# Presentation: 005486

## The Diversity of Nitrite Reductase Genes(nirS and nirK) from Bacterial Communities and Isolates in Nitrate- and Uranium-Contaminated Groundwater and Analysis with Artificial Neural Networks

-      T. Yan1,2^, M.W. Fields (fieldsm1@ornl.gov)1^, Craig Brandt1, Jack Schryver1, L. Wu1, J.M. Tiedje2 and J. Zhou1,2
- 1Oak Ridge National Laboratory, Oak Ridge, TN 37831, 2Center for Microbial Ecology, Michigan State University, East Lansing, MI 48824

**Abstract**
- The presence and diversity of the nitrite reductase genes, *nirS* and *nirK*, were assessed in groundwater samples with nitrate levels between 1 and 1000 mg/l at circumneutral pH sites, and at three acidic pH sites with both increased nitrate and uranium levels compared to background. The *nirK* clones (958) and *nirS* (1162) were screened by RFLP analysis, the nucleotide sequences determined for all unique clones, and compared to the sequences of known denitrifiers as well as FRC bacterial isolates. A single dominant *nirK* restriction pattern was observed for all six wells, and accounted for 67%of the total *nirK* clonal library. The same dominant *nirS* pattern was observed at four of the wells, including background, and accounted for 37% of the total *nirS* clonal library. Percent similarity values for the *nirK* genes ranged from 60-100%, and the predominant sequence for all six sites was 83% similar to that of *Hyphomicrobium zavarzinii*. Percent similarity values for nirS genes ranged from 59-100%, and the three dominant clones were most closely related to *nir*S *Alcaligenes faecalis* or *Ralstonia*. The *nir*S and *nir*K genes were detected in 2 and 18 bacterial isolates from the same samples, respectively. The isolate *nir*K sequences were distantly related to known sequences, but one isolate *nir*K was closely related to the predominant *nir*K clone. A majority of the isolate *nir*S genes were not closely related to previously described sequences, but were similar to cloned *nir*S sequences from FRC. Dominance and diversity indices for *nir*K and *nir*S sequences did not display a strong correlation with contaminant levels, but when compared to background, sites with an increased diversity index for *nir*S had a decreased index for *nir*K, and vice versa. Sequence overlap was observed across all sites, but analysis indicated that some sites were predominated by groups of similar sequences. The majority of the FRC *nir*K and *nir*S gene sequences were not closely related to previously described genes, and may be selected under the different environmental conditions and contribution to biochemical diversity.
**Introduction**
- The Field Research Center (FRC) was established by the NABIR (Natural and Accelerated Bioremediation research) program to exam biogeochemical factors on bioremediation, and is located on the Oak Ridge Reservation in Tennessee. The FRC has four waste ponds contaminated by nitrate, uranium, heavy metal and volatile organics. In the present study, five groundwater samples were obtained from contaminated wells, and one from an uncontaminated well.  Analyzing the structure and function of different bacterial communities is critical to understanding the community dynamics and geochemical processes at the FRC, and the possible affects on biostimulation of uranium reduction.

**FRC *****nir*****K phylogeny**.  Phylogenetic relationship of all unique cloned *nir*K (n=48) sequences, two isolates from the FRC and reference sequences from the GenBank database.   The tree is based on a neighbor-joining method and pairwise deletion.  The percentage of 500 bootstrap values that supported is branch is shown, and bootstrap values below 50% are not shown.  Only one unique clone, D05-015-127, had higher than 90% nucleotide identity with a known *nir*K gene (*Bradyrhizobium* *japonicum*The *nir*K sequence from *Hyphomicrobium* *zavarzinni* was the most closely related known sequence to almost half of the unique FRC *nir*K sequences (83% identity), and approximately 60% of the unique clones had 80 to 85% identity with known sequences from the -*Proteobacteria*, *H*. *zavarzinni*, *Rhizobium* *melitoti*, or *Blastobacter* *denitrificans*.  The remaining unique clones had 70 to 78% nucleotide identity with known *nir*K genes from *H*. *zavarzinni* or *Blastobacter* *denitrificans*.  Two FRC clones had approximately 70% identity with the *nir*K of *Rhodobacter* *sphaeroides *or *Alcaligenes STC1*, were divergent from previously reported *nir*K sequences, and were obtained from the acidic pH sites, FW-010 and FW-015.
-      The *nir*K gene of FRC isolate AM-E2 was most closely related to the dominant *nir*K clone (C01-03-6) with sequence identity of 99%, and the closest reference sequences were from *Hyphomicrobium* *zavarinii* and *Sinorhizobium* *melilto* with identity values of 74% and 71%, respectively (Fig. 4).  It should be noted that partial 16S rDNA gene analysis identified isolate AM-E2 as a low G+C gram-positive bacterium (data not shown).  The *nir*K gene sequence of FRC isolate DM-M had nucleotide identity values of 77%, 70%, and 70% with isolate AM-E2, clone C01-03-6, and *Blastobacter* *denitrificans*, respectively.

**FRC *****nir*****S phylogeny.**  Phylogenetic relationship of all unique cloned *nir*S sequences, 20 isolates from the FRC and reference sequences from the GenBank database.   The tree is based on a neighbor-joining method and pairwise deletion.  The 13 clone groups represent closely related FRC sequences.  The percentage of 500 bootstrap values that supported is branch is shown, and bootstrap values below 50% are not shown. The clone Group 1 accounted for over half of the entire library and had 95% identity with the *nir*S from *Alcaligenes* *faecalis* and approximately 92% identity with the *nir*S of *Psueodomonas* *stutzeri*. The clone Group 2 contained 9 sequences, and had approximately 80% nucleotide identity with the *A*. *faecalis* *nir*S gene.  Clone Group 1 was predominated by clones from wells FW-005, -010, and -015, but almost all sequences in clone Group 2 were obtained from wells FW-003 and TPB-16.  The clone Groups 3 and 4 clustered with the *nir*S of *Azospirillum* *brasilense* (83 and 82%).  The clone Group 5 contained the dominant clone for FW-003, and was only 73% identical to the closest known reference of *A*. *faecalis*.  The *nir*S clone Group 8 closest relative was Group 7 with 79% identity, and the majority of clones were from FW-005.      The clone Group 13 had the dominant clone from TPB-16, and the majority of the clones (67%) were from TPB-16.
- The reference sequence from *Pseudomonas* *aeruginosa* was closely related (96-99% identity) to the *nir*S gene from six isolates (Isolate Group 1) which originated from FW-300 or FW-003.  The isolate DM-N2 had a similar *nir*S gene sequence (96-99%) to the other *Pseudomonas* species.  Isolate Group 2 had nucleotide identity values that ranged from 95-99%, and were related to the *nir*S gene of Isolate Group 1 or *P*. *aeruginosa*, 74-78% and 72-77% respectively.  The *nir*S sequences from Isolate Group 3 were 83-98% similar, were obtained from FW-300 and TPB-16, and the partial 16S rRNA sequence data indicated that all five isolates were -*Proteobacteria*.  The *nir*S gene from *Ralstonia* *eutropha*, also a -*Proteobacterium*, was the most closely related sequence (76-78%).

**Principal components analysis** (PCA) of the sites with respect to geochemical measurements (nitrate, pH, nickel, uranium, total organic carbon, and non-purgable organic carbon). The analysis identified the highly correlated analytes: nitrate, nickel, TOC, and NpOC. When the six sites were subjected to PCA based on geochemical characteristics, some sites were more related than others. However, when the OTU distributions from the samples were analyzed alone with PCA, the results were different, and samples with drastically different geochemical measurements were grouped (data not shown).

-                       _# of clones    OTU__b__     H’__c    __1/D__d__     Evenness__e__   Richness__f_
_*nir*__K_
- FW-300             143              16      2.33    3.30          0.58            225
- FW-003             229              12      0.70    1.20          0.20            3719
- FW-005             185              12      0.78    1.23          0.22            185
- FW-010             134              12      2.13    2.90          0.60            186
- FW-015             140              21      3.10    5.11          0.71            7133
- TPB-16              127              31      2.93    4.07          0.67            359
_*nir*__S_
- FW-300            173               36       2.92    3.10          0.55           8418
- FW-003            210               56       3.86     6.51         0.75           393
- FW-005            253               59       3.60     4.01         0.61            648
- FW-010            174               54       2.15     2.59         0.52           3814
- FW-015            175               39       1.33     1.47         0.32           277
- TPB-16             177               37       1.91     2.07          0.45          287
- a  number of clones in each sub-library analyzed by RFLP	b operational taxonomic unit based on unique RFLP
- c Shannon-Wiener index             		d Reciprocal of Simpson’s index
- e As E approaches 1, population is more evenly distributed      	f Statistical prediction of species or gene number
_**Physical characteristics and diversity estimates for the **__***nir***__**K and **__***nir***__**S clones**_. The *nir*K clone libraries from FW-003 and FW-005 displayed one predominant pattern, and had low diversity.  The other four samples displayed higher diversity and evenness.  Well FW-300 and FW-010 had similar diversity, evenness, and richness indices, even though FW-010 had 35,000-fold higher nitrate levels. The diversity of *nir*S varied from well to well, and FW-015 and TPB-16 had decreased diversity indices compared to background.  The *nir*S clones from FW-003 showed the greatest diversity of either gene from any of the wells. Interestingly, TPB-16 and FW-015 had the lowest *nir*S diversity, but had the highest *nir*K diversity.  Moreover, the sites, FW-003 and FW-005, had the lowest *nir*K diversity, but displayed the highest *nir*S diversity.  When the different diversity indices for *nir*K and *nir*S sequences were compared from the same site, the two gene pools were inversely proportional with an r2=0.88 (data not shown). Also, higher *nir*S diversity was noted in environments with relatively moderate levels of nitrate (175 and 1,000 mg/l), and higher *nir*K diversity was observed in groundwater samples with extremes in nitrate levels (<30 or >1000 mg/l).  These results suggested that particular environmental conditions might select one gene over the other, and that the community dynamics for microorganisms with a *nir*K might affect the composition of microorganisms with a *nir*S and vice versa.

_**Conclusions**_
- • The dominant *nir*K for all sites was 83% identical to the *nir*K of *Hyphomicrobium* *zavarzinii*, and appears to represent a novel group of nitrite reductases
- •  The *nir*K clone Groups 2, 3, and 4 had less than 75% identity to known *nir*K genes
- •  The *nir*K clone Group 4 sequences were predominantly from acidic sites, and may represent *nir*K-containing denitrifiers that can survive at low pH environments
- •  The predominant *nir*S clones from FW-003 and TPB-16 were less than 75% identical to previously known sequences, and may represent novel *nir*S sequences
- •  Many of the *nir*S clones had less than 75% identity with previously known genes, and represent novel and diverse groups
- • FRC environmental conditions might select one gene over the other, and the community dynamics for microorganisms with a *nir*K might affect the composition of microorganisms with a *nir*S and vice versa
- •  ANN analyses perform better than linear or logistical methods.  The MSE for both ANN training and generalization errors were reduced compared to the linear and logistic models (4 to 8-fold).

- Schematic representation of FRC field sites and selected geochemical parameters for the groundwater samples used in this study.  FW-300 is the background area spatially isolated from the contaminated sites.  All values except pH are reported as mg/l and were determined by the FRC management team at Oak Ridge National Laboratory and the data are maintained at _[http://www.](http://www.esd.ornl.gov/nabirfrc/)__[esd](http://www.esd.ornl.gov/nabirfrc/)__[.](http://www.esd.ornl.gov/nabirfrc/)__[ornl](http://www.esd.ornl.gov/nabirfrc/)__[.](http://www.esd.ornl.gov/nabirfrc/)__[gov](http://www.esd.ornl.gov/nabirfrc/)__[/](http://www.esd.ornl.gov/nabirfrc/)__[nabirfrc](http://www.esd.ornl.gov/nabirfrc/)__[/](http://www.esd.ornl.gov/nabirfrc/)_.  TOC, total organic carbon.

**Material and Methods**
**DNA extractin and purification**.  Bacteria from groundwater (1-2 l) were harvested by centrifugation (10,000 x g force, 4С for 30 min), and the pellets were stored at -80С.  The cell pellet was resuspended in a lysis buffer and the cells disrupted with a previously described grinding method (1).  The precipitated DNA was purified by gel electrophoresis plus mini-column preparation (1,2).
**PCR amplification and cloning**.  The fragments of the *nir*K and *nir*S genes were amplified in a 9700 Thermal Cycler with the primer pairs copper 583 F (5’ TCA TGG TGC TGC CGC GKG ACG G 3’) and copper 909R (5’ GAA CTT GCC GGT KGC CCA GAC 3’) for the *nir*K gene, and heme 832 F (5’ TCA CAC CCC GAG CCG CGC GT 3’) and heme 1606R (5’ AGK CGT TGA ACT TKC CGG TCG G 3’) for the *nir*S gene.  The PCR reactions (20 *u*l) contained 2ul 10×buffer (500 mM KCl, 100mM Tris HCl pH 9.0 and 1% Triton X-100), 1.5ul 25 mM/L MgCl2, 0.2 ul 400ng/ul Bovine serum albumin, 0.2 ul 25 mM 4×dNTPs, 10 pmol each primer, 2.5 U Taq polymerase, 1ul purified DNA (5-10 ng).  To minimize PCR-induced artifacts, the optimal number of cycles was determined and five PCR reactions were combined prior to cloning as described previously (2).  The PCR parameters were as follows:  80С for 30 s, 94С for 2 min; 94С for 30 s, 60С for 1 min, 72С for 1 min, 30 cycles; 72С for 7 min. The combined PCR products (326 bp and 774 bp, respectively) were separated by electrophoresis in a low-melting point agarose gel (0.8%), the appropriate band excised, and the DNA extracted with a Wizard Prep Kit according to manufacture instructions.  Recovered DNA was resuspended in 6 ul ddH2O, 2 ul ligated with pCR2.1 vector from a TA-cloning kit, and competent *E.* *coli* cells transformed.
**RFLP analysis. **Approximately 200 white colonies from each sample were randomly selected and screened for *nir*K and *nir*S inserts, which were detected with the primers specific to the polylinker of the vector pCRTMII as described previously (3).  Each single white colony was picked and resuspended in 60 ul 0.1x TE buffer (1 mM TRIS, 0.1 mM EDTA), boiled 5 minutes at 100С, and stored in freezer.  The inserts were amplified (20 *u*l reactions) with the TA primers specific for the pCR2.1 vector as described previously (3).
- Amplified PCR products (6 μl) were digested with the tetrametric enzymes *Msp*I and *Rsa*I (Gibo-BRL, overnight at 37С, 0.1 U each).  Digested fragments were separated by electrophoresis (7V/cm, 4 h) in 3.5% Metaphor agarose gels with 10 μl of 10mg/l ethidium bromide in 1×TBE buffer.  The RFLP patterns were analyzed and clustered with the Molecular Analyst 1.6 software (Applied Math, Kortrijk, Belgium) using the unweighted pair group method of arithmetic averages (UPGMA) and the Jaccard algorithm.
**Sequence and phylogenetic analysis.  **Unique *nir*K and *nir*S clones from each site were selected for sequence analysis based on differences in RFLP patterns.  PCR products (100 μl) amplified with vector-specific primers were purified with the ArrayItTM PCR Purification Kit or treated with ExoSAP-ITTM  according to manufacturer instructions.  DNA sequences were determined with a BigDye Terminator kit (Applied Biosystem) using a 3700 DNA analyzer (Perkin-Elmer) according to the manufacture instructions at a 5:1 dilution.  The sequences obtained with the vector-specific primers were compared with *nir*K and *nir*S sequences from GeneBank. The sequences were aligned with ClustalW, and alignments compared with reference sequences from the database (4).  Phylogenetic and molecular evolutionary analyses were conducted using MEGA version 2.1 (5), and phylogenetic trees were constructed with distance matrices and the neighbor-joining method.

-  Research was funded by the Natural and Accelerated Bioremediation Research (NABIR) program, Biological and Environmental Research (BER), U.S. Department of Energy

- In order to elucidate if generalized linear models could better describe gene cluster frequency, the *nir*K and *nir*S OTUs were each grouped into 5 classes based on sequence similarity.  When the *nir*K and *nir*S class frequencies were predicted with the geochemical PCA components, reasonable performance with linear models was only observed when frequency data was scaled to the (0,1) interval using a non-linear transformation.  Generalization error (average mean square error, MSE) was about an order of magnitude greater than training error (Table 3).  A logistic regression model was subsequently fit to both data sets.  The logistic model scaled predicted output into the (0,1) interval in a manner consistent with the transformed data and LOO generalization error substantially decreased (Table 3), but was still high.

- Diversity indices were not always inversely proportional to contaminant levels or pH, and the PCA of geochemical data or sequence data alone predicted different relationships between the sites.  These results suggested that simple relationships were difficult to delineate from environmental parameters, ecological indices, and/or sequence data, particularly when the datasets were combined and complexity increased.  Therefore, artificial neural networks (ANNs) were explored for the analysis of relationships between gene type and environmental characteristics.

- Diversity indices were not always inversely proportional to contaminant levels or pH, and the PCA of geochemical data or sequence data alone predicted different relationships between the sites.  These results suggested that simple relationships were difficult to delineate from environmental parameters, ecological indices, and/or sequence data, particularly when the datasets were combined and complexity increased.  Therefore, artificial neural networks (ANNs) were explored for the analysis of relationships between gene type and environmental characteristics.

- 	Graphs of observed versus predicted *nir*K (**a**) gene frequencies for logistic multiple regression model (**a**) and artificial neural network model (**b**).  The symbols denote the 5 sequence groups, and filled symbols represent training data and empty symbols are leave-one-out (LOO) data.  The solid and dashed regression lines are for training and LOO data, respectively. Phylogenetic analysis of unique sequences reveled a clustering of sequences by site for only FW-003 and TPB-16, and phylogenetic analysis did indicate that distinctive clusters for low, moderate, and high nitrate could be identified.  The ANN analysis suggested an increase in frequency for *nir*K Group 1 at low contaminant levels, an increase in frequency for Cluster IV at high contaminant levels, and a decrease in frequency for Group 2 at low contaminants.  For *nir*S, ANN suggested an increase in frequency of Group 5, Cluster II, and Cluster III at low to moderate contaminant levels.