Identification of sulfamethazine degraders in swine farm-impacted river and farmland: A comparative study of aerobic and anaerobic environments

Sulfonamides (SAs) are extensively used antibiotics in the prevention and treatment of animal diseases, leading to significant SAs pollution in surrounding environments. Microbial degradation has been proposed as a crucial mechanism for removing SAs, but the taxonomic identification of microbial functional guilds responsible for SAs degradation in nature remain largely unexplored. Here, we employed 13C-sulfamethazine (SMZ)-based DNA-stable isotope probing (SIP) and metagenomic sequencing to investigate SMZ degraders in three distinct swine farm wastewater-receiving environments within an agricultural ecosystem. These environments include the aerobic riparian wetland soil, agricultural soil, and anaerobic river sediment. SMZ mineralization activities exhibited significant variation, with the highest rate observed in aerobic riparian wetland soil. SMZ had a substantial impact on the microbial community compositions across all samples. DNA-SIP analysis demonstrated that Thiobacillus, Auicella, Sphingomonas, and Rhodobacter were dominant active SMZ degraders in the wetland soil, whereas Ellin6067, Ilumatobacter, Dongia, and Steroidobacter predominated in the agricultural soil. The genus MND1 and family Vicinamibacteraceae were identified as SMZ degrader in both soils. In contrast, anaerobic SMZ degradation in the river sediment was mainly performed by genera Microvirga, Flavobacterium, Dechlorobacter, Atopostipes, and families Nocardioidaceae, Micrococcaceae, Anaerolineaceae. Metagenomic analysis of 13C-DNA identified key SAs degradation genes (sadA and sadC), and various of dioxygenases, and aromatic hydrocarbon degradation-related functional genes, indicating their involvement in degradation of SMZ and its intermediate products. These findings highlight the variations of indigenous SAs oxidizers in complex natural habitats and emphasize the consideration of applying these naturally active degraders in future antibiotic bioremediation.

DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms

Stable-isotope probing (SIP) enables researchers to target active populations within complex microbial communities, which is achieved by providing growth substrates enriched in heavy isotopes, usually in the form of ¹³C, ¹⁸O, or ¹⁵N. After growth on the substrate and subsequent extraction of microbial biomarkers, typically nucleic acids or proteins, the SIP technique is used for the recovery and analysis of isotope-labelled biomarkers from active microbial populations. In the years following the initial development of DNA- and RNA-based SIP, it was common practice to characterize labelled populations by targeted gene analysis. Such approaches usually involved fingerprint-based analyses or sequencing clone libraries containing 16S rRNA genes or functional marker gene amplicons. Although molecular fingerprinting remains a valuable approach for rapid confirmation of isotope labelling, recent advances in sequencing technology mean that it is possible to obtain affordable and comprehensive amplicon profiles, or even metagenomes and metatranscriptomes from SIP experiments. Not only can the abundance of microbial groups be inferred from metagenomes, but researchers can bin, assemble, and explore individual genomes to build hypotheses about the metabolic capabilities of labelled microorganisms. Analysis of labelled mRNA is a more recent advance that can provide independent metatranscriptome-based analysis of active microorganisms. The power of metatranscriptomics is that mRNA abundance often correlates closely with the corresponding activity of encoded enzymes, thus providing insight into microbial metabolism at the time of sampling. Together, these advances have improved the sensitivity of SIP methods and allowed using labelled substrates at environmentally relevant concentrations. Particularly as methods improve and costs continue to drop, we expect that the integration of SIP with multiple omics-based methods will become prevalent components of microbial ecology studies, leading to further breakthroughs in our understanding of novel microbial populations and elucidation of the metabolic function of complex microbial communities. In this chapter, we provide protocols for obtaining labelled DNA, RNA, and proteins that can be used for downstream omics-based analyses.

HT-SIP: a semi-automated stable isotope probing pipeline identifies cross-kingdom interactions in the hyphosphere of arbuscular mycorrhizal fungi

BACKGROUND

Linking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive for this goal, Stable-isotope probing-SIP-remains among the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, actively growing microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated, high-throughput SIP (HT-SIP) pipeline to support well-replicated, temporally resolved amplicon and metagenomics experiments. We applied this pipeline to a soil microhabitat with significant ecological importance-the hyphosphere zone surrounding arbuscular mycorrhizal fungal (AMF) hyphae. AMF form symbiotic relationships with most plant species and play key roles in terrestrial nutrient and carbon cycling.

RESULTS

Our HT-SIP pipeline for fractionation, cleanup, and nucleic acid quantification of density gradients requires one-sixth of the hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We applied HT-SIP to ¹³C-AMF hyphosphere DNA from a ¹³CO₂ plant labeling study and created metagenome-assembled genomes (MAGs) using high-resolution SIP metagenomics (14 metagenomes per gradient). SIP confirmed the AMF Rhizophagus intraradices and associated MAGs were highly enriched (10-33 atom% ¹³C), even though the soils' overall enrichment was low (1.8 atom% ¹³C). We assembled 212 ¹³C-hyphosphere MAGs; the hyphosphere taxa that assimilated the most AMF-derived ¹³C were from the phyla Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia-oxidizing archaeon genus Nitrososphaera.

CONCLUSIONS

Our semi-automated HT-SIP approach decreases operator time and improves reproducibility by targeting the most labor-intensive steps of SIP-fraction collection and cleanup. We illustrate this approach in a unique and understudied soil microhabitat-generating MAGs of actively growing microbes living in the AMF hyphosphere (without plant roots). The MAGs' phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling. Video Abstract.

The methane-driven interaction network in terrestrial methane hotspots

BACKGROUND

Biological interaction affects diverse facets of microbial life by modulating the activity, diversity, abundance, and composition of microbial communities. Aerobic methane oxidation is a community function, with emergent community traits arising from the interaction of the methane-oxidizers (methanotrophs) and non-methanotrophs. Yet little is known of the spatial and temporal organization of these interaction networks in naturally-occurring complex communities. We hypothesized that the assembled bacterial community of the interaction network in methane hotspots would converge, driven by high substrate availability that favors specific methanotrophs, and in turn influences the recruitment of non-methanotrophs. These environments would also share more co-occurring than site-specific taxa.

RESULTS

We applied stable isotope probing (SIP) using ¹³C-CH₄ coupled to a co-occurrence network analysis to probe trophic interactions in widespread methane-emitting environments, and over time. Network analysis revealed predominantly unique co-occurring taxa from different environments, indicating distinctly co-evolved communities more strongly influenced by other parameters than high methane availability. Also, results showed a narrower network topology range over time than between environments. Co-occurrence pattern points to Chthoniobacter as a relevant yet-unrecognized interacting partner particularly of the gammaproteobacterial methanotrophs, deserving future attention. In almost all instances, the networks derived from the ¹³C-CH₄ incubation exhibited a less connected and complex topology than the networks derived from the ^unlabelledC-CH₄ incubations, likely attributable to the exclusion of the inactive microbial population and spurious connections; DNA-based networks (without SIP) may thus overestimate the methane-dependent network complexity.

CONCLUSION

We demonstrated that site-specific environmental parameters more strongly shaped the co-occurrence of bacterial taxa than substrate availability. Given that members of the interactome without the capacity to oxidize methane can exert interaction-induced effects on community function, understanding the co-occurrence pattern of the methane-driven interaction network is key to elucidating community function, which goes beyond relating activity to community composition, abundances, and diversity. More generally, we provide a methodological strategy that substantiates the ecological linkages between potentially interacting microorganisms with broad applications to elucidate the role of microbial interaction in community function.

Diversity and structure of phenanthrene degrading bacterial communities associated with fungal bioremediation in petroleum contaminated soil

Fungal bioremediation is a promising technique for the cleanup of sites contaminated with polycyclic aromatic hydrocarbons (PAHs). However, due to limited understanding of the composition and dynamics of the native PAH-degrading microorganisms in contaminated sites, its application has been difficult. In the present study, DNA stable-isotope probing was performed to identify indigenous phenanthrene (PHE)-degrading bacteria and determine their diversity during the fungal bioremediation process. The results showed a total of 14 operational taxonomic units (OTUs) enriched in the heavy DNA fractions, which were related to seven genera (Sphingomonas, Sphingobacterium, Acidovorax, Massilia, Flavobacterium, Cupriavidus, Aeromicrobium, and unclassified Chitinophagaceae). Along with enhanced efficiency of PHE removal, the number and diversity of indigenous PHE-degrading bacteria in soil bioaugmented with fungi were significantly increased. Furthermore, based on the results of linear model analysis, we found that PHE degraders affiliated with the genus Sphingomonas were significantly enriched during fungal bioremediation. Moreover, fungal bioaugmentation promoted indigenous functional Proteobacteria involved in PAH degradation through co-metabolism, suggesting that PAH biodegradation was attributable to cooperative metabolism by fungi and indigenous bacteria. Our findings provide new insights into the diversity of PHE-degrading communities and support a more comprehensive view of the fungal bioremediation process.

Plant host habitat and root exudates shape fungal diversity

The rhizospheric microbiome is clearly affected by plant species and certain of their functional traits. These functional traits allow plants to adapt to their environmental conditions by acquiring or conserving nutrients, thus defining different ecological resource-use plant strategies. In the present study, we investigated whether plants with one of the two nutrient-use strategies (conservative versus exploitative) could influence fungal communities involved in soil organic matter degradation and root exudate assimilation, as well as those colonizing root tissues. We applied a DNA-based, stable-isotope probing (DNA-SIP) approach to four grass species distributed along a gradient of plant nutrient resource strategies, ranging from conservative to exploitative species, and analyzed their associated mycobiota composition using a fungal internal transcribed spacer (ITS) and Glomeromycotina 18S rRNA gene metabarcoding approach. Our results demonstrated that fungal taxa associated with exploitative and conservative plants could be separated into two general categories according to their location: generalists, which are broadly distributed among plants from each strategy and represent the core mycobiota of soil organic matter degraders, root exudate consumers in the root-adhering soil, and root colonizers; and specialists, which are locally abundant in one species and more specifically involved in soil organic matter degradation or root exudate assimilation on the root-adhering soil and the root tissues. Interestingly, for arbuscular mycorrhizal fungi analysis, all plant roots were mainly colonized by Glomus species, whereas an increased diversity of Glomeromycotina genera was observed for the exploitative plant species Dactylis glomerata.

Identification of the autotrophic denitrifying community in nitrate removal reactors by DNA-stable isotope probing

Autotrophic denitrification has attracted increasing attention for wastewater with insufficient organic carbon sources. Nevertheless, in situ identification of autotrophic denitrifying communities in reactors remains challenging. Here, a process combining micro-electrolysis and autotrophic denitrification with high nitrate removal efficiency was presented. Two batch reactors were fed organic-free nitrate influent, with H¹³CO₃^- and H¹²CO₃^- as inorganic carbon sources. DNA-based stable-isotope probing (DNA-SIP) was used to obtain molecular evidence for autotrophic denitrifying communities. The results showed that the nirS gene was strongly labeled by H¹³CO₃^-, demonstrating that the inorganic carbon source was assimilated by autotrophic denitrifiers. High-throughput sequencing and clone library analysis identified Thiobacillus-like bacteria as the most dominant autotrophic denitrifiers. However, 88% of nirS genes cloned from the ¹³C-labeled "heavy" DNA fraction showed low similarity with all culturable denitrifiers. These findings provided functional and taxonomical identification of autotrophic denitrifying communities, facilitating application of autotrophic denitrification process for wastewater treatment.

DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms

Stable-isotope probing (SIP) enables researchers to target active populations within complex microbial communities, which is achieved by providing growth substrates enriched in heavy isotopes, usually in the form of ¹³C, ¹⁸O, or ¹⁵N. After growth on the substrate and subsequent extraction of microbial biomarkers, typically nucleic acids or proteins, the SIP technique is used for the recovery and analysis of isotope-labeled biomarkers from active microbial populations. In the years following the initial development of DNA- and RNA-based SIP, it was common practice to characterize labeled populations by targeted gene analysis. Such approaches usually involved fingerprint-based analyses or sequencing of clone libraries containing 16S rRNA genes or functional marker gene amplicons. Although molecular fingerprinting remains a valuable approach for rapid confirmation of isotope labeling, recent advances in sequencing technology mean that it is possible to obtain affordable and comprehensive amplicon profiles, metagenomes, or metatranscriptomes from SIP experiments. Not only can the abundance of microbial groups be inferred from metagenomes, but researchers can bin, assemble, and explore individual genomes to build hypotheses about the metabolic capabilities of labeled microorganisms. Analysis of labeled mRNA is a more recent advance that can provide independent metatranscriptome-based analysis of active microorganisms. The power of metatranscriptomics is that mRNA abundance often correlates closely with the corresponding activity of encoded enzymes, thus providing insight into microbial metabolism at the time of sampling. Together, these advances have improved the sensitivity of SIP methods and allow the use of labeled substrates at ecologically relevant concentrations. Particularly as methods improve and costs continue to drop, we expect that the integration of SIP with multiple omics-based methods will become prevalent components of microbial ecology studies, leading to further breakthroughs in our understanding of novel microbial populations and elucidation of the metabolic function of complex microbial communities. In this chapter we provide protocols for obtaining labeled DNA, RNA, and proteins that can be used for downstream omics-based analyses.