Antimony efflux underpins phosphorus cycling and resistance of phosphate-solubilizing bacteria in mining soils.

Microorganisms play crucial roles in phosphorus (P) turnover and P bioavailability increases in heavy metal-contaminated soils. However, microbially driven P-cycling processes and mechanisms of their resistance to heavy metal contaminants remain poorly understood. Here, we examined the possible survival strategies of P-cycling microorganisms in horizontal and vertical soil samples from the world's largest antimony (Sb) mining site, which is located in Xikuangshan, China. We found that total soil Sb and pH were the primary factors affecting bacterial community diversity, structure and P-cycling traits. Bacteria with the gcd gene, encoding an enzyme responsible for gluconic acid production, largely correlated with inorganic phosphate (Pi) solubilization and significantly enhanced soil P bioavailability. Among the 106 nearly complete bacterial metagenome-assembled genomes (MAGs) recovered, 60.4% carried the gcd gene. Pi transportation systems encoded by pit or pstSCAB were widely present in gcd-harboring bacteria, and 43.8% of the gcd-harboring bacteria also carried the acr3 gene encoding an Sb efflux pump. Phylogenetic and potential horizontal gene transfer (HGT) analyses of acr3 indicated that Sb efflux could be a dominant resistance mechanism, and two gcd-harboring MAGs appeared to acquire acr3 through HGT. The results indicated that Sb efflux could enhance P cycling and heavy metal resistance in Pi-solubilizing bacteria in mining soils. This study provides novel strategies for managing and remediating heavy metal-contaminated ecosystems.

PCycDB: a comprehensive and accurate database for fast analysis of phosphorus cycling genes.

BACKGROUND: Phosphorus (P) is one of the most essential macronutrients on the planet, and microorganisms (including bacteria and archaea) play a key role in P cycling in all living things and ecosystems. However, our comprehensive understanding of key P cycling genes (PCGs) and microorganisms (PCMs) as well as their ecological functions remains elusive even with the rapid advancement of metagenome sequencing technologies. One of major challenges is a lack of a comprehensive and accurately annotated P cycling functional gene database. RESULTS: In this study, we constructed a well-curated P cycling database (PCycDB) covering 139 gene families and 10 P metabolic processes, including several previously ignored PCGs such as pafA encoding phosphate-insensitive phosphatase, ptxABCD (phosphite-related genes), and novel aepXVWPS genes for 2-aminoethylphosphonate transporters. We achieved an annotation accuracy, positive predictive value (PPV), sensitivity, specificity, and negative predictive value (NPV) of 99.8%, 96.1%, 99.9%, 99.8%, and 99.9%, respectively, for simulated gene datasets. Compared to other orthology databases, PCycDB is more accurate, more comprehensive, and faster to profile the PCGs. We used PCycDB to analyze P cycling microbial communities from representative natural and engineered environments and showed that PCycDB could apply to different environments. CONCLUSIONS: We demonstrate that PCycDB is a powerful tool for advancing our understanding of microbially driven P cycling in the environment with high coverage, high accuracy, and rapid analysis of metagenome sequencing data. The PCycDB is available at https://github.com/ZengJiaxiong/Phosphorus-cycling-database . Video Abstract.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as uranium or nitrate increased. These key microbial functional genes could be used to successfully predict environmental contamination and ecosystem functioning. This study represents a significant advance in using functional gene markers to predict the spatial distribution of environmental contaminants and ecosystem functioning toward predictive microbial ecology, which is an ultimate goal of microbial ecology.

The functional gene composition and metabolic potential of coral-associated microbial communities.

The phylogenetic diversity of coral-associated microbes has been extensively examined, but some contention remains regarding whether coral-associated microbial communities are species-specific or site-specific. It is suggested that corals may associate with microbes in terms of function, although little is known about the differences in coral-associated microbial functional gene composition and metabolic potential among coral species. Here, 16S rRNA Illumina sequencing and functional gene array (GeoChip 5.0) were used to assess coral-associated microbial communities. Our results indicate that both host species and environmental variables significantly correlate with shifts in the microbial community structure and functional potential. Functional genes related to key biogeochemical cycles including carbon, nitrogen, sulfur and phosphorus cycling, metal homeostasis, organic remediation, antibiotic resistance and secondary metabolism were shown to significantly vary between and among the four study corals (Galaxea astreata, Porites lutea, Porites andrewsi and Pavona decussata). Genes specific for anammox were also detected for the first time in the coral holobiont and positively correlated with ammonium. This study reveals that variability in the functional potential of coral-associated microbial communities is largely driven by changes in environmental factors and further demonstrates the importance of linking environmental parameters with genomic data in complex environmental systems.

Plankton community succession in artificial systems subjected to cyanobacterial blooms removal using chitosan-modified soils.

Using artificial systems to simulate natural lake environments with cyanobacterial blooms, we investigated plankton community succession by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) fingerprinting and morphological method. With this approach, we explored potential ecological effects of a newly developed cyanobacterial blooms removal method using chitosan-modified soils. Results of PCR-DGGE and morphological identification showed that plankton communities in the four test systems were nearly identical at the beginning of the experiment. After applying the newly developed and standard removal methods, there was a shift in community composition, but neither chemical conditions nor plankton succession were significantly affected by the cyanobacteria removal process. The planted Vallisneria natans successfully recovered after cyanobacteria removal, whereas that in the box without removal process did not. Additionally, canonical correspondence analysis indicated that other than for zooplankton abundance, total phosphorus was the most important environmental predictor of planktonic composition. The present study and others suggest that dealing with cyanobacteria removal using chitosan-modified soils can play an important role in controlling cyanobacterial blooms in eutrophicated freshwater systems.

[DNA fingerprinting structure of plankton community and its relations to environmental physical-chemical factors in Donghu Lake].

By the method of RAPD fingerprinting, this paper studied the DNA fingerprinting structure of plankton community and its relations to the main environmental physical-chemical factors at five sites in Donghu Lake. From the screened 9 random primers, a total of 210 observable bands with a length of 150-2 000 bp were amplified, 93.3% of which were polymorphic. At the five sites, the average number of amplified bands was 42, with the maximum (53) at site IV and the minimum (35) at site V. The PO4(3-)-P and TP contents were the highest at site I, NH4(+)-N, TN and NO2(-)-N contents were the highest at site V, while the values of all test physical-chemical parameters were the lowest at site IV. No obvious differences in COD, alkalinity, rigidity, and calcium content were observed among the study sites. Similarity clustering analysis showed that the DNA fingerprinting of plankton community based on RAPD marker could cluster the five sites into two groups, i. e., sites I, II and III could be clustered into one group, while sites IV and V could be clustered into another group, which was consistent with the clustering analysis based on the main environmental physical-chemical factors. In conclusion, there was a close relation between the DNA fingerprinting structure of plankton community and the main environmental physical-chemical factors in Donghu Lake.