a higher cell density and microorganism diversity. The obtained enrichment cultures should be tested for canga restoration to generate benefits for biodiversity and contribute to more sustainable iron mining in the region.

synDNA-a Synthetic DNA Spike-in Method for Absolute Quantification of Shotgun Metagenomic Sequencing

Microbiome studies have the common goal of determining which microbial taxa are present, respond to specific conditions, or promote phenotypic changes in the host. Most of these studies rely on relative abundance measurements to drive conclusions. Inherent limitations of relative values are the inability to determine whether an individual taxon is more or less abundant and the magnitude of this change between the two samples. These limitations can be overcome by using absolute abundance quantifications, which can allow for a more complete understanding of community dynamics by measuring variations in total microbial loads. Obtaining absolute abundance measurements is still technically challenging. Here, we developed synthetic DNA (synDNA) spike-ins that enable precise and cost-effective absolute quantification of microbiome data by adding defined amounts of synDNAs to the samples. We designed 10 synDNAs with the following features: 2,000-bp length, variable GC content (26, 36, 46, 56, or 66% GC), and negligible identity to sequences found in the NCBI database. Dilution pools were generated by mixing the 10 synDNAs at different concentrations. Shotgun metagenomic sequencing showed that the pools of synDNAs with different percentages of GC efficiently reproduced the serial dilution, showing high correlation (r = 0.96; R² ≥ 0.94) and significance (P < 0.01). Furthermore, we demonstrated that the synDNAs can be used as DNA spike-ins to generate linear models and predict with high accuracy the absolute number of bacterial cells in complex microbial communities. IMPORTANCE The synDNAs designed in this study enable accurate and reproducible measurements of absolute amount and fold changes of bacterial species in complex microbial communities. The method proposed here is versatile and promising as it can be applied to bacterial communities or genomic features like genes and operons, in addition to being easily adaptable by other research groups at a low cost. We also made the synDNAs' sequences and the plasmids available to encourage future application of the proposed method in the study of microbial communities.

De novo identification of microbial contaminants in low microbial biomass microbiomes with Squeegee

Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low-biomass environments. Contamination from DNA extraction kits or sampling lab environments leaves taxonomic "bread crumbs" across multiple distinct sample types. Here we describe Squeegee, a de novo contamination detection tool that is based upon this principle, allowing the detection of microbial contaminants when negative controls are unavailable. On the low-biomass samples, we compare Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers putative contaminants. We analyze samples of varying biomass from the Human Microbiome Project and identify likely, previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision and thus represents a computational approach for contaminant detection when negative controls are unavailable.

Controversies and hidden risks in biodiversity offsets in critically threatened Canga (ironstone) ecosystems in Brazil

Canga, or ironstone, ecosystems are hotspots of old-growth plant diversity and highly specialized cave invertebrates. These ancient metalliferous habitats are amongst the most threatened ecosystems because of the destruction caused by large-scale iron ore mining. International debate on biodiversity offsets is increasing because these mechanisms are seen as tools for potentially balancing economic development with conservation biodiversity. Leading mining companies worldwide, including some of the largest iron ore producers in Brazil, are signatories to offset principles and best practices that aim to achieve no net loss of habitats, species or ecosystem functions. We aimed to analyse whether Brazilian legal requirements for biodiversity offsets result in the achievement of conservation outcomes or in elevated threat of extinction in canga ecosystems. We evaluated technical reports that support decision-making related to environmental licensing for iron ore mining and specific offset proposals linked to the Atlantic Forest Act. We found a relevant net loss in canga ecosystems and observed shortcomings related to the equivalency and transparency of offset principles. These deficiencies are mainly related to lax norms and regulations and the absence of an integrated database for accessing information on environmental licensing processes. We argue that both policy flaws and low engagement by the Brazilian mining industry in implementing offset principles have increased the threat of extinction in canga ecosystems.

Living Fungi in an Opencast Limestone Mine: Who Are They and What Can They Do?

Opencast limestone mines or limestone quarries are considered challenging ecosystems for soil fungi as they are highly degraded land with specific conditions, including high temperature, prolonged sunlight exposure, and a lack of organic matter, moisture, and nutrients in soil. In such ecosystems, certain fungi can survive and have a crucial function in maintaining soil ecosystem functions. Unfortunately, we know very little about taxonomic diversity, potential functions, and the ecology of such fungi, especially for a limestone quarry in a tropical region. Here, we characterized and compared the living soil fungal communities in an opencast limestone mine, including mining site and its associated rehabilitation site (9 months post-rehabilitation), with the soil fungal community in a reference forest, using the amplicon sequencing of enrichment culture. Our results showed that living fungal richness in the quarry areas was significantly lower than that in the reference forest, and their community compositions were also significantly different. Living fungi in the mining sites mostly comprised of Ascomycota (Eurotiomycetes and Sordariomycetes) with strongly declined abundance or absence of Basidiomycota and Mucoromycota. After nine months of rehabilitation, certain taxa were introduced, such as Hypoxylon spp. and Phellinus noxius, though this change did not significantly differentiate fungal community composition between the mining and rehabilitation plots. The majority of fungi in these plots are classified as saprotrophs, which potentially produce all fifteen soil enzymes used as soil health indicators. Network analysis, which was analyzed to show insight into complex structures of living fungal community in the limestone quarry, showed a clear modular structure that was significantly impacted by different soil properties. Furthermore, this study suggests potential taxa that could be useful for future rehabilitation.

Using AnnoTree to Get More Assignments, Faster, in DIAMOND+MEGAN Microbiome Analysis

In microbiome analysis, one main approach is to align metagenomic sequencing reads against a protein reference database, such as NCBI-nr, and then to perform taxonomic and functional binning based on the alignments. This approach is embodied, for example, in the standard DIAMOND+MEGAN analysis pipeline, which first aligns reads against NCBI-nr using DIAMOND and then performs taxonomic and functional binning using MEGAN. Here, we propose the use of the AnnoTree protein database, rather than NCBI-nr, in such alignment-based analyses to determine the prokaryotic content of metagenomic samples. We demonstrate a 2-fold speedup over the usage of the prokaryotic part of NCBI-nr and increased assignment rates, in particular assigning twice as many reads to KEGG. In addition to binning to the NCBI taxonomy, MEGAN now also bins to the GTDB taxonomy.

IMPORTANCE The NCBI-nr database is not explicitly designed for the purpose of microbiome analysis, and its increasing size makes its unwieldy and computationally expensive for this purpose. The AnnoTree protein database is only one-quarter the size of the full NCBI-nr database and is explicitly designed for metagenomic analysis, so it should be supported by alignment-based pipelines.

Non-Specific Interactions of Rhizospheric Microbial Communities Support the Establishment of Mimosa acutistipula var. ferrea in an Amazon Rehabilitating Mineland

Mimosa acutistipula var. ferrea (Fabaceae) is endemic to ferruginous tropical rocky outcrops in the eastern Amazon, also known as canga. Canga are often associated with mining activities and are the target of protection and rehabilitation projects. M. acutistipula stands out in this biodiversity hotspot with high growth rates, even in rehabilitating minelands (RMs). However, little is known about the diversity of soil microorganisms interacting with M. acutistipula in canga and RMs. This study analyzed the rhizosphere-associated bacterial and fungal microbial communities associated with M. acutistipula growing in an RM and a native shrub canga. The fungal phylum Ascomycota was the dominant taxa identified in the rhizosphere of the canga (RA: 98.1) and RM (RA: 93.1). The bacterial phyla Proteobacteria (RA: 54.3) and Acidobacteria (RA: 56.2) were the dominant taxa identified in the rhizosphere in the canga and RM, respectively. Beneficial genera such as Bradyrhizobium, Rhodoplanes, and Paraconiothyrium were identified in the rhizosphere of M. acutistipula in both areas. However, the analyses showed that the fungal and bacterial diversity differed between the rhizosphere of the canga and RM, and that the microbial taxa adapted to the canga (i.e., Rasamsonia, Scytalidium, Roseiarcus, and Rhodomicrobium) were lacking in the RM. This influences the microbe-mediated soil processes, affecting long-term rehabilitation success. The results showed that M. acutistipula established non-specific interactions with soil microorganisms, including beneficial taxa such as nitrogen-fixing bacteria, mycorrhizal fungi, and other beneficial endophytes, well known for their importance in plant adaptation and survival. High levels of microbe association and a plant’s ability to recruit a wide range of soil microorganisms help to explain M. acutistipula’s success in rehabilitating minelands.

Exploring the Diversity and Aromatic Hydrocarbon Degrading Potential of Epiphytic Fungi on Hornbeams from Chronically Polluted Areas

Plants can ‘catch’ and mitigate airborne pollutants and are assisted by fungi inhabiting their leaves. The structure and function of the fungal communities inhabiting the phyllosphere of hornbeam trees growing in two chronically polluted areas, the oilfield of Bóbrka and the city center of Warsaw, were compared to the ones growing in one nature reserve, the Białowieża National Park. Fungi were isolated and characterized both phylogenetically and functionally for their potential role in air pollution mitigation. Both culture-dependent (e.g., enzyme assays and tolerance tests) and culture-independent methods (e.g., ITS and shotgun sequencings) were used. Furthermore, the degradation potential of the fungi was assessed by gas chromatography mass spectrometry (GC-MS). Shotgun sequencing showed that the phyllosphere fungal communities were dominated by fungi belonging to the phylum Ascomycota. Aureobasidium was the only genus detected at the three locations with a relative abundance ≥1.0%. Among the cultivated epiphytic fungi from Bóbrka, Fusarium sporotrichioides AT11, Phoma herbarum AT15, and Lophiostoma sp. AT37 showed in vitro aromatic hydrocarbon degradation potential with laccase activities of 1.24, 3.62, and 7.2 μU L⁻¹, respectively, and peroxidase enzymes with activities of 3.46, 2.28, and 7.49 μU L⁻¹, respectively. Furthermore, Fusarium sporotrichioides AT11 and Phoma herbarum AT15 tolerated exposure to airborne naphthalene and benzene. Lophiostoma sp. AT37 was the most tolerant to exposure to these pollutants, in line with being the best potential aromatic hydrocarbon degrader isolated in this study.

Understanding the metabolome and metagenome as extended phenotypes: The next frontier in macroalgae domestication and improvement

"Omics" techniques (including genomics, transcriptomics, metabolomics, proteomics, and metagenomics) have been employed with huge success in the improvement of agricultural crops. As marine aquaculture of macroalgae expands globally, biologists are working to domesticate species of macroalgae by applying these techniques tested in agriculture to wild macroalgae species. Metabolomics has revealed metabolites and pathways that influence agriculturally relevant traits in crops, allowing for informed crop crossing schemes and genomic improvement strategies that would be pivotal to inform selection on macroalgae for domestication. Advances in metagenomics have improved understanding of host-symbiont interactions and the potential for microbial organisms to improve crop outcomes. There is much room in the field of macroalgal biology for further research toward improvement of macroalgae cultivars in aquaculture using metabolomic and metagenomic analyses. To this end, this review discusses the application and necessary expansion of the omics tool kit for macroalgae domestication as we move to enhance seaweed farming worldwide.

Emerging priorities for microbial metagenome research

Overwhelming anthropogenic activities lead to deterioration of natural resources and the environment. The microorganisms are considered desirable, due to their suitability for easy genetic manipulation and handling. With the aid of modern biotechnological techniques, the culturable microorganisms have been widely exploited for the benefit of mankind. Metagenomics, a powerful tool to access the abundant biodiversity of the environmental samples including the unculturable microbes, to determine microbial diversity and population structure, their ecological roles and expose novel genes of interest. This review focuses on the microbial adaptations to the adverse environmental conditions, metagenomic techniques employed towards microbial biotechnology. Metagenomic approach helps to understand microbial ecology and to identify useful microbial derivatives like antibiotics, toxins, and enzymes with diverse and enhanced function. It also summarizes the application of metagenomics in clinical diagnosis, improving microbial ecology, therapeutics, xenobiotic degradation and impact on agricultural crops.

Enzymatic Cleavage of 3'-Esterified Nucleotides Enables a Long, Continuous DNA Synthesis

The reversible dye-terminator (RDT)-based DNA sequencing-by-synthesis (SBS) chemistry has driven the advancement of the next-generation sequencing technologies for the past two decades. The RDT-based SBS chemistry relies on the DNA polymerase reaction to incorporate the RDT nucleotide (NT) for extracting DNA sequence information. The main drawback of this chemistry is the "DNA scar" issue since the removal of dye molecule from the RDT-NT after each sequencing reaction cycle leaves an extra chemical residue in the newly synthesized DNA. To circumvent this problem, we designed a novel class of reversible (2-aminoethoxy)-3-propionyl (Aep)-dNTPs by esterifying the 3'-hydroxyl group (3'-OH) of deoxyribonucleoside triphosphate (dNTP) and examined the NT-incorporation activities by A-family DNA polymerases. Using the large fragment of both Bacillus stearothermophilus (BF) and E. coli DNA polymerase I (KF) as model enzymes, we further showed that both proteins efficiently and faithfully incorporated the 3'-Aep-dNMP. Additionally, we analyzed the post-incorporation product of N + 1 primer and confirmed that the 3'-protecting group of 3'-Aep-dNMP was converted back to a normal 3'-OH after it was incorporated into the growing DNA chain by BF. By applying all four 3'-Aep-dNTPs and BF for an in vitro DNA synthesis reaction, we demonstrated that the enzyme-mediated deprotection of inserted 3'-Aep-dNMP permits a long, continuous, and scar-free DNA synthesis.

Integrating environmental variables by multivariate ordination enables the reliable estimation of mineland rehabilitation status

Despite the wide variety of variables commonly employed to measure the success of rehabilitation, the assessment and subsequent definition of indicators of environmental rehabilitation status are not simple tasks. The main challenges are comparing rehabilitated sites with target ecosystems as well as integrating individual environmental and eventually collinear variables into a single tractable measure for the state of a system before effective indicators that track rehabilitation may be modeled. Furthermore, a consensus is lacking regarding which and how many variables need to be surveyed for a reliable estimation of rehabilitation status. Here, we propose a multivariate ordination to integrate variables related to ecological processes, vegetation structure, and community diversity into a single estimation of rehabilitation status. As a case, we employed a curated set of 32 environmental variables retrieved from nonrevegetated, rehabilitating and reference sites associated with iron ore mines from the Urucum Massif, Mato Grosso do Sul, Brazil. By integrating this set of environmental variables into a single estimation of rehabilitation status, the proposed multivariate approach is straightforward and able to adequately address collinearity among variables. The proposed methodology allows for the identification of biases towards single variables, surveys or analyses, which is necessary to rank environmental variables regarding their importance to the assessment. Furthermore, we show that bootstrapping permitted the detection of the minimum number of environmental variables necessary to achieve reliable estimations of the rehabilitation status. Finally, we show that the proposed variable integration enables the definition of case-specific environmental indicators for more rapid assessments of mineland rehabilitation. Thus, the proposed multivariate ordination represents a powerful tool to facilitate the diagnosis of rehabilitating sites worldwide provided that sufficient environmental variables related to ecological processes, diversity and vegetation structure are gathered from nonrehabilitated, rehabilitating and reference study sites. By identifying deviations from predicted rehabilitation trajectories and providing assessments for environmental agencies, this proposed multivariate ordination increases the effectiveness of (mineland) rehabilitation.