Experimental Design and Bioinformatics Analysis for the Application of Metagenomics in Environmental Sciences and Biotechnology

In silico bioprospecting of receptors for Oligoventin: An antimicrobial peptide isolated from spider eggs of Phoneutria nigriventer

BACKGROUND

Irresponsible and wholesale use of antimicrobial agents is the principal cause of the emergence of strains of resistant microorganisms to traditional drugs. Oligoventin is a neutral peptide isolated from spider eggs of Phoneutria nigriventer, with antimicrobial activity against Gram-positive, Gram-negative, and yeast organisms. However, the molecular target and pathways of antimicrobial activity are still unknown. Thus, the aim of the present study is to prospect receptors associated with the antimicrobial activity of Oligoventin using in silico tools.

METHODS

The PharmMapper and PDB server was used to prospect targets originating from microorganisms. Additionally, the PatchDock server was utilized to perform molecular docking between Oligoventin and the targets. Subsequently, the I-TASSER server was adopted to predict the ligand site. Finally, the docking results and predicted sites were compared with literature sites of each target.

RESULTS

Over 100 potential receptors for oligoventin have been identified. Among these, enoyl-ACP reductase (Idpdb1LXC) and thymidylate synthase ThyX (Idpdb 1O28) from bacteria and N-acetylglucosamine phosphate mutase (Idpdb 2DKD) showed superior interaction with oligoventin, exhibiting colocalization between docked residues and cofactor/active sites. These enzymes play a crucial role in fatty acid and DNA biosynthesis in prokaryotes and in cell wall synthesis in yeast.

CONCLUSION

Therefore, in silico results suggest that Oligoventin can impair fatty acid DNA, cell wall synthesis, thereby reducing microbial proliferation and causing microorganism death.

Metagenomics Disentangles Differential Resistome Traits and Risks in Full-Scale Anaerobic Digestion Plants under Ambient, Mesophilic, and Thermophilic Conditions

Anaerobic digestion (AD) systems are vital for converting organic waste to green bioenergy but also serve as a non-negligible environmental reservoir for antibiotic-resistance genes (ARGs) and resistant bacteria of environmental and human health concerns. This study profiles the antibiotic resistome of 90 full-scale biogas reactors and reveals that AD microbiomes harbor at least 30 types and 1257 subtypes of ARGs, of which 16% are located on plasmids showing potential mobility. The total abundance of AD-ARGs ranges widely from 0.13 to 7.81 copies per cell and is distributed into 42-739 subtypes, significantly influenced (P < 0.05) by operational conditions like digestion temperature and substrate types. Compared with the ambient and mesophilic digesters, the thermophilic digesters harbor a significantly lower abundance and diversity as well as greatly reduced mobility and host pathogenicity levels (all P < 0.05) of ARGs, revealing that a higher digestion temperature mitigates the overall resistome risks. The comprehensive analysis of basic traits and key traits of the AD resistome is demonstrated to provide crucial quantitative and qualitative insights into the diversity, distribution pattern, and health risks of ARGs in full-scale AD systems. The revealed knowledge offers new guidance for improving environmental resistome management and developing oriented mitigation strategies to minimize the unwanted spread of clinically important antimicrobial resistance from AD systems.

Diversity and Ecological Relevance of Fumarate-Adding Enzymes in Oil Reservoir Microbial Communities

Oil reservoirs are important hydrocarbon-rich environments, where the addition of hydrocarbons to fumarate mediated by fumarate-adding enzymes (FAE) is one of the dominant mechanisms for anaerobic degradation of hydrocarbons. However, the currently available information about FaeA, the catalytic subunit of FAE, in in situ petroleum reservoirs is limited. Here, we investigated the diversity of FaeA and FaeA-harbouring microbes in oil reservoirs and compared them with marine sediments. We obtained 67 FaeA clusters and 46 FaeA-harbouring MAGs from oil reservoirs. Most FaeA sequences and all FaeA-containing microbes were endemic and unique. In oil reservoirs, FaeA sequences were affiliated with Archaeoglobus and 13 bacterial phyla. Fermentative metabolism was a common lifestyle amongst these organisms. Genomes assigned to Desulfobacterota, Caldatribacteriota and Firmicutes_B were the most diverse and prevalent, while Desulfobacterota and Chloroflexota were dominant in marine. Microbial community diversity at the phylum level was strongly related to FaeA in oil reservoirs but not in marine. This suggested that the ability of anaerobic hydrocarbon biodegradation may shape community structure in oil reservoirs. Together, this study provided systematic and comprehensive information regarding the high diversity of FaeA and FaeA-containing anaerobic hydrocarbon degraders in oil reservoirs and underlined the difference between hydrocarbon-rich environments of oil reservoirs and marine.

From Gene to Structure: Unraveling Genomic Dark Matter in Ca. Accumulibacter

"Candidatus Accumulibacter" is a unique and pivotal genus of polyphosphate-accumulating organisms prevalent in wastewater treatment plants and plays mainstay roles in the global phosphorus cycle. However, the efforts to fully understand their genetic and metabolic characteristics are largely hindered by major limitations in existing sequence-based annotation methods. Here, we reported an integrated approach combining pangenome analysis, protein structure prediction and clustering, and meta-omic characterization, to uncover genetic and metabolic traits previously unexplored for Ca. Accumulibacter. The identification of a previously overlooked pyrophosphate-fructose 6-phosphate 1-phosphotransferase gene (pfp) suggested that all Ca. Accumulibacter encoded a complete Embden-Meyerhof-Parnas pathway. A homologue of the phosphate-specific transport system accessory protein (PhoU) was suggested to be an inorganic phosphate transport (Pit) accessory protein (Pap) conferring effective and efficient phosphate transport. Additional lineage members were found to encode complete denitrification pathways. A pipeline was built, generating a pan-Ca. Accumulibacter annotation reference database, covering >200,000 proteins and their encoding genes. Benchmarking on 27 Ca. Accumulibacter genomes showed major improvement in the average annotation coverage from 51% to 82%. This pipeline is readily applicable to diverse cultured and uncultured bacteria to establish high-coverage annotation reference databases, facilitating the exploration of genomic dark matter in the bacterial domain.

Microbial community dynamics in different floc size aggregates during nitrogen removal process upgrading in a full-scale landfill leachate treatment plant

Upgrading processes to reduce biodegradable organic substance addition is crucial for treating landfill leachate with high pollutant concentrations, aiding carbon emission reduction. Aggregate size in activated sludge processes impacts pollutant removal and sludge/water separation. This study investigated microbial community succession and driving mechanisms in different floc-size aggregates during nitrogen removal progress upgrade from conventional to partial nitrification-denitrification in a full-scale landfill leachate treatment plant (LLTP) using 16S rRNA gene sequencing. The upgrade and floc sizes significantly influenced microbial diversity and composition. After upgrading, ammonia-oxidizing bacteria were enriched while nitrite-oxidizing bacteria suppressed in small flocs with homogeneity and high mass transfer efficiency. Larger flocs enriched Defluviicoccus, Thauera, and Truepera, while smaller flocs enriched Nitrosomonas, suggesting their potential as biomarkers. Multi-network analyses revealed microbial interactions. A deep learning model with convolutional neural networks predicted nitrogen removal efficiency. These findings guide optimizing LLTP processes and understanding microbial community dynamics based on floc size.

Seasonal succession, host associations, and biochemical roles of aquatic viruses in a eutrophic lake plagued by cyanobacterial blooms

Viruses are implicated to play key roles as biogeochemical mediators and ecological drivers in freshwater ecosystems. However, the dynamics of viruses and host associations throughout the seasons and during blooming periods in eutrophic freshwater ecosystems remain poorly understood. From the water microbiomes of planktonic biomass from Lake Taihu, a large eutrophic freshwater lake in China that experiences annual Microcystis-dominated harmful algal blooms (HABs), we recovered 41,997 unique viral clusters spanning a wide taxonomic range, including 15,139 Caudovirales clusters targeting bacteria and 1,044 NCLDV clusters targeting eukaryotes. The viral community exhibited clear seasonal succession, driven primarily by microbial communities (particularly Cyanobacteria and Planctomycetes) and environmental factors (mainly nutrients and temperature). Host prediction revealed that viral infection had a more distinct impact on bacteria-driven nitrogen pathways than on phosphate cycling. HAB-induced variations in microbial composition and environmental conditions affected viral strategies including viral lifestyles, host range, and virus-encoded auxiliary metabolic genes (vAMGs) distributions. Viruses infecting Proteobacteria and Actinobacteria showed an enhanced lysogenic lifestyle and a narrower host range during HAB peak in summer, while viruses infecting Bacteroidota adopted an opposite strategy. Notably, vAMGs were most abundant before the HAB outbreak in spring, compensating for bacterial metabolic processes of their hosts such as carbohydrates metabolism, photosynthesis, and phosphate regulation. The findings highlight the intricate relationships between viruses, host microbes, and the bloom-associated environment, underscoring the important biochemical roles viruses play in eutrophic freshwater ecosystems.

Microbial Metagenomics Revealed the Diversity and Distribution Characteristics of Groundwater Microorganisms in the Middle and Lower Reaches of the Yangtze River Basin

Groundwater is one of the important freshwater resources on Earth and is closely related to human activities. As a good biological vector, a more diverse repertory of antibiotic resistance genes in the water environment would have a profound impact on human medical health. Therefore, this study conducted a metagenomic sequencing analysis of water samples from groundwater monitoring points in the middle and lower reaches of the Yangtze River to characterize microbial community composition and antibiotic resistance in the groundwater environment. Our results show that different microbial communities and community composition were the driving factors in the groundwater environment, and a diversity of antibiotic resistance genes in the groundwater environment was detected. The main source of antibiotic resistance gene host was determined by correlation tests and analyses. In this study, metagenomics was used for the first time to comprehensively analyze microbial communities in groundwater systems in the middle and lower reaches of the Yangtze River basin. The data obtained from this study serve as an invaluable resource and represent the basic metagenomic characteristics of groundwater microbial communities in the middle and lower reaches of the Yangtze River basin. These findings will be useful tools and provide a basis for future research on water microbial community and quality, greatly expanding the depth and breadth of our understanding of groundwater.

In silico bioprospecting of receptors associated with the mechanism of action of Rondonin, an antifungal peptide from spider Acanthoscurria rondoniae haemolymph

Multiple drug-resistant fungal species are associated with the development of diseases. Thus, more efficient drugs for the treatment of these aetiological agents are needed. Rondonin is a peptide isolated from the haemolymph of the spider Acanthoscurria rondoniae. Previous studies have shown that this peptide has antifungal activity against Candida sp. and Trichosporon sp. strains, acting on their genetic material. However, the molecular targets involved in its biological activity have not yet been described. Bioinformatics tools were used to determine the possible targets involved in the biological activity of Rondonin. The PharmMapper server was used to search for microorganismal targets of Rondonin. The PatchDock server was used to perform the molecular docking. UCSF Chimera software was used to evaluate these intermolecular interactions. In addition, the I-TASSER server was used to predict the target ligand sites. Then, these predictions were contrasted with the sites previously described in the literature. Molecular dynamics simulations were conducted for two promising complexes identified from the docking analysis. Rondonin demonstrated consistency with the ligand sites of the following targets: outer membrane proteins F (id: 1MPF) and A (id: 1QJP), which are responsible for facilitating the passage of small molecules through the plasma membrane; the subunit of the flavoprotein fumarate reductase (id: 1D4E), which is involved in the metabolism of nitrogenous bases; and the ATP-dependent Holliday DNA helicase junction (id: 1IN4), which is associated with histone proteins that package genetic material. Additionally, the molecular dynamics results indicated the stability of the interaction of Rondonin with 1MPF and 1IN4 during a 10 ns simulation. These interactions corroborate with previous in vitro studies on Rondonin, which acts on fungal genetic material without causing plasma membrane rupture. Therefore, the bioprospecting methods used in this research were considered satisfactory since they were consistent with previous results obtained via in vitro experimentation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00224-1.

Metabolic profiling of petroleum-degrading microbial communities incubated under high-pressure conditions

While pressure is a significant characteristic of petroleum reservoirs, it is often overlooked in laboratory studies. To clarify the composition and metabolic properties of microbial communities under high-pressure conditions, we established methanogenic and sulfate-reducing enrichment cultures under high-pressure conditions using production water from the Jilin Oilfield in China. We utilized a metagenomics approach to analyze the microbial community after a 90-day incubation period. Under methanogenic conditions, Firmicutes, Deferribacteres, Ignavibacteriae, Thermotogae, and Nitrospirae, in association with the hydrogenotrophic methanogen Archaeoglobaceae and acetoclastic Methanosaeta, were highly represented. Genomes for Ca. Odinarchaeota and the hydrogen-dependent methylotrophic Ca. Methanosuratus were also recovered from the methanogenic culture. The sulfate-reducing community was dominated by Firmicutes, Thermotogae, Nitrospirae, Archaeoglobus, and several candidate taxa including Ca. Bipolaricaulota, Ca. Aminicenantes, and Candidate division WOR-3. These candidate taxa were key pantothenate producers for other community members. The study expands present knowledge of the metabolic roles of petroleum-degrading microbial communities under high-pressure conditions. Our results also indicate that microbial community interactions were shaped by syntrophic metabolism and the exchange of amino acids and cofactors among members. Furthermore, incubation under in situ pressure conditions has the potential to reveal the roles of microbial dark matter.

Anaerobic hydrolysis of recalcitrant tetramethylammonium from semiconductor wastewater: Performance and mechanisms

The treatment of tetramethylammonium hydroxide (TMAH)-bearing wastewater, generated in the electronic and semiconductor industries, raises significant concerns due to the neurotoxic, recalcitrant, and bio-inhibiting effects of TMAH. In this study, we proposed the use of an anaerobic hydrolysis bioreactor (AHBR) for TMAH removal, achieving a high removal efficiency of approximately 85%, which greatly surpassed the performance of widely-used advanced oxidation processes (AOPs). Density functional theory calculations indicated that the unexpectedly poor efficiency (5.8-8.0%) of selected AOPs can be attributed to the electrostatic repulsion between oxidants and the tightly bound electrons of TMAH. Metagenomic analyses of the AHBR revealed that Proteobacteria and Euryarchaeota played a dominant role in the transformation of TMAH through processes such as methyl transfer, methanogenesis, and acetyl-coenzyme A synthesis, utilizing methyl-tetrahydromethanopterin as a substrate. Moreover, several potential functional genes (e.g., mprF, basS, bcrB, sugE) related to TMAH resistance have been identified. Molecular docking studies between five selected proteins and tetramethylammonium further provided evidence supporting the roles of these potential functional genes. This study demonstrates the superiority of AHBR as a pretreatment technology compared to several widely-researched AOPs, paving the way for the proper design of treatment processes to abate TMAH in semiconductor wastewater.

Recent Advances in Metagenomic Approaches, Applications, and Challenge

Advances in metagenomics analysis with the advent of next-generation sequencing have extended our knowledge of microbial communities as compared to conventional techniques providing advanced approach to identify novel and uncultivable microorganisms based on their genetic information derived from a particular environment. Shotgun metagenomics involves investigating the DNA of the entire community without the requirement of PCR amplification. It provides access to study all genes present in the sample. On the other hand, amplicon sequencing targets taxonomically important marker genes, the analysis of which is restricted to previously known DNA sequences. While sequence-based metagenomics is used to analyze DNA sequences directly from the environment without the requirement of library construction and with limited identification of novel genes and products that can be complemented by functional genomics, function-based metagenomics requires fragmentation and cloning of extracted metagenome DNA in a suitable host with subsequent functional screening and sequencing clone for detection of a novel gene. Although advances were made in metagenomics, different challenges arise. This review provides insight into advances in the metagenomic approaches combined with next-generation sequencing, their recent applications highlighting the emerging ones, such as in astrobiology, forensic sciences, and SARS-CoV-2 infection diagnosis, and the challenges associated. This review further discusses the different types of metagenomics and outlines advancements in bioinformatics tools and their significance in the analysis of metagenomic datasets.

Evaluation of different 16S rRNA gene hypervariable regions and reference databases for profiling engineered microbiota structure and functional guilds in a swine wastewater treatment plant

High-throughput 16S rRNA gene amplicon sequencing technology is widely applied for environmental microbiota structure analysis to derive knowledge that informs microbiome-based surveillance and oriented bioengineering. However, it remains elusive how the selection of 16S rRNA gene hypervariable regions and reference databases affects microbiota diversity and structure profiling. This study systematically evaluated the fitness of different frequently used reference databases (i.e. SILVA 138 SSU, GTDB bact120_r207, Greengenes 13_5 and MiDAS 4.8) and primers of 16S rRNA gene in microbiota profiling of anaerobic digestion and activated sludge collected from a full-scale swine wastewater treatment plant (WWTP). The comparative results showed that MiDAS 4.8 achieved the highest levels of taxonomic diversity and species-level assignment rate. For whichever sample groups, microbiota richness captured by different primers decreased in the following order: V4 > V4-V5 > V3-V4 > V6-V8/V1-V3. Using primer-bias-free metagenomic data results as the judging standard, V4 region also best characterized microbiota structure and well represented typical functional guilds (e.g. methanogens, ammonium oxidizers and denitrifiers), while V6-V8 regions largely overestimated the archaeal methanogens (mainly Methanosarcina) by over 30 times. Therefore, MiDAS 4.8 database and V4 region are recommended for best simultaneous analysis of bacterial and archaeal community diversity and structure of the examined swine WWTP.

Metagenomic analysis of microbiological risk in bioaerosols during biowaste valorization using Musca domestica

Bioconversion using insects has gradually become a promising technology for biowaste management and protein production. However, knowledge about microbiological risk of insect related bioaerosols is sparse and conventional methods failed to provide higher resolved information of environmental microbe. In this study, a metagenomic analysis including microorganisms, antibiotic resistance genes (ARGs), virulence factor genes (VFGs), mobile gene elements (MGEs), and endotoxin distribution in bioaerosols during biowaste conversion via Musca domestica revealed that bioaerosols in Fly rearing room possess the highest ARGs abundances and MGEs diversity. Through a metagenome-assembled genomes (MAGs)-based pipeline, compelling evidence of ARGs/VFGs host assignment and ARG-VFG co-occurrence pattern were provided from metagenomic perspective. Bioaerosols in Bioconversion and Maggot separation zone were identified to own high density of MAGs carrying both ARGs and VFGs. Bacteria in Proteobacteria, Actinobacteriota, and Firmicutes phyla were predominate hosts of ARGs and VFGs. Multidrug-Motility, Multidrug-Adherence, and Beta lactam-Motility pairs were the most common ARG-VFG co-occurrence pattern in this study. Results obtained are of great significance for microbiological risk assessment during housefly biowaste conversion process.

Deduplication Improves Cost-Efficiency and Yields of De Novo Assembly and Binning of Shotgun Metagenomes in Microbiome Research

In the last decade, metagenomics has greatly revolutionized the study of microbial communities. However, the presence of artificial duplicate reads raised mainly from the preparation of metagenomic DNA sequencing libraries and their impacts on metagenomic assembly and binning have never been brought to attention. Here, we explicitly investigated the effects of duplicate reads on metagenomic assemblies and binning based on analyses of five groups of representative metagenomes with distinct microbiome complexities. Our results showed that deduplication considerably increased the binning yields (by 3.5% to 80%) for most of the metagenomic data sets examined thanks to the improved contig length and coverage profiling of metagenome-assembled contigs, whereas it slightly decreased the binning yields of metagenomes with low complexity (e.g., human gut metagenomes). Specifically, 411 versus 397, 331 versus 317, 104 versus 88, and 9 versus 5 metagenome-assembled genomes (MAGs) were recovered from MEGAHIT assemblies of bioreactor sludge, surface water, lake sediment, and forest soil metagenomes, respectively. Noticeably, deduplication significantly reduced the computational costs of the metagenomic assembly, including the elapsed time (9.0% to 29.9%) and the maximum memory requirement (4.3% to 37.1%). Collectively, we recommend the removal of duplicate reads in metagenomes with high complexity before assembly and binning analyses, for example, the forest soil metagenomes examined in this study. IMPORTANCE Duplicated reads in shotgun metagenomes are usually considered technical artifacts. Their presence in metagenomes would theoretically not only introduce bias into the quantitative analysis but also result in mistakes in the coverage profile, leading to adverse effects on or even failures in metagenomic assembly and binning, as the widely used metagenome assemblers and binners all need coverage information for graph partitioning and assembly binning, respectively. However, this issue was seldom noticed, and its impacts on downstream essential bioinformatic procedures (e.g., assembly and binning) remained unclear. In this study, we comprehensively evaluated for the first time the implications of duplicate reads for the de novo assembly and binning of real metagenomic data sets by comparing the assembly qualities, binning yields, and requirements for computational resources with and without the removal of duplicate reads. It was revealed that deduplication considerably increased the binning yields of metagenomes with high complexity and significantly reduced the computational costs, including the elapsed time and the maximum memory requirement, for most of the metagenomes studied. These results provide empirical references for more cost-efficient metagenomic analyses in microbiome research.

To assemble or not to assemble: metagenomic profiling of microbially mediated biogeochemical pathways in complex communities

High-throughput profiling of microbial functional traits involved in various biogeochemical cycling pathways using shotgun metagenomic sequencing has been routinely applied in microbial ecology and environmental science. Multiple bioinformatics data processing approaches are available, including assembly-based (single-sample assembly and multi-sample assembly) and read-based (merged reads and raw data). However, it remains not clear how these different approaches may differ in data analyses and affect result interpretation. In this study, using two typical shotgun metagenome datasets recovered from geographically distant coastal sediments, the performance of different data processing approaches was comparatively investigated from both technical and biological/ecological perspectives. Microbially mediated biogeochemical cycling pathways, including nitrogen cycling, sulfur cycling and B12 biosynthesis, were analyzed. As a result, multi-sample assembly provided the most amount of usable information for targeted functional traits, at a high cost of computational resources and running time. Single-sample assembly and read-based analysis were comparable in obtaining usable information, but the former was much more time- and resource-consuming. Critically, different approaches introduced much stronger variations in microbial profiles than biological differences. However, community-level differences between the two sampling sites could be consistently observed despite the approaches being used. In choosing an appropriate approach, researchers shall balance the trade-offs between multiple factors, including the scientific question, the amount of usable information, computational resources and time cost. This study is expected to provide valuable technical insights and guidelines for the various approaches used for metagenomic data analysis.

A Review of Basic Bioinformatic Techniques for Microbial Community Analysis in an Anaerobic Digester

Biogas production involves various types of intricate microbial populations in an anaerobic digester (AD). To understand the anaerobic digestion system better, a broad-based study must be conducted on the microbial population. Deep understanding of the complete metagenomics including microbial structure, functional gene form, similarity/differences, and relationships between metabolic pathways and product formation, could aid in optimization and enhancement of AD processes. With advancements in technologies for metagenomic sequencing, for example, next generation sequencing and high-throughput sequencing, have revolutionized the study of microbial dynamics in anaerobic digestion. This review includes a brief introduction to the basic process of metagenomics research and includes a detailed summary of the various bioinformatics approaches, viz., total investigation of data obtained from microbial communities using bioinformatics methods to expose metagenomics characterization. This includes (1) methods of DNA isolation and sequencing, (2) investigation of anaerobic microbial communities using bioinformatics techniques, (3) application of the analysis of anaerobic microbial community and biogas production, and (4) restriction and prediction of bioinformatics analysis on microbial metagenomics. The review has been concluded, giving a summarized insight into bioinformatic tools and also promoting the future prospects of integrating humungous data with artificial intelligence and neural network software.

Metagenomic analysis and nitrogen removal performance evaluation of activated sludge from a sequencing batch reactor under different salinities

The effect of salinity on the nitrogen removal performance and microbial community of activated sludge was investigated in a sequencing batch reactor. The NH₄⁺-N removal efficiency was over 95% at 0-4% salinity, indicating that the nitrification performance of activated sludge was slightly affected by lower salinity. The obvious nitrite accumulation was observed with the increment of the salinity to 5%, followed by a notable decline in the nitrogen removal performance at 6% salinity. The salinity inhibited the microbial activity, and the specific rate of nitrification and denitrification was decreased by the increasing salinity obviously. Additionally, the lower activity of superoxide dismutase and peroxidase and higher reactive oxygen species content in activated sludge might account for the deteriorative nitrogen removal performance at 6% salinity. Metagenomics analysis revealed that the genes encoding the ABC-type quaternary amine transporter in the ABC transporter pathway were abundant in the activated sludge at 2% and 4% salinity, and the higher salinity of 6% led to the loss of the genes encoding the p-type Na⁺ transporter in the ABC transporter pathway. These results indicated that the salinity could weaken the ABC transporter pathway for the balance of osmotic pressure in activated sludge. The microbial activity and nitrogen removal performance of activated sludge were decreased due to the unbalanced osmotic pressure at higher salinity.

Comammox biogeography subject to anthropogenic interferences along a high-altitude river

The recent discovery of comammox Nitrospira performing complete ammonia oxidation to nitrate has overturned the long-held dogma of two-step nitrification on Earth, yet little is known about the effect of urbanization interference on their distribution. Using gene-centric metagenomics, we provided the first blueprints about comammox community, biogeography, and environmental drivers along a high-elevation (> 2000 m) river flowing through the largest city on the vulnerable Qinghai-Tibetan Plateau. Our study confirmed a wide presence and diversity of yet-uncultured comammox clade B across wet and dry seasons, with average 3.0 and 2.0 times as abundant as clade-A amoA genes in water and sediments, respectively. Species identified from freshwater and drinking water treatment plants dominated the comammox guilds (58∼100%), suggesting this plateau river shared a similar comammox assemblage with the above habitat types. Compared with the urban area harboring more abundant canonical Nitrospira identified in wastewater (average 24%), the upstream suburban reach had a smaller human population but larger proportions of comammox in ammonia-oxidizing prokaryotes (24∼72% of abundances) and Nitrospira sublineages I/II. Higher contents of nitrate and nitrite in water, and antibiotics in water and sediments, may restrain comammox niches in nitrifiers over the urban area. Further random forest analysis revealed that lincosamides and quinolones were the most important antibiotic predictors for the niche differentiations between comammox and canonical nitrifiers in water, while macrolides for those in sediments. Finally, by incubation experiments, we demonstrated higher activity contributions of benthic comammox in the suburban area (36.2∼92.8% of potential ammonia-oxidation rates) than in the urban reach, and that the contribution variation had significant negative relations with macrolides and their major components. Overall, this study highlighted that anthropogenic activities hampered the advantage of riverine complete nitrifiers over the canonical two-step ones.

Microbial diversity and biogeochemical cycling potential in deep-sea sediments associated with seamount, trench, and cold seep ecosystems

Due to their extreme water depths and unique physicochemical conditions, deep-sea ecosystems develop uncommon microbial communities, which play a vital role in biogeochemical cycling. However, the differences in the compositions and functions of the microbial communities among these different geographic structures, such as seamounts (SM), marine trenches (MT), and cold seeps (CS), are still not fully understood. In the present study, sediments were collected from SM, MT, and CS in the Southwest Pacific Ocean, and the compositions and functions of the microbial communities were investigated by using amplicon sequencing combined with in-depth metagenomics. The results revealed that significantly higher richness levels and diversities of the microbial communities were found in SM sediments, followed by CS, and the lowest richness levels and diversities were found in MT sediments. Acinetobacter was dominant in the CS sediments and was replaced by Halomonas and Pseudomonas in the SM and MT sediments. We demonstrated that the microbes in deep-sea sediments were diverse and were functionally different (e.g., carbon, nitrogen, and sulfur cycling) from each other in the seamount, trench, and cold seep ecosystems. These results improved our understanding of the compositions, diversities and functions of microbial communities in the deep-sea environment.

Microbially mediated arsenic mobilization in the clay layer and underlying aquifer in the Hetao Basin, Inner Mongolia, China

The clay layer is a source to facilitate arsenic (As) enrichment in the aquifer. However, little is known about microbial processes in the clay layer and their roles in As mobilization in the underlying aquifer. In this study, high-throughput sequencing of full-length 16S rRNA gene and metagenomics were used to characterize the microbial composition and functional potential in a sediment borehole across the clay and sand layers in Hetao Basin, Inner Mongolia, China. Results showed the significant differences between the clay layer and underlying sand layer in the geochemistry, microbial composition and functional potential. Fermentation, Fe(III) reduction, As(V) reduction, sulfate reduction, thiosulfate disproportionation, reductive tricarboxylic acid and Wood-Ljungdahl pathway identified in sediments from the clay layer were positively correlated to the observed high levels of TOC, soluble ammonium, H₃PO₄-extractable As(III) and As(V) and HCl-extractable Fe(II). Although the microbial compositions of the clay and sand layers were different, the microbial functional potential at the interface between the clay and sand layers was similar with the characteristics of fermentation, ammonification and As(V) reduction. The similarity of microbial functional potential at the interface may be attributable to the interaction between the sand and adjacent clay layer with the fluctuation of groundwater level. These metabolic products from the microbial processes in the clay layers and interface would migrate into the underlying groundwater during groundwater overpumping, which facilitates As enrichment in groundwater.

Identification of Extracellular Key Enzyme and Intracellular Metabolic Pathway in Alginate-Degrading Consortia via an Integrated Metaproteomic/Metagenomic Analysis

Uronic acid in extracellular polymeric substances is a primary but often ignored factor related to the difficult hydrolysis of waste-activated sludge (WAS), with alginate as a typical polymer. Previously, we enriched alginate-degrading consortia (ADC) in batch reactors that can enhance methane production from WAS, but the enzymes and metabolic pathway are not well documented. In this work, two chemostats in series were operated to enrich ADC, in which 10 g/L alginate was wholly consumed. Based on it, the extracellular alginate lyase (∼130 kD, EC 4.2.2.3) in the cultures was identified by metaproteomic analysis. This enzyme offers a high specificity to convert alginate to disaccharides over other mentioned hydrolases. Genus Bacteroides (>60%) was revealed as the key bacterium for alginate conversion. A new Entner-Doudoroff pathway of alginate via 5-dehydro-4-deoxy-d-glucuronate (DDG) and 3-deoxy-d-glycerol-2,5-hexdiulosonate (DGH) as the intermediates to 2-keto-3-deoxy-gluconate (KDG) was constructed based on the metagenomic and metaproteomic analysis. In summary, this work documented the core enzymes and metabolic pathway for alginate degradation, which provides a good paradigm when analyzing the degrading mechanism of unacquainted substrates. The outcome will further contribute to the application of Bacteroides-dominated ADC on WAS methanogenesis in the future.

Adaptation mechanisms of arsenic metabolism genes and their host microorganisms in soils with different arsenic contamination levels around abandoned gold tailings

Soil around the gold tailing due to the smelting process of wastewater and solid waste can lead to metal (loids) contamination, especially arsenic (As). Soil microorganisms have gradually evolved adaptive mechanisms in the process of long-term adaptation to As contamination. However, comprehensive investigations on As metabolism genes and their host microbial communities in soil profiles with different levels under long-term As contamination are lacking. There are selected three typical soil profiles (0-100 cm) with different metal (loids) contamination levels (L-low, M-moderate and H-high) around tailings in this research. It uses a Metagenomic approach to explore the adaptation mechanisms of arsenic metabolism genes and arsenic metabolism gene host microorganisms in both horizontal and vertical dimensions. The results showed that four categories of As metabolism genes were prevalent in soil profiles at different As contamination, with As reduction genes being the most abundant, followed by As oxidation genes, then respiration genes and methylation genes. The As metabolism genes arsBCR, aioE, arsPH, arrAB increased with the increase of metal (loid) contaminants concentration. Longitudinal arsA, arrA, aioA, arsM and acr3 increased in abundance in deep soil. Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi were the dominant phylum of As metabolism gene host microorganisms. Different concentrations of metal (loid) contamination significantly affected the distribution of host As metabolism genes. Random forest prediction identified As as the most critical driver of As metabolism genes and their host microorganisms. Overall, this study provides a reference for a comprehensive investigation of the detoxification mechanisms of As metabolism microorganisms in soil profiles with different As contamination conditions, and is important for the development of As metabolism gene host microbial strains and engineering applications of microbial technologies to manage As contamination.

Risks, characteristics, and control strategies of disinfection-residual-bacteria (DRB) from the perspective of microbial community structure

The epidemic of COVID-19 has aroused people's particular attention to biosafety. A growing number of disinfection products have been consumed during this period. However, the flaw of disinfection has not received enough attention, especially in water treatment processes. While cutting down the quantity of microorganisms, disinfection processes exert a considerable selection effect on bacteria and thus reshape the microbial community structure to a great extent, causing the problem of disinfection-residual-bacteria (DRB). These systematic and profound changes could lead to the shift in regrowth potential, bio fouling potential, as well as antibiotic resistance level and might cause a series of potential risks. In this review, we collected and summarized the data from the literature in recent 10 years about the microbial community structure shifting of natural water or wastewater in full-scale treatment plants caused by disinfection. Based on these data, typical DRB with the most reporting frequency after disinfection by chlorine-containing disinfectants, ozone disinfection, and ultraviolet disinfection were identified and summarized, which were the bacteria with a relative abundance of over 5% in the residual bacteria community and the bacteria with an increasing rate of relative abundance over 100% after disinfection. Furthermore, the phylogenic relationship and potential risks of these typical DRB were also analyzed. Twelve out of fifteen typical DRB genera contain pathogenic strains, and many were reported of great secretion ability. Pseudomonas and Acinetobacter possess multiple disinfection resistance and could be considered as model bacteria in future studies of disinfection. We also discussed the growth, secretion, and antibiotic resistance characteristics of DRB, as well as possible control strategies. The DRB phenomenon is not limited to water treatment but also exists in the air and solid disinfection processes, which need more attention and more profound research, especially in the period of COVID-19.

Predicting antibiotic resistance gene abundance in activated sludge using shotgun metagenomics and machine learning

While the microbiome of activated sludge (AS) in wastewater treatment plants (WWTPs) plays a vital role in shaping the resistome, identifying the potential bacterial hosts of antibiotic resistance genes (ARGs) in WWTPs remains challenging. The objective of this study is to explore the feasibility of using a machine learning approach, random forests (RF's), to identify the strength of associations between ARGs and bacterial taxa in metagenomic datasets from the activated sludge of WWTPs. Our results show that the abundance of select ARGs can be predicted by RF's using abundant genera (Candidatus Accumulibacter, Dechloromonas, Pesudomonas, and Thauera, etc.), (opportunistic) pathogens and indicators (Bacteroides, Clostridium, and Streptococcus, etc.), and nitrifiers (Nitrosomonas and Nitrospira, etc.) as explanatory variables. The correlations between predicted and observed abundance of ARGs (erm(B), tet(O), tet(Q), etc.) ranged from medium (0.400 < R² < 0.600) to strong (R² > 0.600) when validated on testing datasets. Compared to those belonging to the other two groups, individual genera in the group of (opportunistic) pathogens and indicator bacteria had more positive functional relationships with select ARGs, suggesting genera in this group (e.g., Bacteroides, Clostridium, and Streptococcus) may be hosts of select ARGs. Furthermore, RF's with (opportunistic) pathogens and indicators as explanatory variables were used to predict the abundance of select ARGs in a full-scale WWTP successfully. Machine learning approaches such as RF's can potentially identify bacterial hosts of ARGs and reveal possible functional relationships between the ARGs and microbial community in the AS of WWTPs.

Combined whole cell wall analysis and streamlined in silico carbohydrate-active enzyme discovery to improve biocatalytic conversion of agricultural crop residues

The production of biofuels as an efficient source of renewable energy has received considerable attention due to increasing energy demands and regulatory incentives to reduce greenhouse gas emissions. Second-generation biofuel feedstocks, including agricultural crop residues generated on-farm during annual harvests, are abundant, inexpensive, and sustainable. Unlike first-generation feedstocks, which are enriched in easily fermentable carbohydrates, crop residue cell walls are highly resistant to saccharification, fermentation, and valorization. Crop residues contain recalcitrant polysaccharides, including cellulose, hemicelluloses, pectins, and lignin and lignin-carbohydrate complexes. In addition, their cell walls can vary in linkage structure and monosaccharide composition between plant sources. Characterization of total cell wall structure, including high-resolution analyses of saccharide composition, linkage, and complex structures using chromatography-based methods, nuclear magnetic resonance, -omics, and antibody glycome profiling, provides critical insight into the fine chemistry of feedstock cell walls. Furthermore, improving both the catalytic potential of microbial communities that populate biodigester reactors and the efficiency of pre-treatments used in bioethanol production may improve bioconversion rates and yields. Toward this end, knowledge and characterization of carbohydrate-active enzymes (CAZymes) involved in dynamic biomass deconstruction is pivotal. Here we overview the use of common "-omics"-based methods for the study of lignocellulose-metabolizing communities and microorganisms, as well as methods for annotation and discovery of CAZymes, and accurate prediction of CAZyme function. Emerging approaches for analysis of large datasets, including metagenome-assembled genomes, are also discussed. Using complementary glycomic and meta-omic methods to characterize agricultural residues and the microbial communities that digest them provides promising streams of research to maximize value and energy extraction from crop waste streams.

Exploring the taxonomical and functional profile of As Burgas hot spring focusing on thermostable β-galactosidases

In the present study we investigate the microbial community inhabiting As Burgas geothermal spring, located in Ourense (Galicia, Spain). The approximately 23 Gbp of Illumina sequences generated for each replicate revealed a complex microbial community dominated by Bacteria in which Proteobacteria and Aquificae were the two prevalent phyla. An association between the two most prevalent genera, Thermus and Hydrogenobacter, was suggested by the relationship of their metabolism. The high relative abundance of sequences involved in the Calvin-Benson cycle and the reductive TCA cycle unveils the dominance of an autotrophic population. Important pathways from the nitrogen and sulfur cycle are potentially taking place in As Burgas hot spring. In the assembled reads, two complete ORFs matching GH2 beta-galactosidases were found. To assess their functional characterization, the two ORFs were cloned and overexpressed in E. coli. The pTsbg enzyme had activity towards o-Nitrophenyl-β-D-galactopyranoside (ONPG) and p-Nitrophenyl-β-D-fucopyranoside, with high thermal stability and showing maximal activity at 85 °C and pH 6, nevertheless the enzyme failed to hydrolyze lactose. The other enzyme, Tsbg, was unable to hydrolyze even ONPG or lactose. This finding highlights the challenge of finding novel active enzymes based only on their sequence.

Dissipation of Sulfonamides in Soil Emphasizing Taxonomy and Function of Microbiomes by Metagenomic Analysis

Sulfonamides (SAs) are widespread in soils, and their dissipation behavior is important for their fate, risk assessment, and pollution control. In this work, we investigated the dissipation behavior of different SAs in a soil under aerobic condition, focusing on revealing the relationship between overall dissipation (without sterilization and in dark) and individual abiotic (sorption, hydrolysis)/biotic (with sterilization and in dark) factors and taxonomy/function of microbiomes. The results showed that dissipation of all SAs in the soil followed the pseudo-first-order kinetic model with dissipation time at 50% removal (DT₅₀) of 2.16-15.27 days. Based on, experimentally, abiotic/biotic processes and, theoretically, partial least-squares modeling, a relationship between overall dissipation and individual abiotic/biotic factors was developed with microbial degradation as the dominant contributor. Metagenomic analysis showed that taxonomic genera like Bradyrhizobium/Sphingomonas/Methyloferula and functions like CAZy family GT51/GH23/GT2, eggNOG category S, KEGG pathway ko02024/ko02010, and KEGG ortholog K01999/K03088 are putatively involved in SA microbial degradation in soil. Spearman correlation suggests abundant genera being multifunctional. This study provides some new insights into SA dissipation and can be applied to other antibiotics/soils in the future.

Comammox Nitrospira within the Yangtze River continuum: community, biogeography, and ecological drivers

The recent discovery of comammox Nitrospira as complete nitrifiers has fundamentally renewed perceptions of nitrogen cycling in natural and engineered systems, yet little is known about the environmental controls on these newly recognized bacteria. Based on improved phylogenetic resolution through successful assembly of ten novel genomes (71-96% completeness), we provided the first biogeographic patterns for planktonic and benthic comammox Nitrospira in the Yangtze River over a 6030 km continuum. Our study revealed the widespread distributions and relative abundance of comammox Nitrospira in this large freshwater system, constituting 30 and 46% of ammonia-oxidizing prokaryotes (AOPs) and displaying 30.4- and 17.9-fold greater abundances than canonical Nitrospira representatives in water and sediments, respectively. Comammox Nitrospira contributed more to nitrifier abundances (34-87% of AOPs) in typical oligotrophic environments with a higher pH and lower temperature, particularly in the plateau (clade B), mountain and foothill (clade A) areas of the upper reach. The dominant position of planktonic comammox Nitrospira was replaced by canonical Nitrospira sublineages I/II and ammonia-oxidizing bacteria from the plateau to downstream plain due to environmental selection, while the dissimilarity of benthic comammox Nitrospira was moderately associated with geographic distance. A substantial decrease (83%) in benthic comammox Nitrospira abundance occurred immediately downstream of the Three Gorges Dam, consistent with a similarly considerable decrease in overall sediment bacterial taxa. Together, this study highlights the previously unrecognized dominance of comammox Nitrospira in major river systems and underlines the importance of revisiting the distributions of and controls on nitrification processes within global freshwater environments.

Seasonality and Community Separation of Fungi in a Municipal Wastewater Treatment Plant

Fungi are known to play important roles in pollutant transformation in activated sludge-based wastewater treatment plants (WWTPs). However, the seasonality and distributions of fungal populations in different-sized flocs have still remained largely unknown. In this study, seasonal population dynamics and community separation of fungi in a municipal WWTP across a 1-year period were investigated. We classified all taxa into six categories based on abundances to assess their roles and contributions to the whole community. The results showed that the rare taxa (<0.01%) contributed greatly to species richness (95.27%). Conversely, although low in species diversity, abundant taxa (≥1%) accounted for the majority (89.45%) of the total relative abundance, which suggested that a few core abundant fungi existed in the activated sludge ecosystem. The abundant, conditionally rare, and rare taxa contributed 30.14%, 31.11%, and 38.75%, respectively, to temporal shifts in community structure, and their abundances responded differently to environmental variables, suggesting that these three subcommunities exhibited a large difference in environmental sensitivity. Importantly, the results revealed seasonal dynamics of the whole fungal community and the subcommunities of all the microbial taxon categories, resulting in significant differences in community structures between warm and cold seasons. Furthermore, fungal diversity and the compositions of the whole community and subcommunities differed significantly among flocs of different sizes, which underlined the size-based fungal community separation in activated sludge of WWTPs. The findings of this work improved our understanding of fungal population dynamics and community separation in WWTPs.IMPORTANCE Fungi are important contributors to the various functions of activated sludge in wastewater treatment plants (WWTPs). Unlike previous studies, this work demonstrated the seasonality of the fungal community over a longer time span while it also systematically assessed the contributions of abundant, conditionally rare, and rare taxa to the whole community. Importantly, in the present study, we considered sludge flocs of a certain size range rather than the whole sludge flocs as a community. Our results revealed significant differences in fungal community structure among different-sized flocs, which supported the idea that size-based fungal community segregation is occurring in activated sludge ecosystems. The findings provide new insights into the dynamic changes or distribution of fungi in the bioaggregates of sludge flocs in WWTPs.

Antibiotic resistome and microbial community structure during anaerobic co-digestion of food waste, paper and cardboard

Solid organic waste is a significant source of antibiotic resistance genes (ARGs) and effective treatment strategies are urgently required to limit the spread of antimicrobial resistance. Here, we studied ARG diversity and abundance as well as the relationship between antibiotic resistome and microbial community structure within a lab-scale solid-state anaerobic digester treating a mixture of food waste, paper and cardboard. A total of 10 samples from digester feed and digestion products were collected for microbial community analysis including small subunit rRNA gene sequencing, total community metagenome sequencing and high-throughput quantitative PCR. We observed a significant shift in microbial community composition and a reduction in ARG diversity and abundance after 6 weeks of digestion. ARGs were identified in all samples with multidrug resistance being the most abundant ARG type. Thirty-two per cent of ARGs detected in digester feed were located on plasmids indicating potential for horizontal gene transfer. Using metagenomic assembly and binning, we detected potential bacterial hosts of ARGs in digester feed, which included Erwinia, Bifidobacteriaceae, Lactococcus lactis and Lactobacillus. Our results indicate that the process of sequential solid-state anaerobic digestion of food waste, paper and cardboard tested herein provides a significant reduction in the relative abundance of ARGs per 16S rRNA gene.

Aggregate size-dependence of bacterial community separation in a full-scale membrane bioreactor plant

The size of bacterial aggregates can determine both nutrient removal and sludge/water separation in activated sludge processes. In this study, the bacterial community structures and network associations of different sized aggregates obtained from a full-scale membrane bioreactor plant over a one-year period were investigated. Our results showed that biodiversity of larger sized aggregates was significantly higher than that of smaller ones and that the bacterial compositions of different sized aggregates differed significantly from each other. Bacteria related to nutrient removal (e.g. denitrification, hydrolysis and fermentation) were found to be significantly more abundant in larger aggregates than smaller ones. Network analysis revealed significant difference in species-species interactions, topological roles of individual OTU and keystone populations among different sized aggregates. Moreover, the occurrence of keystone OTUs affiliated with denitrifiers (Thermomonas) in networks of large and medium aggregates may suggest that denitrification influences bacterial interactions in large and medium aggregates. Overall, our results indicate the aggregates size-dependence of bacterial community separation in activated sludge. The current findings not only can provide guidance for process design and operation optimization, but also highlight the necessity for paying more attentions to the aggregate-based community, metabolic function and gene expression of activated sludge in future studies.

Metagenomics methods for the study of plant-associated microbial communities: A review

Plant microbiota have different effects on the plant which can be beneficial or pathogenic. In this study, we concentrated on beneficial microbes associated with plants using endophytic microbes as a case study. Detailed knowledge of the microbial diversity, abundance, composition, functional genes patterns, and metabolic pathways at genome level could assist in understanding the contributions of microbial community towards plant growth and health. Recently, the study of microbial community has improved greatly with the discovery of next-generation sequencing and bioinformatics technologies. Analysis of next generation sequencing data and a proper computational method plays a key role in examining microbial metagenome. This review presents the general metagenomics and computational methods used in processing plant associated metagenomes with concentration on endophytes. This includes 1) introduction of plant-associated microbiota and the factors driving their diversity. 2) plant metagenome focusing on DNA extraction, verification and quality control. 3) metagenomics methods used in community analysis of endophytes focusing on maize plant and, 4) computational methods used in the study of endophytic microbiomes. Limitations and future prospects of metagenomics and computational methods for the analysis of plant-associated metagenome (endophytic metagenome) were also discussed with the aim of fostering its development. We conclude that there is need to adopt advanced genomic features such as k-mers of random size, which do not depend on annotation and can represent other sequence alternatives.

Characterizing community dynamics and exploring bacterial assemblages in two activated sludge systems

Bacterial communities in the activated sludge (AS) determine the wastewater treatment performance in the municipal wastewater treatment plants (WWTPs). Aiming at identifying the affecting factors and the variation patterns of the bacterial assemblages in AS, a 2-year time-series AS samples were collected from two separated WWTPs and metagenomic sequencing was conducted. Obvious seasonal shift and succession of the bacterial community were observed in both WWTPs on the genus and species levels, especially for the persistent taxa, implying that temperature was a decisive factor for maintaining bacterial assemblage patterns in long-term period. Taxa abundance distribution (TAD) concerning occurrence frequency and average abundance were found fitting for exponential formulations, and the approximately equal total abundance of persistent taxa suggested that stable and high abundance (~ 90%) of core functional bacterial groups would help to maintain wastewater treatment performance. Drastic changes of environmental factors were found causing temporally significant bacterial structure variation, while the innate correlations between bacterial species could recover the community gradually and maintain relative stability of the AS system. Delayed correlations between environmental factors and abundant (persistent or intermittent) bacterial species were observed widely, while synchronous biotic interactions were identified more frequently. Besides, bacterial species with similar functions were prone to cluster together and shared the same seasonal variation pattern, implicating that the cooperation of functional correlated taxa played the most dominant role in shaping the bacterial assemblages. Furthermore, rare bacterial groups were to be explored for removing emerging pollutants with lower concentrations. The results of this study would assist dealing with operational defect and optimize the treatment system in WWTPs.

Density-Based Separation of Microbial Functional Groups in Activated Sludge

Mechanistic understanding of how activated sludge (AS) solids density influences wastewater treatment processing is limited. Because microbial groups often generate and store intracellular inclusions during certain metabolic processes, it is hypothesized that some microorganisms, like polyphosphate-accumulating organisms (PAOs), would have higher biomass densities. The present study developed a density-based separation approach and applied it to suspended growth AS in two full-scale domestic water resource recovery facilities (WRRFs). Incorporating quantitative real-time PCR (qPCR) and fluorescence in situ hybridization (FISH) analyses, the research demonstrated the effectiveness of density-based separation in enriching key microbial functional groups, including ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB) and PAOs, by up to 90-fold in target biomass fractions. It was observed that WRRF process functionalities have significant influence on density-based enrichment, such that maximum enrichments were achieved in the sludge fraction denser than 1.036 g/cm³ for the enhanced biological phosphorus removal (EBPR) facility and in the sludge fraction lighter than 1.030 g/cm³ for the non-EBPR facility. Our results provide important information on the relationship between biomass density and enrichment of microbial functional groups in AS, contributing to future designs of enhanced biological treatment processes for improved AS settleability and performance.

Floc-size effects of the pathogenic bacteria in a membrane bioreactor plant

The size nature of sludge flocs could affect the occurrence and distribution of bacterial pathogens in wastewater treatment plants (WWTPs). In this study, the floc-size dependence of bacterial pathogens in the activated sludge of a WWTP was investigated using high-throughput metagenomic sequencing approaches. The results showed that a total of 423 pathogenic species belonging to 123 genera were identified in the three size-fractionated flocs. Also, we found that all the pathogens on the WHO's global priority pathogens list were detected in the size-fractionated flocs, with relative abundance of 0.4%, 0.3% and 0.3% for large-size, medium-size and small-size flocs, respectively, indicating the severe human and environmental health risks of activated sludge. Importantly, our results revealed that the pathogenic species showed a clear floc-size dependent distribution manner, leading to significant differences (P < 0.05) of pathogenic communities among the size-fractionated flocs. Additionally, by partitioning pathogens based on the occurrence and significant difference in abundances, we suggested the following distribution features: 1) large flocs-associated pathogens, such as Borrelia recurrentis, Actinobacillus ureae and Campylobacter gracilis; 2) medium flocs-associated pathogens, such as Mycobacterium szulgai and Ureaplasma urealyticum; and 3) small flocs-associated pathogens, such as Rickettsia akari, Staphylococcus anginosus and Helicobacter cinaedi. Overall, this study provides a comprehensive understanding of pathogens in activated sludge, which is expected to aid in assessment and management of pathogen risks.

A robust, cost-effective method for DNA, RNA and protein co-extraction from soil, other complex microbiomes and pure cultures

The soil microbiome is inherently complex with high biological diversity, and spatial heterogeneity typically occurring on the submillimetre scale. To study the microbial ecology of soils, and other microbiomes, biomolecules, that is, nucleic acids and proteins, must be efficiently and reliably co-recovered from the same biological samples. Commercial kits are currently available for the co-extraction of DNA, RNA and proteins but none has been developed for soil samples. We present a new protocol drawing on existing phenol-chloroform-based methods for nucleic acids co-extraction but incorporating targeted precipitation of proteins from the phenol phase. The protocol is cost-effective and robust, and easily implemented using reagents commonly available in laboratories. The method is estimated to be eight times cheaper than using disparate commercial kits for the isolation of DNA and/or RNA, and proteins, from soil. The method is effective, providing good quality biomolecules from a diverse range of soil types, with clay contents varying from 9.5% to 35.1%, which we successfully used for downstream, high-throughput gene sequencing and metaproteomics. Additionally, we demonstrate that the protocol can also be easily implemented for biomolecule co-extraction from other complex microbiome samples, including cattle slurry and microbial communities recovered from anaerobic bioreactors, as well as from Gram-positive and Gram-negative pure cultures.

Aquaponic Systems for Sustainable Resource Recovery: Linking Nitrogen Transformations to Microbial Communities

Aquaponics is a technology for food production (fish and vegetables/fruits) with concomitant remediation of nitrogen-rich aquaculture effluent. There is, however, a critical need to improve the nitrogen use efficiency (NUE) in aquaponics. Here, we employed quantitative polymerase chain reactions and next-generation sequencing to evaluate the bacterial communities and their links to nitrogen transformations for improving NUEs in four bench-scale plant-based floating-raft aquaponics (pak choi, lettuce, chive, and tomato) and three pH levels (7.0, 6.0, and 5.2). Low relative abundance of nitrifiers in plant roots and biofilters suggested nitrogen loss, which decreased NUE in aquaponics. Low pH level was a major factor that shifted the microbial communities and reduced the relative abundance of nitrifiers in aquaponic systems, leading to total ammonia nitrogen accumulation in recirculating water. In plant roots, the abundance of nitrite-oxidizing bacteria (e.g., Nitrospira spp.) did not decrease at low pH levels, suggesting the benefit of growing plants in aquaponics for efficient nitrification and improving NUE. These findings on microbial communities and nitrogen transformations provided complementary strategies to improve the performance of the aquaponics regarding water quality and extent of nutrient recovery from aquaculture effluent.

Bacteria That Make a Meal of Sulfonamide Antibiotics: Blind Spots and Emerging Opportunities

The release of sulfonamide antibiotics into the environment is alarming because the existence of these antibiotics in the environment may promote resistance in clinically relevant microorganisms, which is a potential threat to the effectiveness of antibiotic therapies. Controllable biodegradation processes are of particular significance for the inexpensive yet effective restoration of sulfonamide-contaminated environments. Cultivation-based techniques have already made great strides in successfully isolating bacteria with promising sulfonamide degradation abilities, but the implementation of these isolates in bioremediation has been limited by unknown microbial diversity, vast population responsiveness, and the impact of perturbations from open and complex environments. Advances in DNA sequencing technologies and metagenomic analyses are being used to complement the information derived from cultivation-based procedures. In this Review, we provide an overview of the growing understanding of isolated sulfonamide degraders and identify shortcomings of the prevalent literature in this field. In addition, we propose a technical paradigm that integrates experimental testing with metagenomic analysis to pave the way for improved understanding and exploitation of these ecologically important isolates. Overall, this Review aims to outline how metagenomic studies of isolated sulfonamide degraders are being applied for the advancement of bioremediation strategies for sulfonamide contamination.

Stable oligonucleotide-functionalized gold nanosensors for environmental biocontaminant monitoring

The global propagation of environmental biocontaminants such as antibiotic resistant pathogens and their antibiotic resistance genes (ARGs) is a public health concern that highlights the need for improved monitoring strategies. Here, we demonstrate the environmental stability and applicability of an oligonucleotide-functionalized gold nanosensor. The mecA ARG was targeted as model biocontaminant due to its presence in clinically-relevant pathogens and to its emergence as an environmental contaminant. mecA-specific nanosensors were tested for antibiotic resistance gene (ARG) detection in ARG-spiked effluent from four wastewater treatment plants (WWTPs). The mecA-specific nanosensors showed stability in environmental conditions and in high ionic strength ([MgCl₂]<50mM), and high selectivity against mismatched targets. Spectrophotometric detection was reproducible with an LOD of 70pM (≈4×10⁷genes/μL), even in the presence of interferences associated with non-target genomic DNA and complex WWTP effluent. This contribution supports the environmental applicability of a new line of cost-effective, field-deployable tools needed for wide-scale biocontaminant monitoring.

Exploring the selective lactic acid production from food waste in uncontrolled pH mixed culture fermentations using different reactor configurations

Carboxylic acid production from food waste by mixed culture fermentation is an important future waste management option. Obstacles for its implementation are the need of pH control, and a broad fermentation product spectrum leading to increased product separation costs. To overcome these obstacles, the selective production of lactic acid (LA) from model food waste by uncontrolled pH fermentation was tested using different reactor configurations. Batch experiments, semi-continuously fed reactors and a percolation system reached LA concentrations of 32, 16 and 15gCOD_LA/L, respectively, with selectivities of 93%, 84% and 75% on COD base, respectively. The semi-continuous reactor was dominated by Lactobacillales. Our techno-economic analysis suggests that LA production from food waste can be economically feasible, with LA recovery and low yields remaining as major obstacles. To solve both problems, we successfully applied in-situ product extraction using activated carbon.

Genome-Resolved Meta-Omics Ties Microbial Dynamics to Process Performance in Biotechnology for Thiocyanate Degradation

Remediation of industrial wastewater is important for preventing environmental contamination and enabling water reuse. Biological treatment for one industrial contaminant, thiocyanate (SCN^-), relies upon microbial hydrolysis, but this process is sensitive to high loadings. To examine the activity and stability of a microbial community over increasing SCN^- loadings, we established and operated a continuous-flow bioreactor fed increasing loadings of SCN^-. A second reactor was fed ammonium sulfate to mimic breakdown products of SCN^-. Biomass was sampled from both reactors for metagenomics and metaproteomics, yielding a set of genomes for 144 bacteria and one rotifer that constituted the abundant community in both reactors. We analyzed the metabolic potential and temporal dynamics of these organisms across the increasing loadings. In the SCN^- reactor, Thiobacillus strains capable of SCN^- degradation were highly abundant, whereas the ammonium sulfate reactor contained nitrifiers and heterotrophs capable of nitrate reduction. Key organisms in the SCN^- reactor expressed proteins involved in SCN^- degradation, sulfur oxidation, carbon fixation, and nitrogen removal. Lower performance at higher loadings was linked to changes in microbial community composition. This work provides an example of how meta-omics can increase our understanding of industrial wastewater treatment and inform iterative process design and development.

MEGARes: an antimicrobial resistance database for high throughput sequencing

Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database.

Metagenomics: Probing pollutant fate in natural and engineered ecosystems

Polluted environments are a reservoir of microbial species able to degrade or to convert pollutants to harmless compounds. The proper management of microbial resources requires a comprehensive characterization of their genetic pool to assess the fate of contaminants and increase the efficiency of bioremediation processes. Metagenomics offers appropriate tools to describe microbial communities in their whole complexity without lab-based cultivation of individual strains. After a decade of use of metagenomics to study microbiomes, the scientific community has made significant progress in this field. In this review, we survey the main steps of metagenomics applied to environments contaminated with organic compounds or heavy metals. We emphasize technical solutions proposed to overcome encountered obstacles. We then compare two metagenomic approaches, i.e. library-based targeted metagenomics and direct sequencing of metagenomes. In the former, environmental DNA is cloned inside a host, and then clones of interest are selected based on (i) their expression of biodegradative functions or (ii) sequence homology with probes and primers designed from relevant, already known sequences. The highest score for the discovery of novel genes and degradation pathways has been achieved so far by functional screening of large clone libraries. On the other hand, direct sequencing of metagenomes without a cloning step has been more often applied to polluted environments for characterization of the taxonomic and functional composition of microbial communities and their dynamics. In this case, the analysis has focused on 16S rRNA genes and marker genes of biodegradation. Advances in next generation sequencing and in bioinformatic analysis of sequencing data have opened up new opportunities for assessing the potential of biodegradation by microbes, but annotation of collected genes is still hampered by a limited number of available reference sequences in databases. Although metagenomics is still facing technical and computational challenges, our review of the recent literature highlights its value as an aid to efficiently monitor the clean-up of contaminated environments and develop successful strategies to mitigate the impact of pollutants on ecosystems.