TY - JOUR
AU - Glover, Chris N
AB - Abstract Biosorption of metals by microorganisms is a promising technology to remove accumulated non-process elements in highly recycled biorefinery process water. Removal of these elements would enable greater water reuse and reduce the environmental impact of effluent discharge. A model lignocellulosic ethanol biorefinery wastewater was created based on pulp mill effluent. This generated a wastewater with an environmentally realistic high loading of dissolved natural organic matter (900 mg/l), a potentially important factor influencing metal biosorption. Analysis of feedstock and pulp mill effluent indicated that Mn and Zn are likely to be problematic in highly recycled lignocellulosic ethanol biorefinery process water. Therefore, the growth of several bacteria and fungi from existing collections, and some isolated from pulp mill effluent were tested in the model wastewater spiked with Mn and Zn (0.2 mM). Wastewater isolates grew the best in the wastewater. Metal uptake varied by species and was much greater for Zn than Mn. A bacterium, Novosphingobium nitrogenifigens Y88T, removed the most metal per unit biomass, 35 and 17 mg Mn/g. No other organism tested decreased the Mn concentration. A yeast, Candida tropicalis, produced the most biomass and removed the most total metal (38 % of Zn), while uptake per unit biomass was 24 mg Zn/g. These results indicate that microorganisms can remove significant amounts of metals in wastewater with high concentrations of dissolved natural organic matter. Metal sorption by autochthonous microorganisms in an anaerobic bioreactor may be able to extend water reuse and therefore lower the water consumption of future biorefineries. Introduction Biofuel production is an increasingly important industry, helping to meet escalating energy demands while contributing to economic growth and energy independence. Depending on the source, biofuels generally pose less of an environmental hazard than fossil fuels in terms of green house gas emissions, a factor that also favours their adoption [20]. However, the production of biofuels requires large quantities of high-quality freshwater, a resource of increasingly limited supply [51]. The sustainability and economic feasibility of biofuels can be improved by minimizing water use in the refineries. One mechanism for this is to increase reuse of water within the plant. Water recycling is a common practice in refining processes; however, evidence from the pulp and paper industry shows that the build up of non-process elements, such as metals and salts, can limit the extent to which water can be recycled. These constituents cause problems such as scaling and corrosion, and may also impact product quality [21, 24]. In a biorefinery, a significant amount of water is often lost to evaporation, accelerating the concentration of the non-process elements. If the metals and salts could be removed, water reuse could be greatly extended, and the environmental sustainability of biofuels would be enhanced. Lignocellulosic biofuels are an increasing favourable option. By utilising woody by-products, such as sugar cane bagasse or corn stover, it eliminates the need for land-use change and also avoids direct competition with food resources [20, 45]. One potential lignocellulosic feedstock is wood. In a country such as New Zealand, this is the most common lignocellulosic biomass available, in the form of the pine, Pinus radiata. Sorption by microorganisms is a promising technology to remove heavy metals from water. It also has the advantage of being a more cost-effective treatment than physicochemical means [14, 49]. Metals bind to the carboxyl, hydroxyl, carbonyl, thio, amine and phosphate functional groups on biological membranes and on extracellular polymeric substances (EPS) exuded by microorganisms [14, 49]. Research on sorption of metals by microorganisms usually focuses on removing metal from simple aqueous solutions [14, 37], although some researchers have studied uptake in more complex systems such as actual wastewaters that contain natural organic matter (NOM) [9, 23, 37, 42]. NOM is a broad term referring to the organic constituents of the biomass, and in the case of wood includes lignins and polysaccharides. NOM is likely to be found in very high levels in process waters in lignocellulosic refineries, and may have complicating effects on metals removal, owing to its strong metal-binding capacities [11]. Recent findings have, however, shown that ternary complexes can form among the NOM, microorganisms and metals [5], which could enhance metal biosorption. The question of how microorganisms are capable of sorbing metals from water rich in NOM is also of fundamental interest in toxicology. It is generally recognized that NOM will bind metals, reducing bioavailability and thus toxicity to the organisms [11]. Hence, the biotic ligand model was developed [12] to incorporate the effects of NOM, pH and other cations into predictions of toxicity to aquatic wildlife. The processes governing the bioavailability of metals in a wastewater are likely similar to those in the natural environment and can provide insight into the bioavailability of the metals after they are released into the environment. Metals that can be taken up by a microorganism in a wastewater bioreactor may also be taken up by aquatic wildlife if the effluent is discharged untreated into waterways. The first objective of this study was to generate a model lignocellulosic ethanol biorefinery wastewater and identify metals likely to accumulate to levels of concern. The second objective was to compare the ability of a variety of organisms to grow in, and to remove metals from, a model lignocellulosic biorefinery wastewater. Such an organism will have potential for further investigation as a tool for metal extraction from lignocellulosic biorefinery wastewater. These objectives will allow two key questions to be addressed: (1) Are there organisms capable of growing in lignocellulosic biorefinery effluent? (2) Can microorganisms remove a significant amount of metals from an effluent with high NOM content (i.e. is this metal bioavailable to the microorganisms)? These are the first steps toward future work that will characterize metal uptake mechanisms and develop predictive models for investigating the influence of metal concentration, metal mixtures, NOM concentration and NOM composition on remediation success of lignocellulosic biorefinery effluent. Materials and methods Model wastewater manufacture and metal selection Although no full-scale lignocellulosic ethanol biorefinery currently exists, a report developed from pilot plant data indicates probable conditions of the wastewater [32]. The wastewater treatment system in this report includes anaerobic digestion followed by aerobic digestion. The aerobic treatment step was targeted as the locus for metals removal, with the rationale that the anaerobic step would be primarily aimed at carbon removal, so the aerobic step could be optimized for metals removal. A model wastewater was created by modifying a pulp mill effluent to resemble a lignocellulosic ethanol biorefinery effluent [32]. The pulp mill effluent was from a New Zealand thermo-mechanical mill that produces pulp from P. radiata. The metal content of the pulp mill effluent was measured by nitric acid digestion and inductively coupled mass spectrometry (ICP-MS) analysis (Table 1, RJ Hill Labs, Hamilton) according to APHA method 3125B and USEPA 200.8 [2, 10], whereas total metals in raw P. radiata wood chips were analysed by APHA method 3125B with boiling HNO3 digestion according to APHA method 3030E [2]. The metal concentrations in these samples were used to select metals of interest for this study. On the basis of these data (see “Results and discussion” section) Mn and Zn were chosen as the metals of greatest relevance. Nutrient analyses were also performed on the effluent, to assist with building a characteristic model wastewater. Total ammoniacal-N was measured via phenol/hypochlorite colorimetry (NH4-N = NH4+-N + NH3-N). Total Kjeldahl nitrogen (TKN) was measured by sulphuric acid digestion with copper sulphate catalyst, then phenol/hypochlorite colorimetry. Nitrate-N + nitrite-N were measured as total oxidized nitrogen using automated cadmium reduction and flow injection analysis. Total nitrogen was calculated as TKN + nitrate-N + nitrite-N. Total phosphorus was measured as dissolved reactive phosphorus using molybdenum blue colorimetry. Total carbon (TC) was measured by catalytic oxidation to CO2 and IR detection, and total inorganic carbon (TIC) was determined by acidification to CO2, purging and IR detection. Total organic carbon (TOC) was calculated as TC-TIC. Pinus radiata (n = 1) and pulp mill effluent (n = 3) constituents, and calculated model wastewater composition . P. radiata wood chips (mg/kg) . P. radiata pulp mill effluent (mg/l) . Model wastewater (mg/l) . Metals/salts Aluminium 27 0.11 0.11 Arsenic <0.10 0.023–<0.021 0.023–<0.021 Barium 2.7 0.13 0.13 Boron 1.7 0.14 0.14 Cadmium 0.019 <0.0011 <0.0011 Calcium 470 54 54 Chromium 0.37 <0.011 <0.011 Copper 0.91 0.012–<0.0011 0.012–<0.0011 Iron 19 <0.42 <0.42 Lanthanum 0.010 <0.0021 <0.0021 Lead 0.031 0.0051 0.0051 Magnesium 140 9.4 9.4 Manganese 29 0.38 0.38 Potassium 870 45 51 Sodium <50 60 196 Zinc 9.2 0.34 0.34 Nutrients and other Total nitrogen 2.9 23 Ammoniacal-N 0.048 20 Nitrate-N + nitrite-N 0.047 0.047 Kjeldahl N (TKN) 2.8 23 Phosphorus 3.2 5.5 Dissolved organic carbon (DOC) 890 1,010 Acetic acid 64 464 Ethanol 18 118 NaHCO3 (buffering) 498 pH 5.4 5.4 . P. radiata wood chips (mg/kg) . P. radiata pulp mill effluent (mg/l) . Model wastewater (mg/l) . Metals/salts Aluminium 27 0.11 0.11 Arsenic <0.10 0.023–<0.021 0.023–<0.021 Barium 2.7 0.13 0.13 Boron 1.7 0.14 0.14 Cadmium 0.019 <0.0011 <0.0011 Calcium 470 54 54 Chromium 0.37 <0.011 <0.011 Copper 0.91 0.012–<0.0011 0.012–<0.0011 Iron 19 <0.42 <0.42 Lanthanum 0.010 <0.0021 <0.0021 Lead 0.031 0.0051 0.0051 Magnesium 140 9.4 9.4 Manganese 29 0.38 0.38 Potassium 870 45 51 Sodium <50 60 196 Zinc 9.2 0.34 0.34 Nutrients and other Total nitrogen 2.9 23 Ammoniacal-N 0.048 20 Nitrate-N + nitrite-N 0.047 0.047 Kjeldahl N (TKN) 2.8 23 Phosphorus 3.2 5.5 Dissolved organic carbon (DOC) 890 1,010 Acetic acid 64 464 Ethanol 18 118 NaHCO3 (buffering) 498 pH 5.4 5.4 Model wastewater manufacture and metal selection are described in the “Materials and methods” section Open in new tab Pinus radiata (n = 1) and pulp mill effluent (n = 3) constituents, and calculated model wastewater composition . P. radiata wood chips (mg/kg) . P. radiata pulp mill effluent (mg/l) . Model wastewater (mg/l) . Metals/salts Aluminium 27 0.11 0.11 Arsenic <0.10 0.023–<0.021 0.023–<0.021 Barium 2.7 0.13 0.13 Boron 1.7 0.14 0.14 Cadmium 0.019 <0.0011 <0.0011 Calcium 470 54 54 Chromium 0.37 <0.011 <0.011 Copper 0.91 0.012–<0.0011 0.012–<0.0011 Iron 19 <0.42 <0.42 Lanthanum 0.010 <0.0021 <0.0021 Lead 0.031 0.0051 0.0051 Magnesium 140 9.4 9.4 Manganese 29 0.38 0.38 Potassium 870 45 51 Sodium <50 60 196 Zinc 9.2 0.34 0.34 Nutrients and other Total nitrogen 2.9 23 Ammoniacal-N 0.048 20 Nitrate-N + nitrite-N 0.047 0.047 Kjeldahl N (TKN) 2.8 23 Phosphorus 3.2 5.5 Dissolved organic carbon (DOC) 890 1,010 Acetic acid 64 464 Ethanol 18 118 NaHCO3 (buffering) 498 pH 5.4 5.4 . P. radiata wood chips (mg/kg) . P. radiata pulp mill effluent (mg/l) . Model wastewater (mg/l) . Metals/salts Aluminium 27 0.11 0.11 Arsenic <0.10 0.023–<0.021 0.023–<0.021 Barium 2.7 0.13 0.13 Boron 1.7 0.14 0.14 Cadmium 0.019 <0.0011 <0.0011 Calcium 470 54 54 Chromium 0.37 <0.011 <0.011 Copper 0.91 0.012–<0.0011 0.012–<0.0011 Iron 19 <0.42 <0.42 Lanthanum 0.010 <0.0021 <0.0021 Lead 0.031 0.0051 0.0051 Magnesium 140 9.4 9.4 Manganese 29 0.38 0.38 Potassium 870 45 51 Sodium <50 60 196 Zinc 9.2 0.34 0.34 Nutrients and other Total nitrogen 2.9 23 Ammoniacal-N 0.048 20 Nitrate-N + nitrite-N 0.047 0.047 Kjeldahl N (TKN) 2.8 23 Phosphorus 3.2 5.5 Dissolved organic carbon (DOC) 890 1,010 Acetic acid 64 464 Ethanol 18 118 NaHCO3 (buffering) 498 pH 5.4 5.4 Model wastewater manufacture and metal selection are described in the “Materials and methods” section Open in new tab Immediately after collection this effluent was filtered with Whatman grade 3 filter paper (6 μm), then with Whatman GF/C glass microfibre (1.2 μm) and frozen in 2-l aliquots. The filtration of the raw effluent did not dramatically alter the concentrations of any metals, except Al (data not shown). To prepare the model wastewater, an aliquot was thawed, autoclaved and centrifuged at 5,000×g for 10 min. To each litre of the pulp mill effluent base, 400 μl acetic acid and 127 μl ethanol were added. The chosen amounts were based on concentrations of these constituents predicted before and after anaerobic treatment in a lignocellulosic ethanol pilot plant [32], to account for either of these locations as a likely position for an aerobic metal removal step within a biorefinery. To maintain a biological oxygen demand/nitrogen/phosphorous ratio of 100/3.5/0.6 and the original pH (5.4) of the effluent, NH4Cl (77.5 mg/l), K2HPO4 (13.0 mg/l) and NaHCO3 (498 mg/l) were added. Finally, the solution was 0.45-μm syringe filtered, to provide a homogenous model wastewater and confine this study to the dissolved phase only. Organism collection and isolation Organisms were sought in various culture collections around New Zealand. Some organisms were selected on the basis of known metal tolerance and suitability for mesophilic aerobic conditions. Other organisms, such as Pseudomonas putida mt-2, were included because they are easy to culture in a variety of conditions. Three species of algae, bacteria and mould and one species of yeast were initially collected and subjected to a preliminary test. Algae, bacteria and yeast that did not grow sufficiently to visibly ‘cloud’ the model wastewater after 48 h in an illuminated (70 μmol photon/m2/s) shaking incubator set to 36 °C were not tested further. Moulds were initially tested under similar conditions for 2 weeks at 25 °C. As many of these organisms showed poor growth in the model wastewater, organisms were also isolated from two New Zealand pulp mill wastewater sources specifically for this study. The first source of isolates was effluent from a mill that produces both bleached and unbleached kraft pulp. Organisms were isolated on Phytagel (Sigma) solid media, pH 5, at 35 °C and amended with high amounts of Mn and Zn (1 g/kg each) to attempt to select for highly metal-tolerant species. The second source of isolates was a 5-l sequencing batch reactor (SBR) maintained with the dissolved oxygen no less than 43 % of saturation, 35 °C and feeding at a rate of 3 l/day. The feed for the SBR was a mixture of bleached chemi-thermo-mechanical pulping and thermo-mechanical pulping effluent that had been partially predigested in a moving bed biofilm reactor, supplemented with 20 mg/l ethanol and 125 mg/l acetic acid. Mn and Zn were added in the same concentrations as those spiked in the model wastewater (0.20 mM, 11 mg/l Mn and 13 mg/l Zn). Weekly samples were taken from the SBR, and organisms were isolated by serial dilution in the model wastewater with Mn and Zn (0.2 mM), at 36 °C. The four isolates from wastewater were identified by extracting the DNA with ZR soil microbe DNA MiniPrep™ kit (Zymo, Irvine, CA, USA). For bacterial species, PCR was used to amplify the 16S rDNA with the primer set 27F/1492R according to Lane [26]. DNA clean-up was carried out with a GFX™ PCR DNA kit (Amersham, GE Healthcare, Rydalmere, NSW, Australia). Sequencing was performed at Massey Genome Service (http://genome.massey.ac.nz/). For fungi, the internal transcribed spacer (ITS) regions of the rDNA were amplified using the primer set ITS1F/ITS4 [6]. PCR and sequencing were carried out as described by McCarthy et al. [31]. The raw sequences were edited with Sequence Scanner v1.0 (Applied Biosystems, Mulgrave VIC, Australia) and the sequences (405–835 bp) were identified by comparison to existing sequences using BLAST (http://blast.ncbi.nlm.nih.gov/Blast.cgi). The microbe was identified as the match with the highest sequence homology (≥99 %) and sequences were submitted to the GenBank database. Accession numbers for the isolates and the final list of organisms tested for survival and metal uptake in the model wastewater are described in Table 2. Organisms subjected to screening assay in the model wastewater . Organism . Source . Reference/accession no.a . Bacteria Novosphingobium nitrogenifigens Y88T Pulp & paper mill effluent bioreactor [1] Sphingobium scionensis WP01T Hydrocarbon-contaminated sawmill soil [28] Pseudomonas putida mt-2 Common soil microbe [53] Klebsiella pneumoniae Pulp & paper mill effluent JQ640571 Yeasts Saccharomyces cerevisiae Commercial source Sporopachydermia lactativora Pulp & paper mill effluent JQ640569 Candida tropicalis Pulp mill effluent bioreactor JQ640572 Moulds Ochroconis gallopava Pulp & paper mill effluent JQ640570 . Organism . Source . Reference/accession no.a . Bacteria Novosphingobium nitrogenifigens Y88T Pulp & paper mill effluent bioreactor [1] Sphingobium scionensis WP01T Hydrocarbon-contaminated sawmill soil [28] Pseudomonas putida mt-2 Common soil microbe [53] Klebsiella pneumoniae Pulp & paper mill effluent JQ640571 Yeasts Saccharomyces cerevisiae Commercial source Sporopachydermia lactativora Pulp & paper mill effluent JQ640569 Candida tropicalis Pulp mill effluent bioreactor JQ640572 Moulds Ochroconis gallopava Pulp & paper mill effluent JQ640570 aIf the organism was obtained from an existing collection, a citation on the isolation or characterization is provided. For organisms isolated for this study the GenBank accession number is provided Open in new tab Organisms subjected to screening assay in the model wastewater . Organism . Source . Reference/accession no.a . Bacteria Novosphingobium nitrogenifigens Y88T Pulp & paper mill effluent bioreactor [1] Sphingobium scionensis WP01T Hydrocarbon-contaminated sawmill soil [28] Pseudomonas putida mt-2 Common soil microbe [53] Klebsiella pneumoniae Pulp & paper mill effluent JQ640571 Yeasts Saccharomyces cerevisiae Commercial source Sporopachydermia lactativora Pulp & paper mill effluent JQ640569 Candida tropicalis Pulp mill effluent bioreactor JQ640572 Moulds Ochroconis gallopava Pulp & paper mill effluent JQ640570 . Organism . Source . Reference/accession no.a . Bacteria Novosphingobium nitrogenifigens Y88T Pulp & paper mill effluent bioreactor [1] Sphingobium scionensis WP01T Hydrocarbon-contaminated sawmill soil [28] Pseudomonas putida mt-2 Common soil microbe [53] Klebsiella pneumoniae Pulp & paper mill effluent JQ640571 Yeasts Saccharomyces cerevisiae Commercial source Sporopachydermia lactativora Pulp & paper mill effluent JQ640569 Candida tropicalis Pulp mill effluent bioreactor JQ640572 Moulds Ochroconis gallopava Pulp & paper mill effluent JQ640570 aIf the organism was obtained from an existing collection, a citation on the isolation or characterization is provided. For organisms isolated for this study the GenBank accession number is provided Open in new tab Organism screening assay A 24-h batch culture screening assay was used to evaluate the ability of each organism to grow in the model wastewater. The effect of metals was tested by comparison to treatments without metals added. Tests were conducted at 36 °C, as many bioreactors in pulp and paper mills operate under mesophilic conditions [18] and those in lignocellulosic biorefineries are also likely to [32]. Seven treatment groups (each with 4 replicates) consisted of: Difco nutrient broth (Becton–Dickinson and Co.) un-inoculated (negative control); nutrient broth (positive control); the model wastewater described above un-inoculated (model wastewater negative control); the model wastewater; the model wastewater plus 0.2 mM Mn (11 mg/l); the model wastewater plus 0.2 mM Zn (13 mg/l); and a final treatment of only the effluent base of the model wastewater without added nutrients to check for possible negative effects of the additions on growth. One day prior to the assay, an aliquot of the model wastewater and the liquid inoculum was prepared using aseptic technique. The inoculum was started by transferring a colony from a nutrient agar plate to 50 ml of nutrient broth with 10 μl acetic acid and 3 μl ethanol added (pH ca. 5.5), to roughly simulate conditions of the model wastewater. Exceptions were the commercial yeast and the fungus, which were dissolved or pulverised, respectively, in sterile Milli-Q water just before inoculation. Two of the organisms, P. putida and S. scionensis, did not grow well in the desired inoculum media. The buffering agents (NH4Cl, K2HPO4, NaHCO3) for the model wastewater were added to the inoculum media in similar proportions to grow P. putida. S. scionensis did not grow in either of those conditions or nutrient broth at 36 °C. Therefore, nutrient broth at 33 °C was used to grow the S. scionensis inoculum. Each assay was initiated with the following steps carried out in a laminar flow or biohazard hood. Model wastewater or nutrient broth (50 ml) was measured into a 250-ml Erlenmeyer flask. Flasks were previously cleaned by soaking in 10 % HNO3 overnight then rinsing at least six times with distilled H2O. Then, the metal stock (0.5 ml) was added to appropriate flasks. The stocks were made from chloride salts of the metals (Sigma-Aldrich, Fluka, St. Louis, Mo., USA) and acidified to pH less than 2 with HCl. Separate flasks were used for analytical confirmation of the initial metal concentrations. These flasks contained un-inoculated model wastewater and were preserved with HNO3 immediately after the start of the test. The inoculum was diluted to achieve an optical density (OD) measurement of 0.3 at 600 nm and 0.5 ml was added to each flask. Flasks were covered with Breathseal plate sealer (Greiner Bio-one, Frickenhausen, Germany) and then placed in a shaking (100 rpm) incubator maintained at 36 ± 1 °C. After 24 h, flasks were removed from the incubator. The contents of one flask per treatment were streaked on nutrient agar plates to check the purity of the organism and confirm the sterility of the negative controls. Then a 4-ml aliquot was pipetted from each flask into cuvettes for OD measurement at 600 nm. Another 4-ml aliquot was taken for flow cytometry (FC) analysis. The remaining solution (about 38 ml) was weighed and the pH was measured. This solution was then centrifuged at 2,000×g for 10 min to the pellet biomass and the supernatant was poured off. The supernatants of the inoculated treatments of the model wastewater were acidified to pH less than 2.0 with HNO3. If a species grew well in the presence of metals (OD > 0.3) the acidified supernatant was sent for metal analysis by ICP-MS. The biomass pellet was twice washed with 3 ml distilled H2O and centrifuged. The pellet was then lyophilised and weighed to obtain dry biomass weight. Metal uptake was determined by calculating the absolute metal mass in solution from the weight of the solution in order to avoid error from changes in concentrations caused by evaporation. Uptake was calculated by subtracting the metal mass in the supernatant from the metal mass in flasks set up specifically for the measurement of the initial concentrations. Separate controls were run with metals and without microorganisms to check for precipitation. A very small precipitate was observed after centrifugation. Acid digest and analysis of the precipitate indicated that it contained 1–4 % of the total metal added. Flow cytometry analysis To facilitate cell counting using flow cytometry (FC), cells were stained with SYTO® green fluorescent nucleic acid stains according to the manufacturer’s instructions (Molecular Probes™, USA). SYTO 9 was used to stain bacteria, whereas SYTO BC was used to stain yeast. Cell counts are all semiquantitative as the staining of all cells and the accuracy of counts were not verified for each species. Flow cytometry cannot be performed easily with the filamentous fungus, so this analysis was not done for the fungal species. Samples (1.0 ml) were stained with a 50 μM SYTO® dye solution in phosphate buffered saline (PBS, pH 7.2). A FACSVantage SE flow cytometer (BD Biosciences, USA), which was equipped with DiVa electronics and software, a 488-nm laser powered at 300 mW and a helium neon laser providing 633-nm excitation were used to perform sample analysis. The instrument sheath fluid was PBS delivered through a 70-μm nozzle at 131 kPa. Samples were generally diluted to ca. 1 × 106 cells/ml in PBS prior to fluorescent dye staining. TruCount™ fluorescent beads (BD, USA) were included with samples (ca. 5,000 beads per sample tube) to facilitate quantitation. For all sample analyses, the event threshold was set on the 90° scatter (side scatter, SSC) channel at a value of 200. SYTO dye fluorescence was measured on the FC FL1 channel (530/30 nm). Single-parameter histograms and dual-parameter dot plots of the various channel events were monitored and used for setting gates. SYTO-stained events could then be discriminated on SSC versus FL1 fluorescence dotplots by highlighting these in different colours using the DiVa software. The red-fluorescent FL4 channel (660/20 nm), together with the FL1 channel, was used for isolation of TruCount™ bead fluorescence from labelled-cell fluorescence. The total number of measured events per FC analysis was predetermined by the operator’s ability to visually resolve populations, enabling manual construction of gates around populations of interest. The total number of measured events was generally 10,000, at a rate of 1,000 events/s. The number of cells for each identified population was calculated using the following formula: cells/ml = (cell count × bead count × sample dilution factor)/(actual beads/ml). Metal analysis ICP-MS was performed at the Department of Chemistry, University of Canterbury, Christchurch, NZ. The samples were diluted 20× with 1 % HNO3 and were analysed for Mn and Zn by ICP-MS (Agilent 7500 cx). Quality assurance and control procedures included analysis of two spiked samples for each 20 samples. The average per cent recovery with standard deviation was 112 ± 9 % for both Zn and Mn. Statistics Statistical analyses were performed using R [38]. Analysis of variance (ANOVA) followed by Tukey’s HSD test was used to find significant differences between individual treatment groups (p < 0.05). Results and discussion Model wastewater manufacture Biosorption has significant potential as a technology for removing non-process metals from future biorefinery process water, a mechanism that will extend reuse of process water in the plant. Accordingly, a model effluent from a future lignocellulosic ethanol biorefinery was created to test the possibility of using microorganisms to sorb accumulated metals. Pulp mill effluent was used as the base of the model wastewater because it was the best surrogate organic matter available for a biorefinery that would process P. radiata. The effluent provided a relatively high NOM concentration (DOC of 890 mg/l) to represent a highly recycled process water. Table 1 shows the composition of this pulp mill effluent base and the final model wastewater. The N and P were relatively low (2.9 mg/l total N and 3.2 mg/l PO4 3−) in the mill effluent used as the base of the model wastewater, and in order to provide sufficient nutrients for microbial growth additional N (as NH4Cl) and P (as K2HPO4) were added. The pilot plant report [32] did not contain predictions of N and P concentrations in the effluent, but did suggest that these nutrients would need to be added in large amounts to the anaerobic digester, and it would be likely that some would remain in the effluent from this digester. Effluent samples from the pilot plant had a pH of 4.9–5.4 similar to that in the model wastewater (pH 5.4). Metal selection Metals accumulating in pulp mill process waters are believed to come primarily from the wood [21]. Therefore P. radiata wood chips and pulp mill effluent from a plant that processes P. radiata were used to indicate the metals most likely to accumulate in process water from a lignocellulosic ethanol biorefinery that utilizes this feedstock. Mn and Zn were the heavy metals in highest concentrations in the pulp mill effluent, and the Mn concentration was the highest of the metals in the P. radiata wood chips (followed by Al > Fe > Zn; Table 1). Mn and Zn were also among the heavy metals in highest concentrations in historical data from another pulp mill that primarily processes P. radiata [52]. Much of the focus on removal of non-process metals from closed or partly closed cycle pulp and paper mills has focused on transition metals, mainly Mn and Fe because they interfere with hydrogen peroxide bleaching [16, 27]. Kanto Öqvist et al. [22] compared metal concentrations in the process waters from a mill with part closure to those from a mill with full closure and found the average Mn concentrations were 1.45 and 8 mg/l, respectively. They also found that many wastewater constituents including metals, organic acids and nutrients were about tenfold higher in the fully closed mill compared to the partially closed mill. This factor of 10 can be used to estimate the metal concentrations in highly recycled process water. Mn is problematic in pulp mills not only because it interferes with whitening reagents as described above, but also because it builds up on plumbing as scale [21, 35]. Additionally, if Mn levels in effluent leaving the mill are high enough they can harm aquatic wildlife downstream. Mn is toxic to the model aquatic crustacean Ceriodaphnia dubia, having a medial lethal (LC50) concentration of 9.1 mg/l after 48 h. Zn, like Mn, is essential for life, but it can also damage freshwater ecosystems at much lower concentrations. A Zn concentration of 0.039 mg/l is toxic to the alga Selenastrum capricornutum, causing a 50 % inhibitory effect on cell division (EC50) after 48 h [13]. On the basis of their relative levels in lignocellulosic effluents, and associated negative impacts on mill performance and the aquatic environment, Mn and Zn were chosen as the metals of greatest relevance to the potential bioremediation of a lignocellulosic biofuel biorefinery. These two metals were added to the model wastewater in equimolar amounts (as described in the “Materials and methods” section, 11 mg/l Mn and 13 mg/l Zn) based on their concentrations in the mill effluent (Table 1) and using the rough concentration factor of 10 from Kanto Öqvist et al. [22] to estimate the accumulation of metals in highly recycled process water. Organism screening Two critical factors are required for a model metal-remediating organism for a lignocellulosic ethanol effluent metal-removing bioreactor: the organism needs to be able to live and grow in the wastewater (with or without supplementary nutrients) and needs to be metal tolerant. Many organisms obtained from existing culture collections did not grow after 48 h in the wastewater, so they were not subject to further screening. This included the algae Scenedesmus sp. and Chlorella sp., species isolated from municipal wastewater and found to be tolerant of Zn [34], and Microcystis wesenbergii which is responsible for algal blooms in freshwater systems [50]. A number of moulds also failed to grow in the model wastewater. Trichoderma viride, Trametes versicolor and Antrodia xantha [17, 25] have the ability to grow on chromate copper arsenate-treated wood and were thus hypothesized as potential bioremediators of metal-enriched wastewaters. Clearly organisms adapted to a wastewater environment were needed. Therefore, to obtain a metal-tolerant organism that would grow in the model wastewater, organisms were isolated from metal-enriched wastewaters. This included organisms specifically isolated for the purposes of this study (C. tropicalis, S. lactativora, K. pneumoniae and O. gallopava), and some that had been previously isolated from similar effluents (N. nitrogenifigens [1] and S. scionensis [28]). To test the relative efficacy of our choice of organisms we also examined the utility of more common model bacteria (P. putida) and yeast (S. cerevisiae). These have the advantage in that they are already well characterized and easy to culture. The two “non-effluent” organisms, the brewer’s yeast (S. cerevisiae) and the bacteria P. putida, grew poorly in the model wastewater (Fig. 1a). Only the organisms isolated from similar wastewaters exhibited significant growth (OD > 0.2) in the model wastewater: N. nitrogenifigens, K. pneumoniae, C. tropicalis, S. lactativora and O. gallopava. All species grew well (OD > 1.0) in the nutrient broth positive control (not shown), except for N. nitrogenifigens and S. scionensis. S. scionensis is another wastewater isolate [28] that could grow in the wastewater but only at lower temperatures (<33 °C; not shown). For brevity, biomass measurements are shown only for the species that grew well (Fig. 1b) since the biomass data exhibited similar trends to growth. The only species severely affected by the metals was K. pneumoniae, for which growth was reduced by 85 % upon the addition of Zn, whereas Mn only decreased growth by about 25 %. O. gallopava also showed a 25 % reduction in biomass with either of the metals. Growth was always greater in the model wastewater compared to growth in the effluent without the nutrient addition, showing the necessity of this adjustment. Fig. 1 Open in new tabDownload slide Growth of various organisms indicated by optical density (a) and biomass of selected species (b) after 24 h in model wastewater (W) with no metal, 0.2 mM Mn (M) or 0.2 mM Zn (Z) added, or in the pulp mill effluent base of model wastewater (E). Solutions were inoculated (+) with the indicated species or not inoculated (−). Asterisks indicate differences (p < 0.05) for Tukey’s comparisons of the treatments with metal against the inoculated wastewater without added metal. Each bar represents the mean of 4 replicates ± standard deviation Clearly four of the wastewater isolates—N. nitrogenifigens, C. tropicalis, S. lactativora and O. gallopava—have characteristics that enable them to survive and grow in the tested metal-enriched wastewater. N. nitrogenifigens was isolated from a pulp mill effluent bioreactor by other researchers [1]. C. tropicalis has been studied as the saccharification and fermentation organism for generating bioethanol from rice straw [36], and could therefore function as both the fermenting organism and as part of the wastewater treatment. This organism is also potentially pathogenic so care would need to be taken if it is used on large scale [3]. Less is known about the yeast S. lactativora. This yeast does not have the ability to ferment sugars, although it will utilise glucose, xylose and ethanol as carbon sources [41]. The fungus, O. gallopava, has been found in areas of high temperature and low pH, including hot springs [54], thermal effluents of nuclear power reactors [40], wood pulp samples [46] and is also known to be pathogenic [54]. It may have unique traits for inhabiting these extreme environments, which may enable it to live in a wide range of conditions. Flow cytometry analysis FC analysis offers a different way to measure growth, by providing actual counts of the number of cells. Cell counting using FC showed similar major trends as the biomass and OD data, but there were important differences, primarily in the results from the Zn treatments. Figure 2 shows the FC results of the three best growing species. The FC results indicated that the Zn treatment resulted in lower numbers of yeast cells relative to the Mn and the ‘no metals added’ treatments (Fig. 2). This was true for both yeast species. The OD measurements were also lower in the Zn treatments, suggesting less growth. However, the biomass measurements (Fig. 1b) did not show these differences. This could be due to higher production of EPS in Zn treatments. EPS secretion in response to a metal stressor has previously been shown in yeast [33], and in fish, mucus secretion has been noted in response to Zn exposure [15]. EPS would increase the biomass without increasing the cell number. Also, EPS would likely increase clumping, which would also appear as fewer cells in FC. The role of EPS in metal uptake is not clear as it has been found to either enhance metal sorption [48] or to hinder sorption, presumably by forming clumps of cells and decreasing surface area available for binding [47]. Fig. 2 Open in new tabDownload slide Changes in flow cytometry cell counts of selected species from metal exposure. Cells were grown in the model wastewater (W) with no metal, 0.2 mM Mn (M) or 0.2 mM Zn (Z) added. Solutions were inoculated (+) with the indicated species or not inoculated (−). Asterisks indicate differences (p < 0.05) for Tukey’s comparisons of the treatments with metal against the inoculated wastewater without added metal. Each bar represents the mean of 4 replicates ± standard deviation An alternative explanation for the lower number of cells with constant biomass in Zn treatments could be that the cells were larger. In the yeast S. cerevisiae, the cells quickly take up Zn and store large quantities in the vacuole [29]. This may increase cell size. Additionally, the FC forward scatter parameter (FSC) is often directly proportional to cell size, whereas SSC indicates internal granularity or complexity [43]. FSC intensity from the main population of S. lactativora increased from 20,000 to about 50,000, as shown in representative plots (Fig. 3). A similar doubling of intensity was seen in the plots for C. tropicalis. This suggests that the cells are becoming larger and more complex from the added Zn, supporting the suggestions from the FC counts and biomass data that there were fewer, larger cells in the Zn-exposed yeast species. For N. nitrogenifigens though, the FC analysis and OD measurements did not show these changes. None of these changes were obvious after exposure to Mn (not shown). Fig. 3 Open in new tabDownload slide Representative plots displaying an increased side scatter intensity (SSC) and forward scatter intensity (FSC) from exposure to Zn for S. lactativora (Sl) and C. tropicalis (Ct), but not for N. nitrogenifigens (Nn) Metal sorption Metal uptake varied significantly by species (Fig. 4). C. tropicalis took up the greatest amount of either metal from solution, 38 % of the Zn (5.0 mg/l, Fig. 4a), followed closely by the bacteria, N. nitrogenifigens which removed 32 % of the Zn (4.2 mg/l). The other two species removed less Zn, 14–16 % (1.8–2.1 mg/l). The two yeasts studied had markedly different uptake patterns despite similar changes observed via FC following Zn exposure. C. tropicalis removed about threefold more Zn than S. lactativora. The spores of the genus Sporopachydermia have a relatively thick cell wall with a unique ultrastructure compared to other yeasts, a property that gives this yeast its name [41]. Tests were done using vegetative cells of this species not spores, but the cells may retain some unique properties that have a role in the lower Zn sorption observed in this organism. C. tropicalis, a common yeast which is part of the normal human flora, has previously been found to be resistant to heavy metals [4, 19, 39]. N. nitrogenifigens was isolated from effluent that was unlikely to have metals in high concentrations, although it was isolated on solid media with 5 mM NiCl [1]. Fig. 4 Open in new tabDownload slide Total metal uptake (a) and metal uptake per unit biomass (b) by N. nitrogenifigens (Nn), S. lactativora (Sl), C. tropicalis (Ct), O. gallopava (Og). Initial metal concentrations were 0.2 mM. Each point represents the mean of 4 replicates ± standard deviation. Data points sharing the same letter are not significantly different from each other on the basis of Tukey’s multiple comparisons test (p < 0.05) The yeast C. tropicalis took up the most total metal from solution (Fig. 4a), but the bacteria N. nitrogenifigens, which produced only two-thirds of the biomass of the C. tropicalis (Fig. 1b), took up almost the same amount of Zn. This made it the most efficient biosorber in our experimental system on a per unit biomass basis (Fig. 4b). N. nitrogenifigens removed 35 mg Zn/g biomass and 17 mg Mn/g biomass, whereas C. tropicalis, the next best biosorber, removed 24 mg Zn/g biomass. This could be due to the higher surface area of the smaller cells, or because of differences in the cell wall composition. Mn uptake in general was much lower than that of Zn (Fig. 4a). Only N. nitrogenifigens accumulated a significant amount, accounting for 20 % of the total Mn. Lower sorption of Mn compared to other metals had been observed before and is consistent with the binding strength predicted by the Irving–Williams series [7, 30], which has been used to indicate binding affinity of metals to the functional groups on the cell surface. In another study, Pseudomonas aeruginosa also sorbed more Zn than Mn, with a maximum biosorption capacity of 77.5 mg Zn/g biomass and 38.2 mg Mn/g biomass, at pH 7.0 [44]. In this study, N. nitrogenifigens removed 35 mg Zn/g biomass and 17 mg Mn/g biomass. Metal biosorption is thought to occur primarily by metal binding to functional groups on the cell membranes, such as the carboxyl group, which depends on pH [14]. As the pH increases more deprotonated sites become available for binding by metal ions with a positive charge, increasing the metal binding capacity. The pH of the wastewater was initially low and remained low in the wastewater negative control (un-inoculated), but the pH increased to approximately 8.4 for all organisms that grew well (OD > 0.3) (Fig. 5), favouring metal uptake. The final pH was mildly correlated to Zn uptake (r2 = 0.65 based on % uptake, r2 = 0.52 based on uptake per unit biomass). However there were not sufficient statistical differences among the pH values to make a definitive correlation. Fig. 5 Open in new tabDownload slide The pH after 24 h in wastewater inoculated (+) with the indicated species or not inoculated (−). Organisms were grown in model wastewater (W) with no metal, 0.2 mM Mn (M) or 0.2 mM Zn (Z) added. Each bar represents the mean of 4 replicates ± standard deviation. Tukey’s multiple comparisons tests were performed comparing data within the treatments groups only. Data points with the same letters are not significantly different from each other (p < 0.05) In addition to adsorption of metals to the cell membrane, cells may absorb metal inside the cell, which may enhance the removal capacity from the medium. At the same time, high intracellular concentrations of metals can be toxic. Some organisms have the ability to actively detoxify heavy metal ions and either store them in the periplasm or precipitate them in the form of bicarbonates and hydroxides. In P. putida active efflux of Zn and binding in the periplasm have been observed [8]. Metal tolerance would seem to be an asset for a metal-remediating organism, but the mechanism by which an organism copes with toxic amounts of metals determines if it will be a good remediator. If an organism simply effluxes the undesirable metal back outside the cell and into the culture media it will not be useful for metal removal. On the other hand, an organism that stores the metals inside the cell would be ideal. The high NOM in this model wastewater could have inhibited metal removal by the microorganisms. Organisms consumed the carbon in the acetic acid and ethanol in the model wastewater, while the more recalcitrant NOM from the pulp mill effluent was likely to remain throughout the exposure, and would continue to have an impact on metal speciation, by binding free metal ions. There was approximately ten times as much NOM in the initial effluent base of the wastewater as there was organism biomass at the end of the test. Still, N. nitrogenifigens and C. tropicalis removed 30–40 % of the Zn, indicating that a large proportion of the metal was bioavailable. This suggests that these organisms are very effective at sequestering metals, outcompeting NOM for a large portion of the available metal. Bioavailability is a key concept to consider in terms of the remediating organism, but also is an important factor for organisms in any receiving environment. High bioavailability in such waters, particular freshwaters with limited competitive ions and complexing ligands, is likely to lead to high sensitivity of susceptible aquatic wildlife [12]. This is a problem that could be ameliorated with microbial biosorption bioreactors, which may sequester metals in a non-bioavailable form. C. tropicalis and N. nitrogenifigens were naturally occurring wastewater isolates, and were also the most successful of the tested organisms in terms of being potential remediators of metal-enriched wastewaters. This suggests that any autochthonous species capable of growing in a bioreactor digesting metal-rich effluent should be similarly successful in sorbing metals. Any organisms that grow in the conditions with elevated metal concentrations would obviously need some mechanism to resist metal toxicity. Conversely, any allochthonous, hyperaccumulating organism will probably only grow in a specific set of conditions and may need to be maintained in a monoculture free of other organisms that could out compete the hyperaccumulator. This system would require a great deal of maintenance, whereas a reactor growing autochthonous microbes would be easier to maintain. Indeed, other researchers have found that naturally occurring microbes were useful for metal removal in the environments they were found in [23, 37, 39]. This study shows that uptake does vary by organism and metal, so bioreactor studies will be done in the future to ascertain that uptake is similar in the mixed culture of a reactor as it is for the individual model organisms N. nitrogenifigens and C. tropicalis. Nevertheless, investigation of individual model organism responses to metal-enriched effluents is useful in that it permits an understanding of the mechanisms of uptake, and bioremediation potential. Such experiments could be used to optimize metal removal in a bioreactor scenario. In a biorefinery, water will be used in various stages in the refining process and will likely be collected into one treatment system with a solids removal step, followed by anaerobic digestion of the liquids. The resulting effluent stream could then be treated with a polishing step optimized to remove metals using microbial biomass, before the water is reused [18]. The results presented here suggest that at least a third of the dissolved Zn could be removed in such a polishing bioreactor, even in waters with high concentrations of metal-binding NOM. This treatment may be sufficient to keep Zn accumulation under control in a system that has relatively low metal inputs and continuously reuses the water. However, metal removal is dependent on several factors not explored here and depends on the metal. As seen here, removal of Mn is more challenging than Zn. Finally, the biomass with the metals will need to be removed from the reactor and treated for safe disposal. Recovery of the metals from the biomass is possible [49], but whether or not this is necessary or practical depends on the value or toxicity of the metal(s). Zn for example is toxic to algae, but biomass with Zn could be a nutrient supplement for animals. If the metals cannot be separated from the biomass, the bioreactors will have provided the benefit of concentrating the metal into a much smaller volume for disposal. Conclusions Biorefinery process water recycling is likely to be limited by accumulation of dissolved salts and metals. Zn and Mn are the metals most likely to accumulate to levels of concern in a biorefinery processing P. radiata. N. nitrogenifigens and C. tropicalis were able to remove 30–40 % of the Zn in a model lignocellulosic biofuel biorefinery effluent, despite the high dissolved NOM concentration. Any autochthonous species (such as N. nitrogenifigens and C. tropicalis) are likely to be the easiest to maintain, and will be the most practical choice for a bioreactor, assuming that species in a mixed culture will sorb metals with similar success to the autochthonous species investigated in this study. Bioreactor studies will be done to validate that the removal can be maintained over extended periods in continuous culture. Such metal-sorbing bioreactors could be used in a biorefinery to maintain water quality and enable greater reuse of the process water, thus enhancing the sustainability of the biofuel. Future work will also be directed towards factors that affect metal uptake, including different types and amounts of NOM, so that a model could be used to optimize removal in a bioreactor. Acknowledgments We thank Sally Gaw and Rob Stainthorpe (University of Canterbury) for metals analysis; Matt Stott and Chris Daughney (Institute of Geological and Nuclear Sciences, GNS) for valuable scientific input; Phil Novis (Landcare Research) for providing Scenedesmus sp. and Chlorella sp.; Susie Wood (Cawthron Research) for providing Microcystis wesenbergii and other algae; Tripti Singh (Scion, Rotorua) for providing the Trichoderma viride, Trametes versicolor and Antrodia xantha; Ben MacDonald and Katrin Walbert (Scion). Funding provided by the Foundation for Research, Science and Technology (FRST) programme CO4 × 0801. Conflict of interest This research was funded by the Foundation of Research, Science and Technology (FRST). The funding agency had no scientific input into the study, and the authors declare that they have no conflict of interest. Ethical standard All experiments were conducted in accordance with New Zealand law, with particular attention to the Ministry of Agriculture and Forestry/Environmental Risk Management Authority policies regarding PC1 and PC2 containment facilities. References 1. Addison SL , Foote SM, Reid NM, Lloyd-Jones G Novosphingobium nitrogenifigens sp. nov., a polyhydroxyalkanoate-accumulating diazotroph isolated from a New Zealand pulp and paper wastewater Int J Syst Evol Microbiol 2007 57 11 2467 2471 10.1099/ijs.0.64627-0 Google Scholar Crossref Search ADS PubMed WorldCat 2. American Public Health Association (APHA) (2005) Inductively coupled plasma/mass spectrometry (ICP/MS) method 3125B. In: Standard methods for the examination of water and wastewater, 21st ed. APHA, Washington 3. Barns SM , Lane DJ, Sogin ML, Bibeau C, Weisburg WG Evolutionary relationships among pathogenic Candida species and relatives J Bacteriol 1991 173 7 2250 2255 Google Scholar Crossref Search ADS PubMed WorldCat 4. Berdicevsky I , Duek L, Merzbach D, Yannai S Susceptibility of different yeast species to environmental toxic metals Environ Pollut 1993 80 1 41 44 10.1016/0269-7491(93)90007-B Google Scholar Crossref Search ADS PubMed WorldCat 5. Borrok D , Aumend K, Fein JB Significance of ternary bacteria-metal-natural organic matter complexes determined through experimentation and chemical equilibrium modeling Chem Geol 2007 238 1–2 44 62 10.1016/j.chemgeo.2006.10.013 Google Scholar OpenURL Placeholder Text WorldCat Crossref 6. Bruns T , Gardes M Molecular tools for the identification of ectomycorrhizal fungi: taxon-specific oligonucleotide probes for suilloid fungi Mol Ecol 1993 2 4 233 242 10.1111/j.1365-294X.1993.tb00013.x Google Scholar Crossref Search ADS PubMed WorldCat 7. Burnett P-GG , Handley K, Peak D, Daughney CJ Divalent metal adsorption by the thermophile Anoxybacillus flavithermus in single and multi-metal systems Chem Geol 2007 244 3–4 493 506 10.1016/j.chemgeo.2007.07.006 Google Scholar OpenURL Placeholder Text WorldCat Crossref 8. Choudhury R , Srivastava S Mechanism of zinc resistance in Pseudomonas putida strain S4 World J Microbiol Biotechnol 2001 17 2 149 153 10.1023/A:1016666000384 Google Scholar Crossref Search ADS WorldCat 9. Crane RS , Barton P, Cartmell E, Coulon F, Hillis P, Judd SJ, Santos A, Stephenson T, Lester JN Fate and behaviour of copper and zinc in secondary biological wastewater treatment processes: I. Evaluation of biomass adsorption capacity Environ Technol 2010 31 7 705 723 10.1080/09593330.2010.481314 Google Scholar Crossref Search ADS PubMed WorldCat 10. Creed JT, Brockhoff CA, Martin TD (1994) Determination of trace elements in waters and wastes by inductively coupled plasma—mass spectrometry. Method 200.8. Revision 5.4. United States Environmental Protection Agency (USEPA), Cincinnati 11. de Schamphelaere KAC , Vasconcelos FM, Tack FMG, Allen HE, Janssen CR Effect of dissolved organic matter source on acute copper toxicity to Daphnia magna Environ Toxicol Chem 2004 23 5 1248 1255 10.1897/03-184 Google Scholar Crossref Search ADS PubMed WorldCat 12. Di Toro DM , Allen HE, Bergman HL, Meyer JS, Paquin PR, Santore RC Biotic ligand model of the acute toxicity of metals. 1. Technical basis Environ Toxicol Chem 2001 20 10 2383 2396 10.1002/etc.5620201034 Google Scholar Crossref Search ADS PubMed WorldCat 13. Franklin NM , Adams MS, Stauber JL, Lim RP Development of an improved rapid enzyme inhibition bioassay with marine and freshwater microalgae using flow cytometry Arch Environ Contam Toxicol 2001 40 4 469 480 10.1007/s002440010199 Google Scholar PubMed OpenURL Placeholder Text WorldCat 14. Gadd GM Biosorption: critical review of scientific rationale, environmental importance and significance for pollution treatment J Chem Technol Biotechnol 2009 84 1 13 28 10.1002/jctb.1999 Google Scholar Crossref Search ADS WorldCat 15. Glover CN , Hogstrand C In vivo characterisation of intestinal zinc uptake in freshwater rainbow trout J Exp Biol 2002 205 1 141 150 Google Scholar PubMed OpenURL Placeholder Text WorldCat 16. Gu Y , Edwards L Prediction of metals distribution in mill processes, Part 2: fiber line metals profiles Tappi J 2004 3 2 13 20 Google Scholar OpenURL Placeholder Text WorldCat 17. Guillén Y , Navias D, Machuca Á Tolerance to wood preservatives by copper-tolerant wood-rot fungi native to south-central Chile Biodegrad 2009 20 1 135 142 10.1007/s10532-008-9207-1 Google Scholar Crossref Search ADS WorldCat 18. Habets L , Driessen W Anaerobic treatment of pulp and paper mill effluents—status quo and new developments Water Sci Technol 2007 55 6 223 230 10.2166/wst.2007.232 Google Scholar Crossref Search ADS PubMed WorldCat 19. Harrison JJ , Rabiei M, Turner RJ, Badry EA, Sproule KM, Ceri H Metal resistance in Candida biofilms FEMS Microbiol Ecol 2006 55 3 479 491 10.1111/j.1574-6941.2005.00045.x Google Scholar Crossref Search ADS PubMed WorldCat 20. Hill J , Nelson E, Tilman D, Polasky S, Tiffany D Environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels Proc Natl Acad Sci U S A 2006 103 30 11206 11210 10.1073/pnas.0604600103 Google Scholar Crossref Search ADS PubMed WorldCat 21. Jemaa N , Thompson R, Paleologou M, Berry RM Non-process elements in the kraft recovery cycle, Part I: sources, levels and process effects Pulp Pap Can 1999 100 9 T292 T296 Google Scholar OpenURL Placeholder Text WorldCat 22. Kanto Öqvist C , Kurola J, Pakarinen J, Ekman J, Ikävalko S, Simell J, Salkinoja-Salonen M Prokaryotic microbiota of recycled paper mills with low or zero effluent J Ind Microbiol Biotechnol 2008 35 10 1165 1173 10.1007/s10295-008-0396-8 Google Scholar Crossref Search ADS PubMed WorldCat 23. Kaushik S , Juwarkar A, Malik A, Satya S Biological removal of Cr(VI) by bacterial isolates obtained from metal contaminated sites J Environ Sci Health Part A 2008 43 4 419 423 Google Scholar Crossref Search ADS WorldCat 24. Kiiskia E The effects of water circuit closure in a pulp mill Pap Puu 1994 76 9 574 579 Google Scholar OpenURL Placeholder Text WorldCat 25. Kim G-H , Son D-S, Kim J–J Fungi colonizing Douglas Fir in cooling towers: identification and their decay capabilities Wood Fiber Sci 2005 37 4 638 642 Google Scholar OpenURL Placeholder Text WorldCat 26. Lane D Stackebrandt E, Goodfellow M 16S/23S rRNA sequencing Nucleic acid techniques in bacterial systematics 1991 Chichester Wiley 115 175 Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 27. Lastra A , Gómez D, Romero J, Francisco JL, Luque S, Álvarez JR Removal of metal complexes by nanofiltration in a TCF pulp mill: technical and economic feasibility J Membr Sci 2004 242 1–2 97 105 10.1016/j.memsci.2004.05.012 Google Scholar OpenURL Placeholder Text WorldCat Crossref 28. Liang Q , Lloyd-Jones G Sphingobium scionense sp. nov., an aromatic hydrocarbon-degrading bacterium isolated from contaminated sawmill soil Int J Syst Evol Microbiol 2010 60 413 416 10.1099/ijs.0.008144-0 Google Scholar Crossref Search ADS PubMed WorldCat 29. MacDiarmid CW , Milanick MA, Eide DJ Induction of the ZRC1 metal tolerance gene in zinc-limited yeast confers resistance to zinc shock J Biol Chem 2003 278 17 15065 15072 10.1074/jbc.M300568200 Google Scholar Crossref Search ADS PubMed WorldCat 30. Mantoura RFC , Dickson A, Riley JP The complexation of metals with humic materials in natural waters Estuar Coast Mar Sci 1978 6 4 387 408 10.1016/0302-3524(78)90130-5 Google Scholar Crossref Search ADS WorldCat 31. McCarthy JK , Hood IA, Brockerhoff EG, Carlson CA, Pawson SM, Forward M, Walbert K, Gardner JF Predicting sapstain and degrade in fallen trees following storm damage in a Pinus radiata forest For Ecol Manag 2010 260 9 1456 1466 10.1016/j.foreco.2010.07.044 Google Scholar Crossref Search ADS WorldCat 32. Merrick & Company (1998) Wastewater treatment options for the biomass-to-ethanol process. Project no. 19013104, task 6. Report to the National Renewable Energy Laboratory 33. Mikes J , Siglova M, Cejkova A, Masak J, Jirku V The influence of heavy metals on the production of extracellular polymer substances in the processes of heavy metal ions elimination Water Sci Technol 2005 52 10–11 151 156 Google Scholar PubMed OpenURL Placeholder Text WorldCat 34. Novis P , Halle C, Wilson B, Tremblay L Identification and characterization of freshwater algae from a pollution gradient using rbcL sequencing and toxicity testing Arch Environ Contamin Toxicol 2009 57 3 504 514 10.1007/s00244-009-9312-0 Google Scholar Crossref Search ADS WorldCat 35. Nurmesniemi H , Pöykiö R, Perämäki P, Kuokkanen T The use of a sequential leaching procedure for heavy metal fractionation in green liquor dregs from a causticizing process at a pulp mill Chemosphere 2005 61 10 1475 1484 10.1016/j.chemosphere.2005.04.114 Google Scholar Crossref Search ADS PubMed WorldCat 36. Oberoi HS , Vadlani PV, Brijwani K, Bhargav VK, Patil RT Enhanced ethanol production via fermentation of rice straw with hydrolysate-adapted Candida tropicalis ATCC 13803 Process Biochem 2010 45 8 1299 1306 10.1016/j.procbio.2010.04.017 Google Scholar Crossref Search ADS WorldCat 37. Prigione V , Zerlottin M, Refosco D, Tigini V, Anastasi A, Varese GC Chromium removal from a real tanning effluent by autochthonous and allochthonous fungi Bioresour Technol 2009 100 11 2770 2776 10.1016/j.biortech.2009.01.002 Google Scholar Crossref Search ADS PubMed WorldCat 38. R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org 39. Rehman A , Anjum M Multiple metal tolerance and biosorption of cadmium by Candida tropicalis isolated from industrial effluents: glutathione as detoxifying agent Environ Monit Assess 2011 174 1 585 595 10.1007/s10661-010-1480-x Google Scholar PubMed OpenURL Placeholder Text WorldCat 40. Rippon J , Gerhold R, Heath M Thermophilic and thermotolerant fungi isolated from the thermal effluent of nuclear power generating reactors: dispersal of human opportunistic and veterinary pathogenic fungi Mycopathologia 1980 70 169 179 10.1007/BF00443028 Google Scholar Crossref Search ADS PubMed WorldCat 41. Rodrigues de Miranda L A new genus: Sporopachydermia Antonie Van Leeuwenhoek 1978 44 3 439 450 10.1007/BF00394320 Google Scholar PubMed OpenURL Placeholder Text WorldCat 42. Santos A , Judd S The fate of metals in wastewater treated by the activated sludge process and membrane bioreactors: a brief review J Environ Monit 2010 12 1 110 118 10.1039/b918161j Google Scholar Crossref Search ADS PubMed WorldCat 43. Shapiro H Practical flow cytometry 2003 4 New York Wiley-Liss Google Scholar Crossref Search ADS Google Preview WorldCat COPAC 44. Silva RMP , Rodriguez AA, De Oca J, Moreno DC Biosorption of chromium, copper, manganese and zinc by Pseudomonas aeruginosa AT18 isolated from a site contaminated with petroleum Bioresour Technol 2009 100 4 1533 1538 10.1016/j.biortech.2008.06.057 Google Scholar Crossref Search ADS PubMed WorldCat 45. Somerville C , Youngs H, Taylor C, Davis SC, Long SP Feedstocks for lignocellulosic biofuels Sci 2010 329 5993 790 792 10.1126/science.1189268 Google Scholar Crossref Search ADS WorldCat 46. Suihko M-L , Hoekstra E Fungi present in some recycled fibre pulps and paperboards Nordic Pulp Pap Res J 1999 14 202 206 10.3183/NPPRJ-1999-14-03-p199-203 Google Scholar Crossref Search ADS WorldCat 47. Tourney J , Ngwenya BT, Mosselmans JWF, Magennis M Physical and chemical effects of extracellular polymers (EPS) on Zn adsorption to Bacillus licheniformis S-86 J Colloid Interface Sci 2009 337 2 381 389 10.1016/j.jcis.2009.05.067 Google Scholar Crossref Search ADS PubMed WorldCat 48. Tourney J , Ngwenya BT, Mosselmans JWF, Tetley L, Cowie GL The effect of extracellular polymers (EPS) on the proton adsorption characteristics of the thermophile Bacillus licheniformis S-86 Chem Geol 2008 247 1–2 1 15 10.1016/j.chemgeo.2007.09.012 Google Scholar OpenURL Placeholder Text WorldCat Crossref 49. Vijayaraghavan K , Yun Y-S Bacterial biosorbents and biosorption Biotechnol Adv 2008 26 3 266 291 10.1016/j.biotechadv.2008.02.002 Google Scholar Crossref Search ADS PubMed WorldCat 50. Visser P, Ibelings B, Mur L, Walsby A, Huisman J, Matthijs H (2005) The ecophysiology of the harmful cyanobacterium Microcystis. In: Huisman J, Matthijs H, Visser P (eds) Harmful Cyanobacteria, vol 3. Aquatic Ecology Series. Springer, Netherlands, pp 109–142. doi:10.1007/1-4020-3022-3_6 51. Vörösmarty CJ , Green P, Salisbury J, Lammers RB Global water resources: vulnerability from climate change and population growth Sci 2000 289 5477 284 288 10.1126/science.289.5477.284 Google Scholar Crossref Search ADS WorldCat 52. Wang H , Gielen GJH, Judd MC, Stuthridge TR, Blackwell BG, Tomer MD, Pearce SH Treatment efficiency of land application for thermo-mechanical pulpmill (TMP) effluent constituents Appita J 1999 52 5 383 386 Google Scholar OpenURL Placeholder Text WorldCat 53. Worsey MJ , Williams PA Metabolism of toluene and xylenes by Pseudomonas putida (arvilla) mt-2: evidence for a new function of the TOL plasmid J Bacteriol 1975 124 7 13 Google Scholar Crossref Search ADS PubMed WorldCat 54. Yarita K , Sano A, Murata Y, Takayama A, Takahashi Y, Takahashi H, Yaguchi T, Ohori A, Kamei K, Miyaji M, Nishimura K Pathogenicity of Ochroconis gallopava isolated from hot springs in Japan and a review of published reports Mycopathologia 2007 164 3 135 147 10.1007/s11046-007-9034-7 Google Scholar Crossref Search ADS PubMed WorldCat © Society for Industrial Microbiology 2012 This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) © Society for Industrial Microbiology 2012
TI - Metal biosorption in lignocellulosic biofuel biorefinery effluent: an initial step towards sustainability of water resources
JF - Journal of Industrial Microbiology and Biotechnology
DO - 10.1007/s10295-012-1129-6
DA - 2012-09-01
UR - https://www.deepdyve.com/lp/oxford-university-press/metal-biosorption-in-lignocellulosic-biofuel-biorefinery-effluent-an-72fyCaVq1m
SP - 1345
EP - 1356
VL - 39
IS - 9
DP - DeepDyve
ER -