JOURNAL OF FERMENTATION AND BIOENGINEERING VOI. 72, No. 1, 2 0 - 2 5 . 1991
Medium Optimization by an Orthogonal Array Design for the Growth of Methanosarcina barkeri ROBERTO GAIGER SILVEIRA, TOSHIHIDE KAKIZONO, SUSUMU TAKEMOTO, NAOMICHI NISHIO, ASD SHIRO NAGAI*
Department of Fermentation Technology, Faculty of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 724, Japan Received 7 February 1991/Accepted 18 April 1991 Optimization of the medium composition for Methanosarcina barkeri growing on methanol (8 g//) was carried out by two different methods, (i) "one-at-a-time" and (ii) analysis of marginal means (ANOMM) in an orthogonal array experimental design. The second method showed to be very effective in the improvement of the medium composition capable of increasing the gas production rate (CH4 + C02) over 1.3 and 2.0 times when compared with the "one-at-a-time" optimized medium and the basal medium, respectively.
The results revealed that in the optimized medium obtained by the orthogonal array method, the methane production rate of M. barkeri was significantly enhanced in comparison with those observed in the original basal medium and the "one-at-a-time" method medium.
Recently, the studies of methanogenic bacteria have attracted a lot of interest because of its vital role in anaerobic digestion (1, 2), the importance of methane production as biofuel (3), and the possibility of its utilization for the production of vitamin B12 compounds (4-6), 5-aminolevulinic acid (7, 8) and N A D P H regeneration biocatalyst (9). Numerous studies were carried out to investigate the influence of medium components (e.g. nitrogen, phosphate, metals, vitamins, etc.) upon the growth of methanogenic bacteria (10-12). However, we could not find any studies on the overall optimization of the medium composition of methanogenic bacteria for the enhancement of the gas production rate and/or the increase of the cell yield. Several methods for the optimization of medium composition such as the Graeco-Latin square technique (13, 14), Box and Wilson method (15), and Rosenbrock's method (16) have been reported, however, these methods are impractical when a large number of components in the medium are taken into account since too many combinations have to be considered to optimize the medium composition. Among quality control professionals and statisticians, Taguchi's method for process improvement has raised a renewed interest in the use of fractional factorial designs (17). When a large number of factors has to be considered, this method applies highly fractional orthogonal array designs, and makes it possible to examine a large number of combinations in a relatively few trials. Based on this method, in this work, an attempt was made to demonstrate how a fractional factorial experimental design could be used for the optimization of a multicomponent medium for the growth of a methanogen. The method applied was the "analysis of marginal means" (ANOMM) (18) in an orthogonal array (orthogonal resolution III, symmetrical fractional factorial) experimental design (19, 20), and was compared with the optimization method of "one-at-a-time" (21). Optimization of medium composition for the growth of Methanosarcina barkeri Fusaro on methanol as chosen as an example since this strain was known to be a potent producer of vitamin BIz compounds (4-6) and an effective biocatalyst for the conversion of methanol to methane.
MATERIALS AND METHODS Microbial strain Methanosarcina barkeri strain Fusaro (DSM 804) obtained from the Deutsche Sammlung yon Mikroorganismen (G6ttingen, Germany) was used throughout this study. The culture was maintained by frequent transfer into a methanol basal medium. Culture conditions All manipulations of medium and cultures were carried out in an O2-free atmosphere of N2 gas. Medium preparation and culture techniques were the same as reported previously (22). The cultures were incubated statically at 37°C in 125 ml serum vials containing 50 ml of medium (initial pH 6.5 to 6.6). The inoculation was 49/00 (v/v) of a late log phase culture grown on the methanol (8.0 g//) basal medium. Culture medium The basal medium used for the optimization (23) was as follows (per liter of deionized water): imidazole, 2.72g; K2HPO4, 0.348g; KH2PO4, 0.227 g; MgSO4.7H20, 0.5 g; NH4C1, 0.5 g; CaC12.2H:O, 0.25g; NaC1, 2.25g; FeSO4.7H20, 2mg; COC12.6H20, 0.3 rag; NiC12.6HzO, 0.06 mg; L-cysteine. HC1, 0.3 g; vitamin solution, 10.0 ml; trace element solution without Na: EDTA, 3.0ml; Ti (III)-citrate, 0.075 mM and methanol, 8.0g. Analytical procedure Due to the linear relationship between cell growth and gas production (22, 24), cell growth was estimated by the gas (CH4+CO2) production which was measured by a liquid displacement system (4) after passing the evolved gas through a saturated sodium chloride solution. Methanol concentration in the culture broth was determined by gas chromatography as described previously (25). Cell mass was calculated from the cellular protein content determined by a dye binding method (26) as described by Silveira et al. (6). Evaluation of gas production rate, cell yield and gas yield The gas production rates were estimated for the first 35-h culture and at the exponential phase of growth. The cell yield (g/g) and gas yield (mmol/g) were obtained
* Corresponding author. 20
VoL. 72, 1991
M E D I U M O P T I M I Z A T I O N F O R M. B A R K E R I
from cell mass and evolved gas produced per methanol consumed, respectively, when methanol was completely utilized in the batch culture. Experimental design Eleven components of the medium: K, P (K2HPO4 and KH2PO4), Mg (MgSO4-7H20), N (NH4C1), Ca (CaC12.2H20), Na (NaC1), S (L-cysteine. HC1), Fe (FeSO4.7HzO), Co (COC12.6H20), Ni (NiC12. 6H20), vitamin solution, and trace element solution were selected as factors for the medium optimization. Fe, Co and Ni were chosen to be optimized separately from the trace element solution, since they play important roles on the formation of three tetrapyrroles, which are significant cofactors in the metabolism of methanol to methane (8). The objective of the optimization was to maximize the gas production rate, and furthermore, to examine the influence on the cell yield. Two optimization methods were used: one-at-a-time One component (factor) at 5 -7 different concentrations was tested without changing the other components in the basal medium, and then the effect of the target component on the rate of gas production was evaluated. The concentration of each factor capable of enhancing the gas production rate was selected, and then the same procedure was repeated for the remaining factors until all variables had been considered. Thus, the optimum medium as composed by selecting the optimum level of each factor. search method based on orthogonal array If there are interactions among the factors, the "one-at-a-time" method may miss the optimal settings because it does not thoroughly explore all possible combinations of the eleven TABLE
1.
factors. For example, when considering three levels for each factor, an impossible number of 311 (177, 147) experiments would have to be carried out to explore all possible combinations. Therefore a method entitled "the analysis of marginal means" (ANOMM) (18) was applied here for an 11 factor -3 level orthogonal main-effect experimental design (19,20). This consists of 33 (27) runs (experiments) as shown in Table 1. An orthogonal main-effect design (Table 1) was constructed by writing all the possible treatment combinations of the complete 33 factorials in the first three factors (F1, F2, F3 in Table 1). Then, the other factors (F4 to FI0 were generated by adding these three columns within the ternary system as described by Dey (19) as follows: F 4 ~ - F I T F 2 , F s = F I + F 3 , F6=Fz+F3, FT=2FI+F2, Fs=2FI+F3,
F9=FI+F2+F3,
Flo=2FI+F2+F3,
and
FII
= 2 F 2 + F 3. Thus, all three levels occur the same number of times for all eleven factors, showing that orthogonal arrays are fractional factorial designs which minimize the number of trial runs whilst keeping "the pairwise balancing property" (18). Values for the lower (L0), middle (L0 and higher (L2) levels for each factor were selected for the first experimental unit (Table 2). Each value for L~ was based on the optimized medium determined by the "one-at-a-time" method. To determine the "optimum" level for each factor, the "analysis of marginal mean" (ANOMM) (18) was applied as follows: the averages of the gas production rate (GPrL) at each level, Lo, Ll and L2 were expressed as GPro, GPrl and GPr2 and the"optimum" level was decided on the basis of the highest GPrL. Then, the following strategy as applied to formulate the
Eleven factors, three levels o r t h o g o n a l array experimental design
Runs
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
21
Fl
F2
F3
F4
Factors ( c o m p o n e n t s ) a F5 F6 F7
Fs
F9
FI0
F11
N
K,P
Ca
Mg
Fe
Ni
Na
Co
Vi
Mi
Cys
0b 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
0 0 0 1 1 1 2 2 2 0 0 0 1 1 1 2 2 2 0 0 0 1 1 1 2 2 2
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2
0 0 0 1 1 1 2 2 2 1 l 1 2 2 2 0 0 0 2 2 2 0 0 0 1 1 1
0 1 2 0 1 2 0 1 2 1 2 0 1 2 0 1 2 0 2 0 1 2 0 1 2 0 1
0 1 2 1 2 0 2 0 1 0 1 2 1 2 0 2 0 1 0 1 2 1 2 0 2 0 1
0 0 0 1 1 1 2 2 2 2 2 2 0 0 0 1 1 1 1 1 1 2 2 2 0 0 0
0 1 2 0 1 2 0 1 2 2 0 1 2 0 1 2 0 1 1 2 0 1 2 0 1 2 0
0 1 2 1 2 0 2 0 1 1 2 0 2 0 1 0 1 2 2 0 1 0 1 2 1 2 0
0 1 2 1 2 0 2 0 1 2 0 1 0 1 2 1 2 0 1 2 0 2 0 1 0 1 2
0 l 2 2 0 1 1 2 0 0 1 2 2 0 1 1 2 0 0 1 2 2 0 1 1 2 0
a Factors: N, NH4C1; K,P, K2HPO 4 and KH2PO4; Mg, MgSO4.7H20; Ca, CaCI2.2H20; Na, NaC1; Fe, FeSO4.7H20; Co, CoCIz.6H20; Ni, NiCIz. 6H20; Vi, vitamin solution; Mi, trace element solution; Cys, L-cysteine. HC1. The factors were assigned for each c o l u m n in a randomized order. b Levels: 0, lower level (L0); 1, middle level (L0; 2, higher level (L2).
22
SILVEIRA ET AL.
J. FERMENT. BIOENG.,
next experimental unit: (i) For each factor, if the "optimum" level is L0, then take L0 as Lj, L~ as L2 and a new value for L0 is specified as the lower value. (ii) If the "optimum" level is L2 then take L2 as L~, L~ as L0 and a new value for L2 is specified as the higher value. (iii) If the "optimum" level is L~, and GPr~ > 1.05 GPr~L(average of the gas production rates for the 27 runs), or GPr0, GPr2 < 0.95 GPrav, then L~ is not modified, and a shorter interval between L0, L~ and Lj, L2 is arbitrarily specified. (iv) If the "optimum" level is Ll, and condition (iii) is not satisfied, then the values for L0, L~ and L2 are not modified for the factor. (v) A new experiment unit consisting of 27 runs (Table 1) with the newly specified levels for each factor is carried out. When condition (iv) described above is satisfied for all 11 factors, the optimum medium composition has been established, and a confirmation experiment is carried out.
m g / l order). The same effect was found in previous results (4, 8). A strong decrease of methanogenesis at low NH4CI concentrations (Fig. la) was also found by Murray and Zinder on Methanosarcina strain TM-1 (11). Boone and Mah (10), studying the effect of calcium and magnesium on the growth of Methanosarcina mazei S-6, found the presence of interaction between these two components of the medium by showing that the optimum concentration of Ca to attain the highest specific growth rate depended upon the concentration of Mg applied, and viceversa. To further optimize the "one-at-a-time" medium, mutual effects (interaction) among multiple factors on the gas production rate were examined by an orthogonal fractional factorial design. To reduce the runs (experiments) to a reasonable number, a resolution III (i.e. allow confounding among main-effect and two-factors interaction) orthogonal array design (18, 19) was selected. This design makes it possible to examine a large number of variations in a relatively few trials. However, due to the low resolution of the method, it does not provide information on which components of the growth medium are interacting. "Search method based on orthogonal array" Applying the medium composition obtained by the "one-ata-time" optimization method as a middle level (L~) of the first experimental unit, the values for L0 and L2 were selected as shown in Table 2. For a better understanding of how the ANOMM was ap-
RESULTS AND DISCUSSION
"One-at-a-time" method Figure 1 shows the effect of each medium component on the gas production rate of M. barkeri. Based on this result, the "one-at-a-time" optimum medium was obtained (see Table 4). CoC12- 6 H 2 0 , F e S O 4 - 7 H 2 0 and NiCI 2. 6HzO (Fig. l f, i and j, respectively) were found to be the components with the largest effect on the methanogenesis of M. barkeri (e.g.
~-t~oO4 (g/0 8.0
135
~
3.1
4.65
a
8 ~
4.0
0.0
V
5.0 NH4CI (g//)
0.0
~
10.0 0.0
I
1.0
~
I
i
i
I
2.0 K2,HPO4 (g//)
3.0 0.0
0.2 0.4 CaCI2,2H20 (g//)
0.6 0.0
10
2.0
30
McJSO4,FH20
(g/t)
8.0
~5 0.0
0.0
4.0
8.0
2.0 4.0 6.0 COCI2,6H20 (rag//)
0,0
NaCI (g/t)
20
40 60 80 Vitamin soln.
lO 20 Mineral soln.
(mIlt)
(mR/t)
8.0
J
i
!~
4.0
0.0
J
I
,
I
10 2o Fc~O4o7H2~
(rag/t)
i
I
i
0.20
I
t
0.40
NiCI2"6H20 (mg//)
I
0.60
0.0
1.0
2.0
3.0
CysteineoHCI (g/0
FIG. 1. Effects of medium components on the gas production rate of M. barkeri strain Fusaro. Culture conditions: pH 6.5 to 6.6; temperature 37°C, without shaking. Except for the target component, the other medium composition was the same as in the basal medium. Gas production rate was estimated at the exponential phase of growth.
MEDIUM OPTIMIZATION FOR M. BARKERI
Voz. 72, 1991
23
TABLE 2. Selected levels (component concentrations) of the first experimental unit on the medium optimization by the "search method based on orthogonal array" for the growth of M. barkeri Levelsa
Factor (component) NH4CI K2HPO4 KH2PO4 MgSO4.7H20 NaC1 CaCI2.2HzO FeSO4.7H20 CoClz- 6H20 NiCI2.6HzO Vitamin solution Mineral solution L-Cysteine • HC1
g/l g/l g/l g/l g/l g/l mg/l mg/l mg/l ml/l ml/l g/l
L0
LI
L2
0.5 0.18 0.12 0.5 3.0 0.13 5.0 0.15 0.06 10 6 0.05
1.0 0.35 0.23 1.0 4.5 0.25 10.0 0.29 0.12 20 12 0.10
1.5 0.70 0.45 2.0 6.0 0.5 15.0 0.58 0.24 30 18 0.20
-20
.
.
1
~
.
.
.
N
K, P Mg 0
Na
Ca
Fe
Co
Ni
Vit. Min.
S
N
K,P
Mg
Na
Ca
Fe
Co
Ni
Vit
Min
S
N
K,P
Mq
Na
Ca ~
Fe
Co
Ni
Vit
Min
S (4)
~
o
-10 6
go .c
a Lo, Lower level; LI, middle level; L2, higher level. -6
10
plied for the estimation of the "optimum" level of each factor, and how to construct the strategy to define the next experimental unit, in the case of two of the eleven factors, cysteine and COC12.6H20 (Co), the results from the first experimental unit (27 runs) are depicted in Fig. 2. The h~&h_er level (L2) of cysteine (i.e. 0.2 g//) gave the higher GPrL (Fig. 2a, inlet), therefore to satisfy condition (ii), (see Materials and Methods), in the second experimental unit, 0.2 g/l was taken as the middle level (L0, 0.1 g/l as the lower level (L0), and a new value was specified for L2, (0.3 g//) (data not shown). In the case of CoC1:. 6H20, conditions of (i) and (ii) were satisfied (Fig. 2b inlet), however, a
8
-20
• 005
, 01
0.2
2 3 4 5 6 7 8 9101112131415161718192021222324252627
Runs (experiments)
8
E
b)
8
I -10
'
N
K,P
Mg
K,P
Mg
'
Na
Ca
Fe
Co
Ni
Vil
Min
S
Na
Ca
Fe
Co
Ni
Vit
Min
S
v
-8
N
FIG. 3. Comparison of the GPrL (GPr0, GPq, GPr2), for each factor of the growth medium expressed as 6 (for the definition, see Fig. 2). The numbers expressed the experimental unit. For culture conditions, see Fig. 1. Symbols: i~, lower level (L0); • , middle level (L0; [], higher level (L2).
smaller interval between the levels must be specified in order to satisfy condition (iii). The new levels selected for the second experimental unit were 0.17, 0.29 and 0.46 mg/l, for L0, LI, L2, respectively (data not shown). Figure 3 shows the comparison of GPr0, G P q , GPrz with each of the 11 factors of the basal medium. A total of 5 experimental units were required to obtain the optimized medium (Table 3), that is, for the "optimum" level of all 11 factors to be settled at the LI level (Fig. 3-(5)). For every TABLE 3.
Medium compositions for the growth of M. barkeri
Component
1 2 3 4 5 6 7 8 9101112131415161718192021222324252627
Runs
(experiments)
FIG. 2. Gas production rate for the first experimental unit of the medium optimization by the "search method based on orthogonal array". (a) Depicting the levels of cysteine.HCl (S), (b) Depicting the levels of COC12.6H20. Orthogonal array: see Table 1. The inlet shows the GPrL at each level (GPr0, GPr], GPr2) expressed as 3 = 100 (GPrLGPrav)/GPrav (increment or decrement in % from the average of the GPr for all 27 runs). For culture conditions, see Fig. 1. Symbols: ½, lower level (L0); • , middle level (L0; [], higher level (L2); dotted line ( ), GPr~v.
. ,,
- u
NH4C1 K2HPO4 KH2PO4 MgSO4-THzO NaCl CaC12.2HzO FeSO4.7H20
COC12.6H20 NiCI2.6H20 Vitamin solution Mineral solution t-Cysteine •HCI
basal
g/l g/I g/l g/I g/l g/l mg/l mg/l mg/l ml/l ml/! g/l
Medium "oneorthogonal at-a-time" array
0.5
1.0
0.5
0.35 0.23 0.5 2.25 0.25 2.0 0.55 0.07 10 30 0.30
0.35 0.23 1.0 4.5 0.25 10.0 0.29 0.12 20 12 0.10
1.40 0.90 1.0 6.0 0.75 5.0 0.17 0.17 5 18 0.30
24
J. FERMENT. BIOENG.,
SILVEIRA ET AL.
TABLE 4. Comparison of gas production rates, cell and gas yields of M. barkeri obtained with the optimized media -
200
Basal Gas production rate ~ (mM/h) Initial gas production rate b (mM/h)
g 100
Cell yieldc (g/g)
(..9
Gas yieldd (mmol/g) O~ ~ - ~
0
r
,
20
i
,
40 Time
I
60
"One-at-a-time" Orthogonal array
4.98
7.57
10.12
1.13
1.40
2.01
0.17
0.25
0.26
26.8
26.0
26.2
,
80
(h)
FIG. 4. Time course for the methanogenesis of M. barkeri strain Fusaro on the three growth media. For culture conditions, see Fig. 1. Symbols: O, basal medium; c3, "one-at-a-time" optimum medium; , "search method based on orthogonal array" optimum medium.
e x p e r i m e n t a l unit the a v e r a g e gas p r o d u c t i o n rate (GPrav) increased f r o m 3.69 in the first to 6.42 m M / h in the fifth exp e r i m e n t a l unit with a smaller s t a n d a r d d e v i a t i o n f r o m 1.30 to 0.55 m M / h , i n d i c a t i n g that for every new experi m e n t a l unit carried out, a s u p e r i o r c o m b i n a t i o n for the m e d i u m c o m p o s i t i o n was achieved. F i g u r e 4 shows the t i m e c o u r s e or the m e t h a n o g e n e s i s o f M . barkeri o n the three g r o w t h m e d i a (Table 3). T h e gas p r o d u c t i o n rate o n the m e d i u m derived by the o r t h o g o n a l a r r a y o p t i m i z a t i o n m e t h o d increased o v e r 2.0 and 1.3 times w h e n c o m p a r e d to the basal a n d the " o n e - a t - a - t i m e " m e d i a , respectively. A l s o , increases on the initial gas p r o d u c t i o n rate and on the cell yield were f o u n d w h e n c o m p a r e d with the o t h e r t w o m e d i a , while the gas yield slightly d e c r e a s e d (Table 4). T o verify if the increase on the m e t h a n o g e n i c activity for the m e d i u m o b t a i n e d by the o r t h o g o n a l a r r a y m e t h o d m i g h t be due to the smaller v a r i a t i o n o f p H o b t a i n e d by the increase in the strength o f the p h o s p h a t e buffer (higher K2HPO4, KH2PO4 c o n c e n t r a t i o n s , see T a b l e 2), f u r t h e r exp e r i m e n t s were carried o u t for each m e d i u m with d o u b l e the c o n c e n t r a t i o n o f i m i d a z o l e (i.e. 5.44 g / / ) for buffer. H o w e v e r , a l m o s t the s a m e gas p r o d u c t i o n rates (Table 4) and no v a r i a t i o n o n the p H at the end o f c u l t i v a t i o n were o b s e r v e d (data n o t s h o w n ). T h e search m e t h o d based o n the o r t h o g o n a l a r r a y has been p r o v e d a p o w e r f u l m e a n s in the o p t i m i z a t i o n o f a m u l t i - c o m p o n e n t f e r m e n t a t i o n m e d i u m for M . barkeri, suggesting that the m e t h o d m i g h t be widely applied for the o p t i m i z a t i o n o f any type o f f e r m e n t a t i o n processes due to its rather simple t e c h n i q u e and the small n u m b e r o f experim e n t s r e q u i r e d . M o r e o v e r , the search m e t h o d based o n ort h o g o n a l arrays m a y m a k e possible the o p t i m i z a t i o n o f state variables such as t e m p e r a t u r e , p H , a g i t a t i o n speed, etc, t o g e t h e r with q u a n t i t a t i v e variables such as m e d i u m components. REFERENCES
1. Nagai, S. and Nishio, N.: Biological aspects of anaerobic digestion, p. 710-752. In Cheremisinoff, N.P. (ed.), Handbook of heat and mass transfer, vol. 3, Catalysis, kinetics and reactor engineering. Gulf Publishing Co., Houston, London, Paris, Tokyo (1989).
~' Gas production rate at each exponential phase of growth: 38 to 52 h for basal, 38 to 50 h for "one-at-a-time", and 35 to 45 h for orthogonal array. b Gas production rate for the first 35 h culture. Cell mass produced per methanol consumed when methanol was completely consumed. d Evolved gas (CH4 + CO2) produced per methanol consumed when methanol wag completely consumed.
2. Stronach, S. M., Rudd, T., and Lester, J. N.: Anaerobic digestion process in industrial wastewater treatment, p. 21-36. In Aiba, S., Fan, L.T., Fiechter, A., and Schugerl, K. (ed.), Biotechnology monographs, vol. 2. Springer-Verlag, Berlin, Heidelberg, New York, Tokyo (1986). 3. Sonoda, Y., Kida, K., and Nagai, S.: Conventional anaerobic digestion, p. 753-786. In Cheremisinoff, N. P. (ed.), Handbook of heat and mass transfer, vol. 3, Catalysis, kinetics and reactor engineering. Gulf Publishing Co., Houston, London, Paris, Tokyo (1989). 4. Mazumder, T.K., Nishio, N., Fukusaki, S., and Nagai, S.: Production of extracellular vitamin B12 compounds from methanol by Methanosarcina barkeri. Appl. Microbiol. Biotechnol., 65, 511-516 (1987). 5. Mazumder, T.K., Nishio, N., Hayashi, M., and Nagai, S.: Production of corrinoids including vitamin BI2 by Methanosarcina barkeri growing on methanol. Biotechnol. Lett., 8, 843-848 (1987). 6. Silveira, R. G., Nishida, Y., Nishio, N., and Nagai, S.: Corrinoid production with Methanosarcina barkeri in a repeated fed-batch reactor with membrane module. Biotechnol. Lett., 12, 721-726 (1990). 7. Friedmann, H . C . , Thauer, R. K., Gough, S.P., and Kannangara, G. C.: A-Aminolevulinic acid formation in the archaebacterium Methanobacterium thermoautotrophicum requires tRNA. Carlsberg. Res. Commun., 52, 363-371 (1987). 8. Lin, D., Nishio, N., Mazumder, T. K., and Nagai, S.: Influence of Co2% Ni 2~ and FC + on the production of tetrapyrrole by Methanosarcina barkeri. Appl. Microbiol. Biotechnol., 30, 196200 (1989). 9. Nishio, N., Sugawa, K., Hayase, N., and Nagai, S.: Conversion of D-xylose into xylitol by immobilized cells of Candida pelliculosa and Methanobacterium sp. HU. J. Ferment. Bioeng., 67, 356-360 (1989). 10. Boone, D. R. and Mah, R. A.: Effects of calcium, magnesium, pH and extent of growth on the morphology of Methanosarcina mazei S-6. Appl. Environ. Microbiol., 53, 1699-1700 (1987). 11. Murray, P.A. and Zinder, S.H.: Nutritional requirements of Methanosarcina sp. TM-1. Appl. Environ. Microbiol., 50, 49-55 (1985). 12. Scherer, P. A., Bochem, H. P., Davis, J. D., and White, D. C.: Flocculation in methanogens, a comparative study of Methanosarcina barkeri strains Julich and Fusaro. Can. J. Microbiol., 32, 137-144 (1986). 13. Auden, J., Gruner, J., Nueseh, J., and Knusel, F.: Some statistical methods in nutrient medium optimization. Pathol. Microbiol., 30, 858-866 (1967). 14. Gomes, J., Gomes, I., Esterbauer, H., Kreiner, W., and Steiner,
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15. 16.
17.
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