Characteristics of
Abstract
A packed bed bioreactor efficiently treated low-level radioactive waste for years with a retention time of 24 h using acetate as the sole carbon source. However, there was generation of dead biomass. This bioreactor biomass was used to develop a bacterial consortium, which could perform the function within 4 h while simultaneously accumulating nitrate and phosphate. The dead mass was negligible. Serial dilution technique was used to isolate the world’s first pure culture of a nitrate accumulating strain from this consortium. This isolate could simultaneously accumulate nitrate and phosphate from solution. Its ability to form biofilm helped develop a packed bed bioreactor system for waste water treatment, which could optimally remove 94.46% nitrate within 11 h in batch mode while 8 h in continuous mode from waste water starting from 275 ppm of nitrate. The conventional approach revealed the strain to be a member of genus Bacillus but showed distinct differences with the type strains. Further insilico analysis of the draft genome and the putative protein sequences using the bioinformatics tools revealed the strain to be a novel variant of genus Bacillus. The sequestered nitrate and phosphate within the cell were visualized through electron microscopy and explained the reason behind the ability of the isolate to accumulate 1.12 mg of phosphate and 1.3 gm of nitrate per gram of wet weight. Transcriptome analysis proposed the mechanism behind the accumulation of nitrate and phosphate in case of this novel bacterial isolate (MCC 0008). The strain with the sequestered nutrients work as biofertilizer for yield enhancement in case of mung bean while maintaining soil fertility post-cultivation.
Keywords
- nitrate accumulation
- packed bed biofilm reactor
- Bacillus sp MCC 0008
- insilico analysis
- transcriptome analysis
- radioactive effluent
1. Introduction
All ore mining produce waste rock that in turn may produce acid mine drainage (AMD), due to the presence of sulfides. The waste generated is treated by physico-chemical means and is either stored in engineered containments or in open surface based on the nature of the effluent. Only limited information is available about effects of microbial processes used for similar purposes during large-scale operation. In addition, the mining itself and processing are often associated with a wide range of potential human health risks. Surface and underground mining generate a large volume of waste rock, which may contain only very little uranium but has fission products, for example, radium (radioactive) or lead (highly toxic) that is left behind as a waste. The second step is a process, known as the milling of the ore in which the rocks are crushed and ground. Chemical leaching follows and over 50% of uranium ore is obtained with classic mining methods. Water used in this process that cannot be recycled within a processing plant as well as excess water from a mine needs to be removed or treated to meet environmental requirements. The multistep process of recovery includes neutralization of the effluents, precipitating any metals, and reducing the uranium and radium content. [1–3]. This treatment depends upon the uranium recovery process, chemicals used, and contaminant ores. Water recovered may get recharged as groundwater or is either discharged or used for plant operations. Often this water needs further treatment before it could be reused or discharged for removal of contaminants. The multistep process begin with coagulating or precipitating heavy metals followed by neutralizing acids, or adjusting pH and then precipitating radium with barium chloride. The water treatment process is often followed by additional “clarification” or “polishing” steps using clarifiers, sand filters, and even reverse osmosis. The alternative option might be to use microbial bioremediation using sulfate-reducing bacteria [4].
The foremost source of waste generation occurs during nuclear fuel cycle operations that comprises of facilities to purify, convert, and enrich uranium from mining and milling and to manufacture fuel elements for nuclear reactor and gives rise to a variety of materials and product outputs [2, 3]. Enrichment of radioactive ore involves use of chemicals which lead to high levels of nitrate in the effluent.
The effluent generated cannot be discharged into the environment without treatment. The physicochemical treatment is expensive and economically not feasible during large-scale operation. Hence, biological options were sought. The problem in hand was to develop a microbial process, which could efficiently treat low-level radioactive waste containing nitrate generated from ore enrichment. Nitrate being a common pollutant in municipal as well as agricultural waste water, municipal sewage was passed through corrugated sheets of a packed bed reactor to develop a biofilm-based bioreactor that could treat low-level radioactive effluent within 24 h on a continuous basis [5] using acetate as the sole carbon source. However, dead mass was generated during the operation. The biomass was characterized [5] and further enrichment in nitrate broth (HiMedia M439) resulted in isolation of the fastest nitrate removing consortium. This consortium was further characterized to yield the world’s first nitrate accumulating pure culture [11] of a
2. Consortium development and characterization
Nitrate removal from the medium by the bacteria was the primary step for selecting a consortium for nitrate removal. Either an assimilatory or a dissimilatory pathway results in nitrate removal from solution [6]. An alternative pathway for the nitrate removal was through nitrate accumulation, as evident in isolates from genus
The inoculum standardization indicated 10% of the parent culture as optimum for biofilm development. This consortium reduced 97.44% nitrate from the medium within 4 h (Figure 2) while simultaneously reducing 48.2% phosphate during incubation in a biofilm-based bioreactor. This consortium could reduce 500 ppm and 1000 ppm nitrate load within 7 and 5 h, respectively. Nitrate concentrations between 1500 and 4000 ppm could be reduced by 99% within 4 h (Figure 2), and 5000 ppm nitrate was reduced by 80.5% after treating for 11–12 h and 99.62% after 24 h. The correlation coefficient was −0.53173, which signifies no direct correlation between the initial nitrate load and bioreactor reduction for the range tested in this study. The above data show the aerobic consortium (BN7) to perform the fastest nitrate removal by a microbial system to the best of our knowledge.
On further analysis, this consortium was found to accumulate both nitrate and phosphate simultaneously (2.84 gm/gm wet weight for nitrate and 1.14 mg/gm wet weight for phosphate). Cd, Sr, and Ce inhibited the bacterial growth even at a concentration of 0.1 mM, whereas Co and Zn were inhibitory at 0.5 mM. For Cu, Fe, and Zn salts, lower concentrations had minimal impact on the nitrate reduction, and the reduction efficiency in the presence of Pb salts was at par with the control set. After 4 h of growth, 0.5 mM of Pb salts decreased the reduction efficiency by only 3%. Moreover, the nitrate reduction in the presence of Cu salts after 2 h was higher than for the control (37% in Cu-treated cells compared to 8.5% in control), which can be attributed to the presence of
Preservation experiment revealed both subculture maintenance and glycerol stock storage at –80°C (two months storage) to be equally efficient with nitrate reduction efficiency of 94% and 92%, respectively, after 12 h of growth for BN7. Preserving the culture as a streak plate or stab reduced the efficiency to approximately 88%. The lyophilized form was less efficient relative to the other three storage methods. Thus, using a glycerol stock could be an efficient strategy for the long-term maintenance of the microbial consortium. At the molecular level, the BN7 harbored members which closely resembled
3. Purification of nitrate accumulator and its characterization
Nitrate removal by denitrification and assimilation is well documented for bacterial species. Nitrate accumulation by bacterial genus
Catalase, oxidase, protease, amylase, lipase, DNAse positive, lecithinase negative | |
It utilizes dextrose, trehalose, esculin, glycerol, maltose | |
Phosphatase and ammonia production positive, indole acetic acid, hydroxymate siderophore and hydrogen cyanide production negative | |
Sensitive to ciprofloxacin, norfloxacin, cephadroxil, neomycin, gentamycin, doxycycline hydrochloride | |
Resistant to metronidazole, rifampicin, ampicilin, trimethoprim, roxythromycin, cloxacin, ceftazidime |
The transmission electron micrographs clearly revealed the presence of vacuoles (Figure 4b) which has earlier been reported for nitrate accumulators. This indicates the possibility that the isolate is a nitrate accumulator. The nitrate accumulation study following sonication-based lysis of the harvested pellet and measurement of released nitrate from the intracellular cell free supernatant as per the method of Cataldo et al. [12] exhibited nitrate accumulation of up to 1278.66–1302.122 ppm/gm (0.021 M) of wet weight. It is less than the extent of accumulation reported for
The strain showed polysaccharide formation starting from the fourth hour that continued till the eighth hour. This property might provide the benefit of attachment to suitable surfaces to the strain. Active log-phase culture was used to determine whether the isolate could form biofilm according to the method of Martin et al. [8].
Different percentages (1%, 2%, 4%, 6%, 8%, 10%, 15%) of actively growing culture were inoculated in nitrate broth into small falcon containing identical number of plastic rachig rings. The performance in terms of nitrate and phosphate removal was checked for repeated recharges with sterile nitrate broth. The isolate showed good biofilm formation with 10% inoculum being the optimum. The biofilm formation showed saturation by eleventh hour. Optimum performance in terms of nitrate reduction was also observed in the eleventh hour (Figure 5). This optimization was further utilized for immobilization of the isolate in the reactor.
Accompanied by this, the isolate’s ability for active biofilm formation was checked by assaying the supernatant in the tissue culture plate for nitrate and phosphate removal. By this, the time needed for biofilm formation along with optimal functioning in terms of nitrate and phosphate removal was determined to be 11 h for nitrate and 22 h for phosphate (Figure 6).
Since the isolate grows as biofilm, it could be used for setting up of a biofilm-based bioreactor for continuous waste water treatment in terms of nitrate removal. However, a prerequisite for it was to design the minimal growth condition for the same. This would ensure that enrichment culture components would not be needed to run the process and in turn the influent would not add to the COD load of the effluent. Dextrose, glycerol, and citric acid were chosen to check the growth of MCC0008 in minimal condition. The isolate showed the best growth in glycerol, and hence, it was further utilized as the carbon source to determine the optimum percentage of carbon source for growth as well as performance. One percentage of glycerol showed the optimum growth as well as nitrate and phosphate removal under minimal condition. Hence, 1% of glycerol was standardized as the carbon source for the isolate for further studies in packed bed bioreactor.
The comparison of the isolate’s activity under different oxygen availability in the eighth hour after inoculation revealed that the isolate performed optimally in aerobic condition followed by anaerobic condition. Oxygen depletion in anaerobic state resulted in a decrease in activity. Highest amount of nitrate reduction and subsequent conversion to ammonia was also in aerobic state due to the assimilatory pathway. Substantial accumulation also occurred in aerobic state so that the accumulated nitrate could be used as terminal electron acceptor in oxygen-depleted state.
In the 5 L suspended bioreactor, the strain grew exponentially up to 5 h with 65% denitrification and phosphate removal taking place within the fourth hour (Figure 7).
4. Immobilization and acclimatization in a packed bed bioreactor
Fixed packed bed configuration has high surface area to volume ratio, thereby increasing the microbial density and improving the conditions necessary for nutrient removal. Biofilm-based reactors also have the advantage over other types of bioreactors with respect to ease of operation, high-density accumulation of microbe, resistance of the system to environmental stress [13] and do not require any additional measure to retain biomass in culture [14]. Rotating biological contractors (RBC), trickling filters and biofilm membrane bioreactor are some of the widely used biofilm-based bioreactor. Thus, in order to make the system more cost-effective along with better nutrient sequestration rate, the abilities of the isolate were further exploited. In order to exploit these biofilm forming, nitrate, and phosphate sequestration abilities, a reactor packed with suitable matrix with a fixed bed was developed. The bioreactor was designed of glass with steel mesh as immobilization matrix (Figure 8). The isolate could bind equally well to steel and plastic. The total capacity of the bioreactor was 9 L with a working volume of 5 L post-filling up with steel matrix up to sixty percent capacity. The steel mesh acted as the matrix for the formation of MCC0008 biofilm. Ports were designed at different heights of the bioreactor as shown in the Figure 8.
The graphical representation shows the initial acclimatization period for proper biofilm development. The initial rise and fall in the performance correlate well with the biofilm character of slough off and growth to achieve stability. It required about 30 loadings to attain stability. After the 39th loading, approximately full nitrate reduction was obtained in one hour only in nitrate broth which was retained for more than 90 days (Figure 9a).
After stable performance of the bioreactor in enriched media, next the performance of the reactor was monitored in minimal media (Figure 9b). This was done in order to acclimatize the reactor to minimal conditions before exposure to waste water. It contained 495ppm nitrate and 1% glycerol.
The biofilm was observed to be dense with thick layer of polysaccharide during environmental scanning electron microscopy (Figure 10).
Post-acclimatization of the biofilm to minimal media, non-radioactive wastewater was charged. The dynamics of nitrate removal in batch mode is reflected in Figure 11. Since the isolate is from a consortium acclimatized to radioactive waste water, it is expected to show similar performance with low-level radioactive waste.
The equation, statistics, summary, and ANOVA for nitrate reduction kinetics (depicted in Figure 11a) are as follows:
Statistics:
Reduction | |
---|---|
Number of points | 12 |
Degrees of freedom | 9 |
Reduced Chi squarer | 7.39081 |
Residual sum of squares | 66.51727 |
Adj. |
0.99046 |
Fit status | Succeeded(100) |
The equation, statistics, summary, and ANOVA for remaining nitrate in the medium with time (depicted in Figure 11b) are as follows:
Complete nitrate removal from wastewater took place in 11 h. The longer retention time for waste water treatment as compared to that in minimal media in terms of nitrate removal may be due to the presence of other contaminants to which the biofilm is sensitive. Multivariate analysis using response surface methodology revealed higher nitrate removal at higher initial concentration of nitrate with little effect of the flow rate (within the range tested) on the system performance (Figure 12).
Response | 1 | Nitrate reduction | ||||
---|---|---|---|---|---|---|
ANOVA for response surface quadratic model | ||||||
Analysis of variance table [Partial sum of squares—Type III] | ||||||
Model | 279.17 | 9 | 31.02 | 17.36 | 0.0029 | Significant |
A-Flow rate | 14.96 | 1 | 14.96 | 8.37 | 0.0340 | |
B-Nitrate concentration | 76.14 | 1 | 76.14 | 42.61 | 0.0013 | |
C-Phosphate concentration | 1.25 | 1 | 1.25 | 0.70 | 0.4414 | |
AB | 0.93 | 1 | 0.93 | 0.52 | 0.5034 | |
AC | 4.56 | 1 | 4.56 | 2.55 | 0.1711 | |
BC | 0.39 | 1 | 0.39 | 0.22 | 0.6586 | |
A2 | 0.42 | 1 | 0.42 | 0.24 | 0.6477 | |
B2 | 12.37 | 1 | 12.37 | 6.92 | 0.0465 | |
C2 | 14.61 | 1 | 14.61 | 8.18 | 0.0354 | |
Residual | 8.93 | 5 | 1.79 | |||
Lack of fit | 7.84 | 1 | 7.84 | 28.59 | 0.0059 | Significant |
Pure error | 1.10 | 4 | 0.27 | |||
Cor total | 288.11 | 14 |
Std. dev. | 1.34 | R-squared | 0.9690 | |
Mean | 92.69 | Adj R-squared | 0.9132 | |
C.V. % | 1.44 | Pred R-squared | −1.9466 | |
PRESS | 848.93 | Adeq precision | 15.118 |
Intercept | 94.22 | 1 | 0.58 | 92.74 | 95.70 | |
A-Flow rate | −1.93 | 1 | 0.67 | −3.65 | −0.22 | 2.00 |
B-Nitrate concentration | 4.36 | 1 | 0.67 | 2.64 | 6.08 | 2.00 |
C-Phosphate concentration | 0.56 | 1 | 0.67 | −1.16 | 2.28 | 2.00 |
AB | 0.68 | 1 | 0.95 | −1.75 | 3.11 | 2.00 |
AC | −1.51 | 1 | 0.95 | −3.94 | 0.92 | 2.00 |
BC | 0.44 | 1 | 0.95 | −1.99 | 2.87 | 2.00 |
A^2 | −0.23 | 1 | 0.48 | −1.47 | 1.00 | 1.00 |
B^2 | −1.27 | 1 | 0.48 | −2.50 | −0.029 | 1.00 |
C^2 | −1.38 | 1 | 0.48 | −2.61 | −0.14 | 1.00 |
The final equations obtained through RSM-based optimization are as follows:
Nitrate reduction = −81.1 + 424.3 * Flow rate −0.049 * Nitrate concentration + 4.74 * phosphate concentration + 0.15 * Flow rate * Nitrate concentration − 6.04 * Flow rate * Phosphate concentration + 3.13e−004 * Nitrate concentration * Phosphate concentration − 292.25 * Flow rate2 − 5.002e−005 * Nitrate concentration2 − 0.018 * Phosphate concentration2
The packed bed bioreactor system could treat waste water optimally removing 94.46% nitrate within 11 h in batch mode while 8 h in continuous mode from waste water containing 275 ppm of nitrate at 0.63 L/h flow rate.
5. Application as biofertilizer
Singh et al. [15] conducted experiments using
Sample | Control | MCC0008 (coated) | MCC0008 (soil) |
---|---|---|---|
Germination percentage | 74.074 | 83.333 | 87.037 |
Germination index | 39.772 ± 9.39 | 62.298 ± 12.234 | 75.313 ± 9.44 |
Vigor index | 1639.056 | 2390.688 | 2006.801 |
Soil application gave better result, and so further experiments were conducted by sowing soaked seeds, followed by soil application of the isolate. The germination in the presence of antifungal agent (Saaf) was better upon application of the isolate to soil.
16.04 | −7.99 | |
2.84 | −7.20 | |
14.49 | 7.08 | |
25.41 | 8.97 | |
12.82 | −66.60 | |
4.39 | −19.16 | |
12.57 | −26.24 | |
5.59 | −12.59 |
Pot trial and field trial were carried out. For field trial, randomized block design with four replicates was carried out. The sowing was done in the north–south orientation. The seeds’ post-germination was subjected to thinning such that each 1 m2 area contained a total of 40 plants (4 rows of 10 plants each). The inoculum for the germination trial was 4.2 × 106 cells per 125 gm soil in a thermo coal glass/germination tray, 1.39 × 107 cells per 8 kgs soil in each pot and 3.68 × 109 cells per 1 m2 plot for field trial. The yield per hectare of land was calculated for the consortium when compared with control (without fertilizer) and chemical fertilizer application. The yield per hectare for control, MCC0008 application, and chemical fertilizer application was 1277.5 kg, 1974.5 kg, and 1685 kg, respectively. The elemental content improved post-application as compared to control as measured through EDXRF analysis (Table 3). This shows that not only the yield improves as compared to chemical fertilizer but also the elemental content was better as compared to control as well as chemical treatment in MCC0008-treated seeds. The data revealed that upon treatment with MCC0008, there was desirable change in the nutritional quality parameters. There was increase in energy value (4.3%), total carbohydrate (4.5%), total sugar (0%), total dietary fiber (4.5%), protein (4.9%) content while a decrease in moisture content (23.4%), total ash (6.4%), and crude fat (7.5%). The decrease in moisture would ensure better storage of the grains, decrease in ash content means less non-utilizable component, while decrease in fat improves the quality further.
According to the previous reports, gamma irradiation of seeds brings about faster germination [16–18]. This is due to increased levels of transcription. The antinutrient as well as elemental levels following irradiation (presowing) is also reported to be lower. Thus, a combined effect of low-dose gamma irradiation of mung bean seeds along with biofertilizer application was tested. The effect of combined application of low-dose gamma irradiation (2.6 Gray and 5 Gray) on germination, yield enhancement, and elemental content of mung bean seeds were tested. The cell structure and viability of the irradiated seeds were studied following ESEM analysis and microtomy using standard techniques. There was mild improvement in germination following irradiation at 5 Gray while significant yield enhancements in irradiated seeds as shown in the Figure 13.
In order to explore the reason behind improved germination, detailed analysis of seed structure and hilum morphology was carried out using ESEM as shown in Figure 14a and b.
However, this depth of analysis could reveal just dehydration and nothing beyond that. Dehydration is expected to delay germination, while here we observe faster germination. Hence, there must be some other phenomenon which is induced during irradiation. Since germination is initiated through hilum and it is the point of contact for imbibition of water, further analysis with conventional microtomy was carried out. It revealed loosening of the compact arrangement of protein sheets with starch granules upon irradiation (Figure 15). Since irradiation might inactivate the germplasm hence viability staining was carried out for the same set, it was revealed that the vitality of the seeds was maintained for the irradiated seeds within the range tested. Hence, low-dose gamma irradiation does not destroy the seed but makes the hilum loose to enable better uptake of water and nutrients and hence faster germination and enhanced yield. Further analysis at the transcription level will be required for better understanding of the phenomenon.
The application of this strain as biofertilizer to enhance yield while maintaining nutritional quality of the grain and soil fertility has been filed as patent application in India [19]. To protect the intellectual property associated with this discovery, a PCT has also been filed [19].
6. Bioinformatics-based strain identification
The genus “
The phylogenetic analysis of the novel strain was done with its closest neighbors using the 16SrRNA sequence as well as using seven housekeeping genes, namely RNA polymerase B (rpo B), gyrase B subunit (gyrB), pyruvate carboxylase A(pyc A), malate dehydrogenase (mdh), rod shape determining protein(MreB), DNA mismatch repair protein (MutS), and transcription regulator (pIcR). The software used was MEGA (Molecular Evolutionary Genetics Analysis) Version 6.0. MEGA is an integrated tool which is used for constructing sequence alignment, inferring phylogenetic trees, estimating divergence times, mining online databases, estimating rates of molecular evolution, inferring ancestral sequences, and testing evolutionary hypotheses. MEGA is used by biologists in a large number of laboratories for reconstructing the evolutionary histories of species and inferring the extent and nature of the selective forces shaping the evolution of genes and species.
The draft genome sequence of
House-keeping genes | Closest neighbor |
---|---|
DNA gyrase subunit B | |
DNA-directed RNA polymerase beta subunit | |
Malate dehydrogenase | |
DNA mismatch repair protein mutS | |
Phosphatidylinositol specific phospholipase C | All the strains of |
Rod shape determining protein MreB | |
Pyruvate carboxyl transferase | |
Partial 16S rRNA |
DNA–DNA hybridization which calculate the inter-genomic distances between the strains with the score of >70% indicates the same species. The strain was compared with the type strains of
7. Phylogenetic analysis of putative protein
The nucleotide sequence stretches: ANAU01000001, ANAU01000016, ANAU01000020, ANAU01000033, ANAU01000036, ANAU01000046, ANAU01000052, ANAU01000062, and ANAU010000274— each containing several genes – from the draft genome of MCC0008 [11] were translated in MEGA6 [23] using the standard genetic code. The protein sequences generated from these stretches were submitted to HAMAP [24], Interproscan [25, 26], EMBLFasta [26, 27], Prositescan [26, 27], and NPSA blast [28] for predicting their functions. The largest amino acid sequence stretch derived from ANAU01000036 was divided into parts, and the protein blast search of NCBI [29] was used to decipher the function of its individual proteins. The consensus predictions from the tools used, were selected for further detailed analysis. Each of the prediction was verified by scanning the proteins for function specific sequence signatures, using the Scanprosite [30, 31] tool. Alternatively, conserved patterns were identified from the HAMAP seed alignment [24] and uniprot protein cluster —UniRef [32] of the said functional protein category.
Nucleotide sequence stretch of MCC0008 | Putative protein | Closest species | Prosite entry | HAMAP entry | UniRef entry | Sequence motif in MCC0008 | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
ANAU01000001 | Malate synthase | PS00510 | KDHSAGLNCGRWDYIF | |||||||||
ANAU01000001 | NAD kinase | MF_00361 | GGDG | |||||||||
ANAU01000001 | FabH | MF_01815 | AACAGF | |||||||||
ANAU01000001 | ATP dependent helicase | MF_01452 | LIA | |||||||||
ANAU01000001 | Peptide ABC transporter permease | PS50928 | TRVSLYIALLAAAIDLVIGVAYGGISAF | |||||||||
ANAU01000001 | spx transcription regulator | MF_01132 | IDEKRLQVGY, SCTSC | |||||||||
ANAU01000016 | Quinone oxidoreductase | PS01162 | VLIHAAAGGIGTT | |||||||||
ANAU01000020 | Zinc containing alcohol dehydrogenase | PS00059 | GHEFSGEV | |||||||||
ANAU01000020 | Transaldolase | PS01054 | GVTTNPSLV | |||||||||
ANAU01000020 | Phosphate uptake ABC transporter permease | PS50928 | RLCIETMASLPSIVVGLFGLLVFVTMTGW | |||||||||
ANAU01000020 | FAD dependent oxidoreductase | PS00862 | IRVVGSGH | |||||||||
ANAU01000020 | GerLA | UniRef50_Q93N70 | PAMYVALVSYHQGLI | |||||||||
ANAU01000020 | GerLB | UniRef50_Q93N69 | GTYLAW | |||||||||
ANAU01000033 | Phosphoglycerate kinase | PS00111 | RVDFNVP | |||||||||
ANAU01000033 | Uvr domain A | PS50151 | EKTIAKMEAEMKEAAKALDFERAA | |||||||||
ANAU01000033 | Uvr domain B | PS50151 | EKTIAKMEAEMKEAAKALDFERAA | |||||||||
ANAU01000033 | Central glycolytic genes regulator | UniRef90_A0RKS8 | SASLGMT | |||||||||
ANAU01000033 | Murein hydrolase export regulator | UniRef50_Q6HR39 | TTVAIASD | |||||||||
ANAU01000033 | Transcription regulator WhiA | UniRef50_O06975 | TLKELGEMV | |||||||||
ANAU01000033 | Autotransporter | UniRef90_B7HGW2 | LKREV | |||||||||
ANAU01000036 | Acetyl ornithine deacetylase | UniRef50_K0IAN5 | YGRG | |||||||||
ANAU01000036 | Acyl co-A dehydrogenase | PS00072 | ALTEPNAGSDALS | |||||||||
ANAU01000036 | Alpha beta hydrolase | MF_00832 | YDQR | |||||||||
ANAU01000036 | Aminotransferase classIII | PS00600 | FIADEVMTGLGRTGAW | |||||||||
ANAU01000036 | Aspartate semialdehyde dehydrogenase | PS01103 | MAATCVRVPVISGHS | |||||||||
ANAU01000036 | ATPase AAA | UniRef90_A0A0A0WLW6 | NFNEN | |||||||||
ANAU01000036 | Chloramphenicol acetyltransferase | UniRef90_A0REA1 | GETMG | |||||||||
ANAU01000036 | Choloylglycine hydrolase | UniRef90_Q81H11 | GVNEHG | |||||||||
ANAU01000036 | Citrate synthase | PS00480 | GFGHRVY | |||||||||
ANAU01000036 | Cold shock protein | UniRef50_Q45096 | NLIFADTS | |||||||||
ANAU01000036 | D-alanyl D-alanine carboxypeptidase | UniRef90_Q6HBP6 | SYAAGI | |||||||||
ANAU01000036 | Diguanylate cyclase | UniRef90_A0R9R1 | NITLA | |||||||||
ANAU01000036 | DNA binding protein |
PS50943 | LKTIREKEKLSLEKVSQLTGVSKTMIGQ | |||||||||
ANAU01000036 | Glucokinase | UniRef90_Q738U1 | YQLFSRYVVD | |||||||||
ANAU01000036 | Membrane protein | UniRef50_C3BJ03 | LGITV | |||||||||
ANAU01000036 | MFS transporter | PS50850 | MIRILAIVAFFVGLDSLLVAP | |||||||||
ANAU01000036 | Multidrug ABC transporter | PS50893 | GPTGSGKTTIINLLTRFYD | |||||||||
ANAU01000036 | NADH ubiquinone oxidoreductase | UniRef90_Q81K10 | ARGVYANA | |||||||||
ANAU01000036 | Serine threonine protein kinase | PS50011 | IGMGSYGVTYVV | |||||||||
ANAU01000036 | Threonyl tRNA synthetase | MF_00184 | GFYYD, GAYWRGD | |||||||||
ANAU01000046 | Fenl | UniRef90_Q6HIP8 | NTTYKKHELRAVW | |||||||||
ANAU01000052 | Nitrite/Nitrate response regulatory protein | PS50110 | SVLVVDDHVAVGLGTKALIEKYDDMNVEVVHDST | |||||||||
ANAU01000052 | ABC transporter | PS50893 | ILKQGETLGVVGKTGSGKTTLVRQ | |||||||||
ANAU01000062 | Non homologous End joining protein Ku | MF_01875 | WKG | |||||||||
ANAU01000062 | Spore coat cotJA | UniRef50_Q45536 | HSPQDPCPPIGKKYY | |||||||||
ANAU010000274 | Hypothetical protein |
Hence from the combined interpretation it is concluded that due to extensive genomic rearrangement,
The members of the Genus
The consensus predictions for the translated nucleotide sequence stretches of the draft genome of MCC0008 are summarized in Table 5. The putative proteins showed sequence specific characteristics of the predicted functions, as validated through sequence motifs in the prosite database /HAMAP family profile/UniRef. The sequence alignments of the MCC0008 proteins with the corresponding proteins of the Genus
8. Transcriptome analysis (BioProject PRJNA222597)
From transcriptome analysis (Figure 17 and Table 6), it is concluded that there is significant upregulation of sporulation genes, which can be due to the accumulation of poly-P in the bacterial cells [39]. The sporulation of
For nitrate accumulation, it is hypothesized that the nitrate accumulation occurs due to electrochemical gradient (Δp) [48]. In plants, typically vacuolar-type H+ATPases and H+pyrophosphatases (HPPases) catalyze a proton translocation over endomembranes to generate a Δp for solute transport and likely also nitrate transport [49]. Vacuolar-type ATPases also occur in plasma membranes of some Archaea, but they are rarely encountered in Bacteria [50, 51]. A vacuolar Hþ-pyrophophatase (hppA) and an uncommon Ca2+ translocating ATPase, may also contribute to generation of a Δp/ΔPh [52]. From transcriptome analysis it is revealed that there is 3.95-fold change in cation-transporting ATPase, which can be responsible for electrochemical gradient and nitrate accumulation.
Genes | Protein encoded | Fold Change |
log2Fold Change |
Function |
---|---|---|---|---|
9. Conclusion
The isolate MCC0008 is an extracellular protease, amylase, lipase, catalase, oxidase, phosphatase, and DNAse secreting strain which can form well-structured biofilm. It was isolated from a consortium developed from low-level radioactive waste treatment plant biomass. The strain is a novel species of genus
Acknowledgments
The research was conducted using different funds from Government of India namely Department of Atomic Energy under the BRNS scheme (consortium isolation and characterization); Indian Council of Agricultural Research under the NFBSFARA (Biofertilizer application, pure strain isolation); Ministry of Human Resource and Development under the FAST scheme (strain characterization, development of packed bed reactor for waste water treatment), University Grant Commission-Department of Atomic Energy (testing pure isolate as biofertilizer with and without seed irradiation). The authors acknowledge the financial assistance of all these granting agency. It also acknowledges the financial assistance of Department of Biotechnology, GOI for providing student fellowship The authors would like to thank Late Sourav Chakratorty, Arpan Pal and Abhishek Mitra for their technical assistance; Late Prof T K Das of Department of Anatomy, All India Institute of Medical Sciences, New Delhi, India for the TEM facility, Ms Nabanita Halder for extensively helping in the formatting of the manuscript.
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