Effective Screening of Carbon and Nitrogen Substrates by ... - Saepub

Asian Journal of Biochemical and Pharmaceutical Research Issue 3 (Vol. 4) 2014 ISSN: 2231-2560 CODEN (USA): AJBPAD Research Article

Asian Journal of Biochemical and Pharmaceutical Research Effective Screening of Carbon and Nitrogen Substrates by Plackett-Burman Design for Production of Vancomycin by Amycolatopsis orientalis P. Naga Padma3, A. Bhaskar Rao2 and Gopal Reddy1* 1

Department of Microbiology, Osmania University, Hyderabad 500007, India 2 Indian Institute of Chemical Technology, Hyderabad 500007, India 3 BVB Vivekananda College, Secunderabad 500094, India.

Received: 16 June 2014; Revised: 07 August 2014; Accepted: 30 August. 2014

Abstract: Plackett-Burman statistical design was used to screen diverse carbon and nitrogen sources for glycopeptides antibiotic vancomycin production. Different monosaccharides, disaccharides, polysaccharides, complex carbohydrates like rice bran and wheat bran extract and cereal flours numbering 23 were screened using 24 experimental design. Similarly different inorganic nitrogen sources, complex organic nitrogen sources like sprouted seeds, pulse flours and amino acids numbering 23 were also screened using the same 24 experimental design. The fermentation was carried out for 10 days and the vancomycin yields were subjected to statistical analysis. Significant carbon and nitrogen sources were short listed based on regression coefficients and t-values. The significant carbon sources were malt extract, sucrose, starch and ragi flour and the significant nitrogen sources were sodium nitrate, corn steep liquor and yeast extract. These were selected and further short listed for optimization studies using second step of Plackett-Burman screening and Response Surface Methodology (RSM). Optimized production medium using cheaper raw materials like raagi flour, starch, corn steep liquor is commercially viable and a necessity for any industrial production. Key words: Amycolatopsis orientalis, Vancomycin, Carbon sources, Nitrogen sources.

INTRODUCTION: Glycopeptide antibiotics produced by Streptomyces species are highly effective aganist drug resistant staphylococcal infections and vancomycin is important among them. This antibiotic is bactericidal and acts by inhibiting one or both of the two sequential enzymatic reactions involved in cell wall synthesis namely peptidoglycan elongation or transglycosylation and cross linking or transpeptidation [1,2]. Development of resistant strains of Staphylococcus sp, Pneumococcus sp and Enterococcus sp has not only resurrected vancomycin after its first clinical use in 1958 but also increased its use worldwide. Vancomycin is the drug of choice for treatment of infective endocarditis caused by Staphylococcus aureus [3-5] and infections caused by coagulase-negative Staphylococci. It is also used to treat infections caused by different bacteria like penicillin-resistant strains of Streptococcus pneumoniae [6], Bacillus anthracis, Bacillus cereus [7], Corynebacterium diphtheria [8] etc. Intraventricular application of vancomycin is an effective therapeutic regimen for treatment of shunt associated staphylococcal ventriculitis [9]. It is also used to combat Gram-positive bacterial infections in intensive care patients [10]. Looking at the importance of this drug and its usage, indigenous 200

Asian Journal of Biochemical and Pharmaceutical Research

Issue 3 (Vol. 4) 2014 CODEN(USA) : AJBPAD

production is a necessity both to meet the demand and reduce the cost of drug. Development of fermentative technology for production of vancomycin suitable to Indian conditions is required. Taking this aspect into consideration in the present study different cheaper and locally available carbon and nitrogen sources were screened using statistical design like Plackett- Burman [11] in an attempt to optimize suitable production medium. This design is a statistical methodology used to screen up to n-1 variables in just n number of experiments. MATERIALS AND METHODS: Microorganism, its physical and physiological conditions ( Medium used) : Amycolatopsis orientalis ATCC 43491 was grown and maintained on ISP 2 medium slants or yeast-malt agar slants (Glucose - 4g/L, malt extract - 10g/L and yeast extract - 4g/L at pH 7.2 ). The inoculums for the fermentation was prepared in two stages. Sporulating culture from slant was inoculated into a shake flask of the medium and incubated at 280C for 3 days at 220 rpm. The fermentation conditions used were those optimized for the strain for vancomycin production [12]. The culture grown was used for screening of carbon and nitrogen sources for optimization of production medium. Bioassay: The flasks were incubated for 12 days. The fermented broth was collected and assayed for vancomycin every alternate day (2nd, 4th, 6th, 8th, 10th and 12th day) until the maximum broth potency had been passed. The samples were collected aseptically, centrifuged at 5000g for 15 min, supernatant was filtered through a 0.45µm Millipore filter. Bioassay plates were prepared by pouring 25ml of preseeded agar having 1 ml of sensitive culture Bacillus subtilis ATCC 11774 containing 105 cells/ml. Agar wells were made with a 6mm dia cork borer and the filtrate was bioassayed for vancomycin [13]. The zones of inhibition developed were measured, and the concentration of the antibiotic was determined using a graph of the standard vancomycin antibiotic. The bioassay results were compared with those of HPLC and tallied [14- 15]. Statistical Analysis: Different carbon and nitrogen sources were tested by a 24 experimental design of Plackett-Burman [11], taking care of their concentrations and status (ingredients added as such to prevent any thickening as many were flours). While fixing levels for all nutrients, care was taken to see that their combined concentrations were not inhibitory to either growth or production. The lower and upper levels fixed for the selected carbon sources was 0.02 and 0.2 the selected nitrogen sources was 0 and 0.1 respectively. In each case the nutrients are added according to the pattern of the design. The fermentation was carried out for 12 days with sample collection from 4th to 10th day. The broth samples collected were bio-assayed, antibiotic yields determined and results analysed statistically using ‘Indostat’ software package. The most important nutrients under different categories were selected after statistical analysis, based on regression coefficients and highest t-values. Those with p-values less than 0.005 were considered to be significant and shortlisted for further optimization studies.

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RESULTS: Different monosaccharides, disaccharides, polysaccharides, complex carbohydrates like rice bran and wheat bran extract and cereal flours numbering 23 were screened using 24 experimental design of Plackett-Burman [11]. The antibiotic production varied in different flasks on different days and ranged from minimum of 50 µg/ml to a maximum of 740 µg/ml. The antibiotic production data was subjected to statistical analysis which yielded regression coefficients and t-values. The probability of the experiment was 0.00001 and highly significant. Nutrients with highest positive regression coefficients and their corresponding t-values were ranked first, second and so on, on different days (Table 1). The ranking of ingredients varied on different days (Fig 1) . As observed in Figure 1 malt extract ranked first on all days while the others changed places with time but in general the next four places were generally occupied by soluble starch, raagi ( finger millet) flour, sucrose, rice bran extract and corn starch. Similarly different amino acids, inorganic nitrogen sources, complex organic nitrogen sources and sprouted seeds and gram flours numbering 23 were screened using 24 experimental design of Plackett-Burman [11]. The antibiotic production varied in different flasks on different days and ranged from less than 10 µg/ml to a maximum of 740 µg/ml. This statistical analysis also yielded regression coefficients and t-values (Table 2) and the experiment was highly significant as the probability of the experiment was 0.00001. Nutrients with highest positive regression coefficients and their corresponding t-values were ranked first, second and so on, on different days (Fig 2). As observed in Figure 2, yeast extract ranked first, on almost all the days while sodium nitrate ranked second followed by Kashmiri bean sprouts, pea sprouts, corn steep liquor and soya bean meal all significant on all days with change in order of ranking. DISCUSSION: The primary objective in developing a microbial culture medium is to ensure that the required nutrients are present in appropriate forms and at non-inhibitory optimum concentrations [16]. Taking the fact that microorganisms exhibit diverse nutritional requirements ranging from simple compounds like inorganic salts to complex compounds like vitamins, yeast extract etc. into consideration, various nutrients are being screened by application of statistical methods like Plackett-Burman [11] designs [17,18]. An optimization strategy in common use in the laboratory is the uni-dimensional approach but this search is both laborious and time consuming, especially for large number of variables. A statistical search is very helpful both in rapid and reliable short listing of nutrients and also understanding their interactions at varying concentrations. A full factorial search is useful for small number of variables as for example evaluation of 6 nutrients at 3 concentrations requires 729 (3)6 experimental trials. Therefore for large number of variables the most appropriate method is that of Plackett-Burman design [19] as it screens upto n-1 variables in number of experiments. 202

just n



Carbon sources are utilised by a heterotrophic microorganism for the production of cell mass, primary and secondary metabolites and also as an energy source [20- 22], [15]. Four carbon sources were short listed for second step screening like sucrose, malt extract, starch and ragi flour. These are significant as members of the glycopeptides group of antibiotics have carbohydrate content in their structure [23] mostly sugars like glucose (which can be formed by degradation of sucrose, starch, ragi flour). Reports also indicate that vancomycin is produced under glucose-limited conditions though it has a glucose in its structure [24] as free glucose is not a donor for the activity of the enzyme aglycosyl vancomycin-glucosyl transferase, which adds glucose to vancomycin heptapeptide core [25]. Ragi flour was found to be the significant carbon source it has amino acids like arginine and tyrosine in good amount and these are known to be necessary for vancomycin production [25,26]. Microbes require nitrogen to support the biosynthesis of both primary and secondary metabolites. Primary metabolites like purines, pyramidines, amino acids and secondary metabolites like antibiotics contain nitrogen in their structure. The influence of nitrogen sources on secondary metabolism in Streptomyces is well established [27-29]. Work of Bascaran and Hardisson et al [30] with S.clavuligerus also indicated that activities of enzymes involved in nitrogen nutrition are decreased by presence of ammonium. This observation too was applicable to present study as vancomycin antibiotic production in case of nitrogen sources was very less and it could be due to ammonium repression. The statistical method of screening facilitated identification of most significant nitrogen sources for vancomycin production yeast extract ranked 1st in significance. Yeast extract not only serves as a good nitrogen source but also as a source of vitamins, growth factors, amino acids etc. In the present study both the carbon and nitrogen sources selected by screening were significant as they not only served as nutrient source but also provided the structural components of the antibiotic vancomycin like glucose of the carbon sources and amino acids arginine and tyrosine in both ragi flour and nitrogen sources like yeast extract. The present study was useful in screening a large number of cheaper and locally available carbon and nitrogen sources for vancomycin production in less number of experiments. The statistical design allowed to efficiently screen n-1 variables in just n number of experiments saving both time and chemicals a very important aspect in design of production medium. ACKNOWLEDGEMENT: The authors thank Council of Scientific and Industrial Research (CSIR), New Delhi, India for financial support to carry out this work.

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FIGURE 1: Variation in the Regression coefficients and t-Values of the Selected and Short Listed Carbon Sources for Vancomycin Production on 4th, 6th, 8th and 10th Day

FIGURE 2 : Variation in the Regression coefficients and t-values of the selected and Short listed Nitrogen sources for Vancomycin production on 4th, 6th,8th and 10th

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TABLE 1: The Regression coefficients and t-values of the Carbon sources for Vancomycin production over a period of 10 days. S.No

4th Day

Ingredient

6th Day

8th Day

10th Day

1

Intercept

91.25

75.99

Reg. Coeff 175.63

2

Fructose

-20.42

17.00

-20.21

10.43

-31.46

15.67

-30.00

14.39

3

Glucose

-10.42

8.68

6.46

3.33

23.96

11.94

16.25

7.79

4

Lactose

-7.08

5.90

-9.79

5.05

-8.96

4.46

-8.75

4.20

5

Sucrose

24.58

-20.47

29.38

15.15

64.38

32.07

63.75

32.57

6

Maltose

13.75

11.45

8.96

4.62

28.96

14.43

25.42

12.19

7

Mannose

-0.42

0.35

-3.54

1.83

9.38

4.67

13.75

6.59

8

Mannitol

13.75

11.45

24.38

12.58

31.46

15.67

39.58

18.98

9

Xylose

-14.58

12.15

-21.88

11.29

-36.88

18.37

-34.17

16.39

10

Dextrin

-26.25

21.86

-18.13

9.35

-36.88

18.37

-35.00

16.79

11

Malt extract

44.58

37.13

50.63

26.12

94.79

47.23

88.33

42.36

12

Molasses

12.08

10.06

18.13

9.35

6.0-4

3.01

1.67

0.80

13

Corn starch

18.75

15.62

25.63

13.22

35.21

17.54

34.58

16.59

14

Soluble starch 28.75

23.94

48.13

24.83

84.36

42.03

85.42

40.96

15

Cassava starch Potato starch

11.25

9.37

-8.54

4.41

-24.38

12.14

-12.08

5.80

-22.92

19.09

-41.45

21.39

-72.71

36.22

-80.42

38.57

16.25

13.53

33.54

17.30

70.63

35.19

59.17

28..38

16

Reg. Coeff

t-value

t-value Reg. Coeff 90.61 336.46

t-value Reg. Coeff 167.62 333.33

159.86

t-value

-12.08

10.06

-8.96

4.62

-43.96

21.90

33.75

16.19

19

Rice bran extract Wheat bran extract Bajra flour

-12.92

10.76

-33.96

17.51

-49.79

24.81

-39.17

18.78

20

Barley flour

-10.42

8.68

23.13

11.93

62.71

31.24

54.17

25.98

21

Jowar flour

-7.08

5.90

-17.29

8.92

-14.38

7.16

-20.00

9.59

22

Ragi flour

31.25

26.03

45.63

23.54

77.29

38.51

81.67

39.17

23

Rice flour

-10.42

8.68

-23.96

12.36

-8.13

4.05

-5.00

2.40

24

Wheat flour

10.42

8.68

9.38

4.84

14.79

7.37

17.92

8.60

17 18

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TABLE 2 : The Regression coefficients and t-values of the Nitrogen sources for Vancomycin production over a period of 10 days. S.No

4th Day

Ingredient

6th Day

8th Day

10th Day

1

Intercept

Reg. Coeff 75.42

2

Asparigine

-0.42

1.00

-20.83

19.02

-27.29

10.59

-19.38

9.39

3

Proline

-8.75

21.00

-15.83

14.45

-7.70

2.99

-21.04

10.20

4

Tyrosine

0.42

1.00

5.83

5.32

18.13

7.03

8.13

3.94

5

Sodium nitrate

25.42

61.00

46.67

42.60

76.46

29.67

85.63

41.51

6

Potassium nitrate

7.92

19.00

-15.00

13.69

2.71

1.05

1.88

0.91

7

Ammonium nitrate

-0.42

1.00

11.67

10.65

-2.29

0.89

17.70

8.58

8

Ammonium sulphate

8.75

21.00

5.83

5.32

15.63

6.06

8.13

3.94

9

Triammonium citrate -7.92

19.00

-20.00

18.26

-36.88

14.31

-47.29

22.93

10

Casein hydrolysate

-33.75

81.00

-39.17

35.75

-80.21

31.13

-78.96

38.28

11

Corn steep liquor

33.75

81.00

41.47

38.03

49.79

19.32

71.88

34.84

12

Peanut meal

16.25

39.00

19.17

17.50

22.71

8.81

26.88

13.03

13

Soya bean meal

33.75

81.00

30.00

27.38

57.71

22.39

66.46

32.22

14

Yeast extract

33.75

81.00

55.00

50.20

73.96

28.70

89.79

43.53

15

French bean Sprouts

8.75

21.00

5.83

5.32

7.29

2.82

14.79

7.17

16

White bean sprouts

-24.58

59.00

-42.50

38.79

-57.29

22.23

-81.46

39.49

17

Pea sprouts

8.75

21.00

39.17

35.75

59.38

23.04

55.21

26.76

18

Chenna sprouts

8.75

21.00

1.67

1.52

5.21

2.02

-3.54

1.72

19

Red gram sprouts

-25.42

61.00

-28.33

25.86

-63.96

24.82

-56.46

27.37

20

Blackgram sprouts

7.92

19.00

21.67

19.78

16.04

6.23

33.13

16.06

21

Greengram sprouts

8.75

21.00

-5.83

5.32

-1.88

0.73

-6.88

3.33

22

Kashmiri bean sprouts Soyabean sprouts

25.42

61.00

36.67

33.47

66.46

25.79

75.21

36.46

-25.42

61.00

-30.00

27.38

-46.04

17.87

-43.54

21.11

8.75

21.00

10.83

9.89

29.38

11.40

13.54

6.56

23 24

Horse gram sprouts sprouts

tvalue 181.00

Reg. tCoeff value 144.17 104.21

Reg. Coeff 177.29

tvalue 68.80

Reg. Coeff 207.79

tvalue 101.70

*

Correspondence author : Prof. Gopal Reddy, Department of Microbiology, Osmania University, Hyderabad -500007, India. e-mail : [email protected] 206



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*Correspondence Author: Gopal Reddy, Department of Microbiology, Osmania University, Hyderabad 500007, INDIA.

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