Open Access

Effect of stoned olive pomace on rumen microbial communities and polyunsaturated fatty acid biohydrogenation: an in vitrostudy

  • Grazia Pallara1,
  • Arianna Buccioni1,
  • Roberta Pastorelli2,
  • Sara Minieri1,
  • Marcello Mele3,
  • Stefano Rapaccini1,
  • Anna Messini1,
  • Mariano Pauselli4,
  • Maurizio Servili5,
  • Luciana Giovannetti1 and
  • Carlo Viti1Email author
BMC Veterinary Research201410:271

https://doi.org/10.1186/s12917-014-0271-y

Received: 4 March 2014

Accepted: 6 November 2014

Published: 26 November 2014

Abstract

Background

Stoned olive pomace (SOP), which represents approximately 50% of the conversion process of olive in oil, is largely not-utilized and creates costs for its disposal and problems related to environmental impact. In-vitro trial experiments were employed to study the effect of feeds integrated with this bio-waste rich in polyphenols on rumen biohydrogenation, using sheep rumen liquor as inoculum.

Results

Fatty acid (FA) analysis and polymerase chain reaction denaturing gradient gel electrophoresis (DGGE) approach aimed to microbial community characterization showed that including SOP in feeds at the level of 50 g/kg and 90 g/kg induced changes in FA profile and in microbial populations. The contemporary decrease of Butyrivibrio proteoclasticus and the accumulation of vaccenic acid was observed. A depression of Neisseria weaveri, Ruminobacter amylophilus and other unclassified bacteria related to members of the Lachnospiraceae and Pasteurellaceae families was detected, suggesting that these microbial groups may be involved in rumen biohydrogenation.

Conclusions

Supplementation of feeds with SOP changes rumen bacterial community, including bacteria responsible for vaccenic acid hydrogenation to stearic acid, thus modifying FA profile of rumen liquor. Hence, an use of SOP aimed to produce meat or dairy products enriched in functional lipids could be hypothesized.

Keywords

Stoned olive oil pomace Sheep rumen microbiota Fatty acid biohydrogenation PCR-DGGE

Background

The main factor affecting ruminal biohydrogenation (BH) is animal diet, whose quality influences the content of healthful fatty acids (FA) in milk and meat. The inclusion of polyphenols in ruminant feeds has an inhibitory effect on BH of dietary PUFA, as consequence of their influence on microbial activity and diversity [1]. This has been shown to increase duodenal flow of bioactive FA, as vaccenic (trans-11 C18:1, VA) and, as consequence, to improve the nutritional value of milk fat from large and small dairy ruminants, since this FA can be ∆9-desaturated to rumenic acid (cis-9,cis-12 C18:2, RA) in the mammary gland and in other tissues. However, from literature it is well known that the availability of VA in ruminant products is limited by its hydrogenation to stearic acid (C18:0, SA) or isomerization to other C18:1 isomers by microbial activity taking place in the rumen [2].

Rumen microbial community comprises an enormous number of microbial species belonging to Bacteria, Archaea and Eucarya domains. However, only a limited number of them has been isolated and characterized physiologically until now [3]. Among the different microbial species already identified, those ones belonging to the Butyrivibrio group appear of particular interest, because they are known to be directly involved in BH [4]. Recent studies carried out on different species of ruminants have reported that diets enriched with polyphenols caused a decrease in SA and a contemporary decline of key species of Butyrivibrio [1],[5]. In last few years there has been also an arising interest on the impact of polyphenols on the methanogenic community, which largely contributes to the emissions of greenhouse gas to the atmosphere [6].

In Mediterranean area, during the period of olive oil production, there is an high production of moist virgin olive pomace that represents a problem for its disposal. The most recent stoning virgin olive pomace techniques permit to obtain a residual product (stoned olive pomace, SOP) characterized by a good level of polyphenols and low lignin content, which is considered the main factor reducing digestibility of olive pomace or olive cake when these by-products are utilized as animal feed [7]-[9]. These chemical characteristics make SOP potentially able to interfere with rumen fermentation [7],[10]. However, little information is available in literature on the effect of SOP inclusion in ruminant diets on microbial strains involved in BH processes and methanogenesis. The aim of the present study was to verify whether SOP supplementation in sheep diet is able to affect both the overall rumen microbial profile and specific rumen microbial groups with particular regard to the Butyrivibrio group and methanogenic archeal populations, thus influencing the PUFA profile of rumen liquor (RL).

Results

Rumen liquor fatty acid composition

During the fermentation of the three feeds, the concentration of acetic acid (C2:0) did not show significant differences with the exception of 12 h, when the percentage of this volatile fatty acid was higher in RL fermenting S5 and S9 (Table 1). Moreover, the presence of SOP in feeds significantly increased the concentration of propionic (C3:0), butyric (C4:0) and iso-valeric (iso C5:0) acids compared to the content of these FA in RL with C. As consequence, the ratio C2:0/C3:0 in S5 and S9 was significantly lower than that in RL fermented with C at 12 and 24 h (Table 1).
Table 1

Effect of stoned olive pomace (SOP) concentration (mM) on volatile fatty acid (VFA) production in ruminal fluid at 6, 12 and 24 h of incubation 1

VFA

Feed

 

Time (h)

 

SEM

P

  

6

12

24

  

C2:0

C

5.690

7.360

9.370 c

0.240

0.021

 

S5

6.700

8.020

9.190 c

  
 

S9

3.690

8.530

9.200 c

  

C3:0

C

2.450 α

2.670 α

3.010 α

0.340

0.047

 

S5

3.090 αβ

3.250 αβ

3.790 αβ

  
 

S9

3.150 β

3.990 β

4.230 β

  

C4:0

C

3.050

3.490

3.840

0.060

0.042

 

S5

3.450

3.750

4.020

  
 

S9

3.670

3.980

4.150

  

iso C4:0

C

0.156

0.189

0.193

0.075

0.083

 

S5

0.135

0.147

0.153

  
 

S9

0.114

0.113

0.112

  

C5:0

C

0.165

0.196

0.264

0.081

0.079

 

S5

0.194

0.217

0.210

  
 

S9

0.105

0.233

0.235

  

iso C5:0

C

0.350

0.360

0.500

0.030

0.037

 

S5

0.460

0.600

0.680

  
 

S9

0.490

0.800

0.820

  

C2/C3

C

2.322

2.756 αab

3.113

0.292

0.048

 

S5

2.168 α

2.68αβ

2.424 α

  
 

S9

1.171

2.138βb

2.175

  

α,β,γ Within a column, means with different Greek superscripts are significantly different (P < 0.05); a,b,c within a row, means with different Latin superscripts are significantly different (P < 0.05). C = control feed; S5 = treatment with 50 g/kg of SOP; S9 = treatment with 90 g/kg of SOP.

1Mean values with their standard errors (SEM); number of samples for each treatment at any time =3.

C14:0 and C16:0 increased in rumen fluid incubated with S5 while with C and S9 the concentration of these FA significantly decreased (Table 2). S5 and S9 significantly increased the C13:0 concentration within 12 h but at 24 h the percentage of this FA was significantly lower than that found in fermenters containing C (Table 2). Moreover at 24 h C15:0 percentage was the highest in S5 and C fermenters. C17:0 production was significantly depressed by S9 but not by S5, that resulted similar to C (Table 2).
Table 2

Effect of stoned olive pomace (SOP) concentration (g/100g total fatty acids, FA) on medium chain fatty acid production in ruminal fluid at 6, 12 and 24 h of incubation 1

FA

Feed

 

Time (h)

 

SEM

P

FA

Feed

 

Time (h)

 

SEM

P

  

6

12

24

 

F

FxT

  

6

12

24

 

F

FxT

C12:0

C

0.507

0.447 ab

0.357

0.048

0.069

0.027

anteiso C15

C

0.510 α

0.570 α

0.523 α

0.020

0.996

0.049

 

S5

0.403 abβ

0.363 b

0.443 aαβ

    

S5

0.477

0.490

0.626

   
 

S9

0.553 aαβ

0.403 b

0.320

    

S9

0.700

0.463

0.443

   

C13:0

C

0.973

1.133

1.676

0.041

0.791

0.034

iso C16

C

0.143 α

0.147

0.123 α

0.020

0.199

0.027

 

S5

1.117

1.360

1.340

    

S5

0.106

0.147 b

0.173

   
 

S9

0.640

1.526

1.463

    

S9

0.146

0.169 b

0.186

   

C14:0

C

0.847

0.823

0.753

0.030

0.874

0.012

iso C17

C

0.110

0.136 α

0.133 α

0.030

0.002

0.044

 

S5

0.663

0.730

0.913

    

S5

0.123 a

0.183

0.176 bαβ

   
 

S9

0.930

0.796

0.593

    

S9

0.107 a

0.183

0.193

   

C16:0

C

5.440

5.063

4.957

0.058

0.059

0.039

anteiso C17

C

0.143 αβ

0.173

0.174 α

0.007

0.041

0.042

 

S5

4.570

4.740

5.537

    

S5

0.116

0.133 a

0.201

   
 

S9

5.780

4.327

3.860

    

S9

0.177

0.133 a

0.101

   

C17:0

C

0.080

0.093 a

0.127

0.020

0.943

0.048

C12:1

C

0.040

0.047

0.013

0.030

0.061

0.002

 

S5

0.073

0.103 b

0.120

    

S5

0.017

0.036

0.050

   
 

S9

0.113

0.089 b

0.088

    

S9

0.037

0.020

0.030 abγ

   

iso C13

C

0.081

0.111 α

0.103 α

0.020

0.610

0.048

C14:1

C

0.277

0.353

0.287 aαβ

0.016

0.077

0.047

 

S5

0.086

0.081 α

0.087 α

    

S5

0.233 aαβ

0.260

0.363

   
 

S9

0.091a

0.173

0.167

    

S9

0.333

0.273 abβ

0.250

   

iso C14

C

0.087 α

0.087

0.097 α

0.010

0.497

0.015

C15:1

C

0.077 α

0.076

0.053 α

0.030

0.046

0.046

 

S5

0.077 aαβ

0.091 a

0.130

    

S5

0.053

0.056 a

0.093

   
 

S9

0.110

0.081 b

0.081

    

S9

0.100

0.057 b

0.093

   

iso C15

C

0.076

0.073 aαβ

0.037

0.010

0.275

0.047

C16:1

C

0.087

0.116

0.103

0.016

0.051

0.049

 

S5

0.053

0.080

0.076

    

S5

0.167

0.149

0.133

   
 

S9

0.073 α

0.057 α

0.060 β

    

S9

0.123

0.100

0.093

   

α,β,γ Within a column, means with different Greek superscripts are significantly different (P<0.05); a,b,c within a row, means with different Latin superscripts are significantly different (P<0.05). C = control feed; S5 = treatment with 50 g/kg of SOP; S9 = treatment with 90 g/kg of SOP; F, FxT: probability of significant effect due to experimental factors: feeds (F) and the interaction feed x time (FxT).

1Mean values with their standard errors (SEM); number of samples for each treatment at any time = 3.

At the last point of sampling the concentration of iso C15, iso C16 and iso C17 was significantly higher in S5 and S9 fermenters than in C (Table 2). Respect to C, anteiso C15 content was depressed during the fermentation of S9 and enhanced when S5 was fermented (Table 2). Moreover, the content of C17 ante increased during the fermentation of S5, whereas S9 showed an opposite trend (Table 2). The concentration of C12:1, C14:1 and C15:1 was characterized by an increasing trend in fermenters containing S5 (Table 2). The content of C18:0 increased during the whole time of fermentation regardless the treatment but with a lower extent for fermenters containing SOP in a dose dependent manner (Table 3). When RL was incubated with S5, cis-11 C18:1 and cis-13 C18:1 increased significantly after 12 h compared to the fermenters containing C and S9 (Table 3). Moreover, S5 decreased significantly the BH rate of cis-9 C18:1, that at 24 h showed the highest concentration (Table 3). VA was progressively accumulated during the whole period of fermentation when SOP is added to feeds regardless the percentage of inclusion, as consequence of a decrease of BH extent (Table 3). No significant differences among feeds were found for the other trans monoenes (Table 3). RA was accumulated at 12 h in any case but, when S5 and S9 were fermented, the its percentage in RL was the highest according to a decrease of BH rate (Table 3). In contrast, trans-10,cis-12 C18:2 was detected only at 12 h in S5 fermenters (Table 3). The BH rate of linoleic (cis-9,cis-12 C18:2, LA) and α-LNA (cis-9,cis-12,cis-15 C18:3) acids was similar in C and S9 (Table 3). In S5 it was simply lowered leading to a higher accumulation of LA and α-LNA at 24 h. Conjugated linolenic acid (cis-9,trans-11,cis-15 C18:3) and vaccelenic acid (trans-11,cis-15 C18:2) were detected at 24 h only in S9 fermenters (Table 3).
Table 3

Effect of stoned olive pomace (SOP) concentration on C18 fatty acids (g/100 g FA) production in ruminal fluid at 6, 12 and 24 h of incubation 1

FA

Feed

 

Time (h)

 

SEM

P

FA

Feed

 

Time (h)

 

SEM

P

  

6

12

24

    

6

12

24

  

C18:0

C

2.377

2.590

4.167

0.047

0.006

trans-11 C18:1

C

0.580 a

0.350

0.120

0.021

0.005

 

S5

2.203

3.080

3.446

   

S5

0.483 a

0.677

0.850

  
 

S9

1.760

2.806

2.999

   

S9

0.473 a

0.653

0.830

  

cis-9 C18:1

C

2.063

1.610

1.290

0.023

0.032

trans-12 C18:1

C

0.047

0.047

0.053

0.024

0.485

 

S5

1.950

1.526

1.567

   

S5

0.056

0.050

0.043

  
 

S9

2.563

1.663

1.163

   

S9

0.053

0.036

0.029

  

cis-11 C18:1

C

0.437

0.420

0.473

0.068

0.046

cis-9,cis-12 C18:2

C

4.527

3.180

1.733

0.043

0.031

 

S5

0.340 a

0.360 a

0.527 b

   

S5

3.750

2.653

2.060

  
 

S9

0.487

0.350

0.363

   

S9

4.780

2.523

1.680

  

cis-12 C18:1

C

0.033 a

0.150

0.110

0.010

0.006

cis-9,trans-11 C18:2

C

0.000 a

0.021

0.000 a

0.020

0.033

 

S5

0.050 a

0.060

0.117

   

S5

0.000 a

0.112

0.000 a

  
 

S9

0.040 a

0.040

0.073

   

S9

0.000 a

0.113

0.000 a

  

cis-13 C18:1

C

0.040

0.070

0.050

0.013

0.046

trans-10,cis-12 C18:2

C

0.000

0.000 α

0.000

0.001

0.001

 

S5

0.036

0.040

0.073

   

S5

0.000 a

0.067

0.000 a

  
 

S9

0.080

0.036

0.053

   

S9

0.000

0.000 α

0.000

  

cis-15 C18:1

C

0.020 α

0.020

0.037

0.009

0.045

cis-9,cis-12,cis-15 C18:3

C

0.530

0.393

0.283

0.006

0.044

 

S5

0.036 α

0.036

0.033

   

S5

0.400

0.357

0.370

  
 

S9

0.053

0.023 b

0.020 b

   

S9

0.597

0.337

0.283

  

trans-9 C18:1

C

0.037

0.040

0.040

0.008

0.045

cis-9,trans-11,cis-15 C18:3

C

0.000

0.000

0.000 α

0.001

0.002

 

S5

0.037

0.047

0.030

   

S5

0.000

0.000

0.000 α

  
 

S9

0.037

0.050

0.027

   

S9

0.000 a

0.000 a

0.056

  

trans-10 C18:1

C

0.047

0.040

0.053

0.011

0.910

trans-11,cis-15 C18:2

C

0.000

0.000

0.000 α

0.001

0.004

 

S5

0.060

0.063

0.057

   

S5

0.000

0.000

0.000 α

  
 

S9

0.043

0.050

0.047

   

S9

0.000 a

0.000 a

0.143

  

α,β,γ Within a column, means with different Greek superscripts are significantly different (P < 0.05); a,b,c within a row, means with different Latin superscripts are significantly different (P < 0.05). C = control feed; S5 = treatment with 50 g/kg of SOP; S9 = treatment with 90 g/kg of SOP.

1Mean values with their standard errors (SEM); number of samples for each treatment at any time =3.

Microbial population profiling

DGGE analysis of PCR-amplified partial 16S rRNA genes was performed on total bacteria, Butyrivibrio, and methanogenic populations of RL incubated with the three diets. Microbial profiles obtained using universal primers for bacteria showed a complex band pattern in all samples (Figure 1A). UPGMA dendrogram separated samples incubated with S5 and S9 diets and collected at 24 h from all the other samples, with 82.8% similarity (Figure 1A). Within the cluster containing S5 and S9 and collected at 24 h two subclusters (86.2% similarity) were evident, based on the percentage of SOP (Figure 1A). Samples collected at 0 and 6 h formed a different group when compared with samples collected at 12 h and with control samples collected at 24 h, with a similarity of 87.6%. A similarity higher than 92% was found in RL samples inoculating C, S5 and S9 collected at 0 and 6 h (Figure 1A).
Figure 1

Cluster analysis based on unweighted pair group method with arithmetic mean of polymerase chain reaction denaturing gradient gel electrophoresis profiles showing the effect of C, S5 and S9 diets on total bacteria (A) and the Butirivibrio group (B) in rumen liquor collected at 0, 6, 12 and 24 h. C = control feed; S5 = treatment with 50 g/kg of stoned olive pomace; S9 = treatment with 90 g/kg of stoned olive pomace. Scale relates to percent similarity.

PCR-DGGE analysis of members of the Butyrivibrio group showed a less complex pattern than total bacteria (Figure 1B). Two main clusters were evident, separating all samples collected at 0 and 6 h from those collected at 12 and 24 h, with 77.0% similarity (Figure 1B). Subclusters once again reflected clearly the percentage of the amount of SOP added and the collection time (Figure 1B). Control samples collected at 0 and 6 h grouped differently from samples incubated with S5 and S9 diets (Figure 1B), with 81.2% similarity. Moreover, all samples collected at 12 h grouped separately from those collected at 24 h, with 85.6% similarity (Figure 1B). Along within the latter group, samples added with S5 and S9 diets grouped together, separating from control samples, with 90.6% similarity (Figure 1B).

PCR-DGGE profiles obtained from the analysis of methanogens did not show differences at any sampling time for all feeds (data not shown).

Sequence analysis of bacterial and Butyrivibrio-specific PCR-DGGE bands

PCR-DGGE bands exhibiting remarkable changes in response to SOP in total bacteria or in Butyrivibrio populations (bands 1, 5, 7, 8, 9, 11, 12, 17, 18, 20, 21, 22, 23 and 24) were excised, re-amplified and sequenced (Figure 2). Moreover, in order to gain more information on the composition of rumen bacterial community of sheep, ten bands obtained with primers F968/R1401 for total bacteria (bands 2, 3, 4, 6, 10, 13, 14, 15, 16 and 19) were selected and sequenced, even if their intensity was not affected by SOP (Figure 2A). Putative taxonomic identification of each band subjected to sequencing is reported in Table 4.
Figure 2

PCR-DGGE profiles of total bacterial community (A) and Butyrivibrio members (B) in rumen liquor inoculating C, S5 and S9 diets and collected at 0, 6, 12 and 24 h. C = control feed; S5 = treatment with 50 g/kg of stoned olive pomace; S9 = treatment with 90 g/kg of stoned olive pomace. Bands indicated by numbers were selected for sequencing.

Table 4

Identification of the selected polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) fragments

PCR-DGGE band

Nearest match (GenBank accession no.; % sequence similarity)

Taxonomic classification

Total bacterial community analysis

 

1

Pasteurella testudinis (NR_042889; 90%)

Unclassified Pasteurellaceae

2

Bergeriella denitrificans (NR_040933; 99%)

Bergeriella denitrificans

3

Bergeriella denitrificans (NR_040933; 99%)

Bergeriella denitrificans

4

Clostridium lavalense (NR_044289; 93%)

Unclassified Clostridiaceae

5

Neisseria weaveri (NR_025902; 99%)

Neisseria weaveri

6

Neisseria weaveri (NR_025902; 98%)

Neisseria weaveri

7

Neisseria weaveri (NR_025902; 99%)

Neisseria weaveri

8

Neisseria weaveri (NR_025902; 98%)

Neisseria weaveri

9

Neisseria flavescens (KF030235; 100%)

Neisseria flavescens

10

Clostridium citroniae (NR_043681; 90%)

Unclassified Clostridiaceae

11

Ruminobacter amylophilus (NR_026450; 99%)

Ruminobacter amylophilus

12

Neisseria flavescens (KF030235; 100%)

Neisseria flavescens

13

Neisseria flavescens (KF030235; 100%)

Neisseria flavescens

14

Neisseria weaveri (NR_025902; 98%)

Neisseria weaveri

15

Howardella ureilytica (NR_044022; 94%)

Unclassified Clostridiaceae

16

Roseburia faecis (NR_042832; 90%)

Unclassified Lachnospiraceae

17

Butyrivibrio hungatei (NR_025525; 90%)

Unclassified Lachnospiraceae

18

Butyrivibrio hungatei (NR_025525; 93%)

Unclassified Lachnospiraceae

19

Ruminococcus torques (NR_036777; 90%)

Unclassified Lachnospiraceae

Butyrivibrio-specific analysis

 

20

Butyrivibrio proteoclasticus (NR_102893; 92%)

Unclassified Lachnospiraceae

21

Butyrivibrio proteoclasticus (NR_102893; 98%)

Butyrivibrio proteoclasticus

22

Butyrivibrio proteoclasticus (NR_102893; 99%)

Butyrivibrio proteoclasticus

23

Robinsoniella peoriensis (NR_041882; 94%)

Unclassified Lachnospiraceae

24

Eubacterium ruminantium (NR_024661; 92%)

Unclassified Lachnospiraceae

Phylogenetic analysis of the nineteen sequences of the PCR-DGGE fragments obtained with primers F968/R1401 (total bacteria) and sequences from rumen bacteria of equivalent length retrieved from the GenBank database was performed. The results indicated that seven sequences (bands 4, 10, 15, 16, 17, 18 and 19) were related to known species of Clostridiales (Figure 3), ten sequences (bands 2, 3, 5, 6, 7, 8, 9, 12, 13 and 14) were related to Neisseriales and the remaining two sequences were related to Pasteurellales (band 1) and Aeromonadales (band 11) (Figure 3, Table 4).
Figure 3

Neighbour-joining tree built using all 16S rRNA sequences obtained from total bacteria PCR-DGGE gels and sequences of rumen bacteria of equivalent length, retrieved from the GenBank database. Sequences obtained in this study are shown in boldface. Bootstrap values >50% based on 1000 replications are indicated at the nodes. The 16S rRNA gene sequence of Escherichia coli (NR_024570) was selected as the outgroup.

The analysis of total bacterial PCR-DGGE profiles evidenced that seven bands, corresponding to Neisseria weaveri (bands 5, 7 and 8), Ruminobacter amylophilus (band 11), unclassified Pasteurellaceae (band 1) and Lachnospiraceae (bands 17 and 18) reduced their intensity at 24 h in samples receiving the S9 diet in comparison to controls, whereas one band, identified as Neisseria flavescens (band 9), increased in S9 samples at the same sampling time (Figure 2A). On the contrary, minor differences were observed in presence of S5 diet at 24 h in comparison to controls, since the only disappearance of band 12 (Neisseria flavescens), and the appearance of band 9 (Neisseria flavescens) were detected (Figure 2A).

A phylogenetic tree was also constructed with the five sequences obtained with the Butyrivibrio-specific primers F968/Bfib and other sequences of equivalent length, representative of bacterial species related to the Lachnospiraceae family. As shown in Figure 4, two sequences (bands 21 and 22) grouped with sequences representative of Butyrivibrio proteoclasticus, whereas three sequence (band 20, 23 and 24) displayed a very low level of similarity with other known bacterial species belonging to the Lachnospiraceae family.
Figure 4

Neighbour-joining tree built using all 16S rRNA sequences obtained from Butirivibrio -specific PCR-DGGE gels and sequences of rumen bacteria of equivalent length, retrieved from the GenBank database. Sequences obtained in this study are shown in boldface. Bootstrap values of >50% based on 1000 replications are indicated at the nodes. The 16S rRNA gene sequence of Escherichia coli (NR_024570) was selected as the outgroup.

PCR-DGGE profiles obtained using Butyrivibrio-specific primers showed weak changes in the Butyrivibrio community in relation to diets. In S5 and S9 samples bands 21 and 22, identified as Butyrivibrio proteoclasticus, reduced their intensity already at 12 h when compared to C (Figure 2B). Moreover, considering samples collected at 24 h, band 20, (unclassified Lachnospiraceae), showed a lower intensity than controls after incubation with S5 and S9 diets, whereas bands 23 and 24 (unclassified Lachnospiraceae) decreased slightly only in presence of S9 diet (Figure 2B).

Discussion

In literature it is well known that the inclusion of plant polyphenols in animal feed interferes with rumen metabolism, decreasing dietary protein degradation for a better rumen energy-protein balance and reducing methanogenesis by means targeting specific group of microorganisms [1],[5]. SOP, by-product of olive oil extraction containing a high proportion of polyphenols, has been proposed as supplement in ruminant feeding with the aim to improve the content of PUFA in dairy products deriving from ruminant livestock, contributing at the same time to the environmental sustainability of animal productions [7],[10]. However, until now, there is a lack of knowledge on the effect of SOP on lipid metabolism and rumen microbial communities involved in fatty acid BH processes. This information is essential in order to optimize its employment in ruminant feeding.

According with a validate experimental design [1], our finding showed that the inclusion of SOP in feeds stimulated the production of volatile fatty acids, suggesting that microbial activity was modified by the presence of polyphenols in feeds: the highest increase of C3:0 in the fermented RL inoculating S5 and S9 can be related to a good level of amilolytic bacteria activity, while the constant production of C2:0 and the increase of iso C5, arising from microbial degradation of dietary aminoacids, can be an indication of a stimulated cellulolytic bacteria activity [11]. Iso C5 is the precursor of iso C15 and iso C17, which arise from the peculiar rumen methabolism of cellulolytic bacteria [11]. In our experiment iso C15 and iso C17 production was stimulated by SOP confirming that cellulolytic activity was not perturbed although literature demonstrated the antimicrobial activities of olive oil mill waste-waters against different groups of bacteria [12].

SOP supplementation in feeds did not contribute to protect double bond cis-9 from the saturation as demonstrated by BH of OA and RA that decreased during the fermentation period. A decrease of OA isomerisation to other trans C18:1 isomers could be hypothesized because not significant variations in the concentration of these monoenes have been detected. The temporary RA accumulation at 12 h in RL fermented with S5 and S9 can be related to a negative feed-back effect caused by the VA accumulation in these fermenters. This hypothesis could be extended also to conjugated linolenic acid and vaccelenic acid, further precursor of VA from α-LNA biohydrogenation, which appeared only at the end of fermentation in fermenters containing the highest content of SOP. VA accumulation in RL fermented with S5 and S9 is closely related to a decrease in Butyrivibrio proteoclasticum growth as revealed by PCR-DGGE analysis, as following discussed. SOP did not contribute to preserve LA and α-LNA from isomerisation to their cis-9,trans-11 isomers, indicating that LA-Isomerase activity is not influenced by SOP inclusion in feeds. Moreover, the shift of LA and α-LNA biohydrogenation toward the trans-10 isomers falls is not enhanced. This trend agrees with several studies that demonstrated polyphenols do not favour the increase of trans-10 monoenes synthesis [1],[5],[7].

Cluster analysis of PCR-DGGE profiles obtained with universal primers for 16S rRNA gene clearly showed a shift in total bacterial community in presence of SOP-enriched diets, in comparison to controls. Buccioni et al. [1] evidenced that tannins, a class of polyphenols, were able to affect the FA composition of solid- and liquid-associated bacteria communities from the rumen of sheep, suggesting changes in their composition and/or activity in relation to the BH process. In our study, the effect of SOP on rumen bacterial communities seemed to depend on the level of its supplementation in the diet and on the incubation time. Indeed, after 24 h of incubation with 90 g/kg SOP some bands in PCR-DGGE profiles showed a decreased intensity. We thus hypothesize that the changes observed in PCR-DGGE banding pattern may reflect the reduced abundance of the most sensitive species of ruminal bacteria to the antimicrobial action of SOP. Our observation is in agreement with previous in vitro studies, underlining that polyphenols from different plants are able to reduce the activity and the proliferation of different ruminal microorganisms [13]. The inhibitory effect exerted by this compounds has been explained by their ability to form complexes with the bacterial wall and to inactivate many extracellular enzymes secreted [14].

Until now few studies have been carried out on sheep rumen microbiota using PCR-DGGE analysis followed by sequencing and identification of the main bacterial groups. Here only eleven PCR-DGGE bands obtained from the total bacterial community analysis resulted highly related to the 16S rRNA gene of known species, whereas the other ones correspond to yet unclassified bacteria. This result is not surprisingly, since the use of different culture-independent methods has demonstrated that rumen microbiota is more diverse than previously hypothesized taking into account the number of cultivated species [3]. On the whole, the sequenced bands resulted related mainly to species belonging to the Clostridiaceae family and to the genus Neisseria. The first taxonomic group includes many cellulolytic and amylolytic species, often found in the rumen [3]. On the contrary, only a gram-negative carbohydrate-fermenting bacteria similar to Neisseria has been isolated from sheep rumen [15]. However, since the members of the Neisseriaceae family are mammalian commensals [16], their presence in the rumen is likely. In the analyzed samples, we also detected the presence of Ruminobacter amylophilus, a typical rumen bacteria that may occur in reasonably large number in high grain or high roughage diets [17].

The most interesting changes in PCR-DGGE profiles were observed after 24 h in RL inoculating S9 diet for the species Neisseria flavescens, Neisseria weaveri, Ruminobacter amylophilus and for members of the Lachnospiraceae and Pasteurellaceae families. Previous in vitro and in vivo studies have shown that some members of the Lachnospiraceae family, such as Butyrivibrio species, are the main known bacteria involved in rumen BH [18]. Nevertheless, analyzing the RL of dairy cows by T-RFLP and DGGE approaches [19], have recently suggested that other yet not known bacterial species may play a role in the BH process. Thus, according to these authors, the findings obtained until now from studies on pure cultures may be not able to explain the bacterial contribution to rumen BH in vivo, that appears more complex than previously thought. Our study strengthens this hypothesis, even if further research is need to clarify the potential role of the detected bacterial groups in FA metabolism of sheep rumen.

Previous in vitro experiments have shown that members of the Butyrivibrio group are able to biohydrogenate unsaturated FA more rapidly than other species. However, among this group, only B. proteoclasticus has been recognized to reduce C18:1 to C18:0 [4]. Since members of the Butyrivibrio group comprise only a minor part of ruminal bacteria [20] we performed a Butyrivibrio-specific PCR-DGGE analysis to investigate in detail the effect of SOP supplementation on this taxonomic group. Cluster analysis showed that both diets supplemented with SOP affected the composition of the Butyrivibrio population. Indeed, both at 12 h and at 24 h of incubation we observed a reduced intensity of specific PCR-DGGE bands. This result is consistent with previous in vitro observations that evidenced the sensitivity of some members of the Butyrivibrio group to polyphenol extracts obtained from tannin-rich plants [13],[14]. Sequence analysis revealed that two bacterial group responding negatively to SOP after 12 h of incubation were closely related to B. proteoclasticus (levels of 16S rDNA similarity above 98.0%), that is the only cultured SA producer. Since a significant increase of VA was observed in relation to incubation time only in samples added with SOP, we hypotheses that B. proteoclasticus, and other species of Butyrivibrio here not identified, might play a role in the conversion of trans C18:1 to C18:0. Our data confirm the hypothesis formulated by Vasta et al. [5], who found a correlation between the reduced abundance of B. proteoclasticus and the contemporary increase of VA in lamb rumen fluid, following the addiction of polyphenols from quebracho tannins to the diet. Thus, our data suggest that SOP may decrease the hydrogenation of trans C18:1 and trans C18:2 intermediates by affecting negatively the growth of B. proteoclasticus.

The present study reports also some results on the effect of SOP on rumen archeal methanogens, in order to elucidate if addition of this type of feed to ruminant diet may cause shifts in the methanogenic community. Surprisingly, we found that SOP addition did not significantly affect methanogen diversity and relative abundance, independently of the time of sampling and of the dietary SOP level. Until now few studies have dealt with the effect of polyphenols on rumen methanogenic communities, even if a study carried out by Jeyanathan et al. [21] showed that archaeal communities remained relatively constant across different ruminant species and diets, differently from bacterial communities. Our data are in agreement with these findings, but further investigations are required to understand if SOP may affect total methanogens abundance, that has been suggested to be more important in determining methane emission rates than the composition of methanogenic community [22].

Conclusions

Supplementation of feeds with SOP inhibited in a dose dependent manner the rumen BH of C18 unsaturated FA, resulting in a decrease of SA concentration and in an increase of VA. In particular, changes in rumen fatty acid profile were associated with changes in the bacterial community, including bacteria responsible for VA hydrogenation to SA. Hence, an use of SOP aimed to produce meat or dairy products enriched in functional lipids could be hypothesized. Moreover, the use of SOP in animal feeding can represent a revaluation of a bio-waste from food chain, thus contributing to environmental sustainability.

Methods

Feed composition

Feeds used as substrate of the fermentation were: a control diet (C) in which the SOP was not included and other two diets (S5 and S9) in which the integration with SOP was respectively of 50 g/kg on DM and 90 g/kg on DM. The amount of SOP used in this experiment was chosen with the criteria of the practicality under farm conditions. The diets were formulated to be isoproteic and isoenergetic. The ingredients and chemical composition of feeds are showed in Table 5. SOP was obtained after mechanical extraction of virgin olive oil using the following operative conditions [10]: the olives were stoned and malaxed for 40 min at 25°C and the oil extraction was performed using an RCM Rapanelli three phases decanter mod. 400 eco. After storage at room temperature for 36 hours, stoned olive cake was dried using a fluid bed dryer; the initial temperature of the drying air flow was 120°C and the maximum temperature of olive cake during the drying process was 45°C. The dried stoned olive cake was stored at room temperature. The proximate composition (according to A.O.A.C procedures, 1990) of SOP was: DM (873.80 g/kg), crude protein (118.31 g/kg on DM), neutral detergent fibre (490.51 g/kg on DM), acid detergent fibre (347.40 g/kg on DM), acid detergent lignin (85.61 g/kg on DM) and 63.43 g/kg on DM of crude fat in which the main FA contained were C16:0 (12.81 g/100 g of total FA), cis-9 C18:1 (76.43 g/100 g of total FA) and cis-9,cis-12 C18:2 (6.82 g/100 g of total FA). Polyphenols composition of SOP was determined according to Servili et al. [9]: 3,4-dihydroxyphenolethanol (1.16 g/kg DM), 4-hydroxyphenolethanol (0.11 g/kg DM); p-cumaric acid (0.04 g/kg DM), verbascoside (1.33 g/kg DM), 2-(3,4-hydroxyphenyl)ethyl(3S,4E)-4-formyl-3-(2-oxoethyl)hex-4-enoate (1.16 g/kg DM). Total polyphenols content in SOP was 3.80 g/kg DM.
Table 5

Composition of feeds used as substrate of the fermentation and main fatty acids (FA) in rumen liquor (RL) at the start of fermentation

Feed composition

C

S5

S9

Ingredients (g/kg DM)

   

Grass hay

103.45

103.45

98.04

Wheat straw

103.45

103.45

98.04

Mais meal

545.52

510.00

504.80

Soybean meal

42.76

42.76

40.52

Wheat bran

33.10

33.10

31.37

Bean flakes

20.69

20.69

19.61

Soybean flakes

12.41

12.41

11.76

Horsebean flakes

11.03

11.03

10.46

Barley

109.66

95.17

78.43

Stoned olive oli cake

---

50.00

90.00

Maize germ meal

17.93

17.93

16.99

Chemical composition (g/kg DM)

   

Dry Matter kg

724.70

719.00

713.0

expressed as (g/kg DM)

   

Crude protein (6.25 x N)

115.91

116.23

116.40

Crude fat

23.42

24.51

25.63

Neutral detergent fiber

366.00

379.40

391.81

Acid detergent fiber

194.73

205.63

215.82

Lignin

81.64

81.81

82.53

Ash

58.76

61.25

63.56

Non protein nitrogen

2.48

4.43

5.27

Soluble protein

8.57

9.72

10.39

Neutral detergent insoluble protein

2.50

5.60

7.99

Acid detergent insoluble protein

1.11

2.30

3.21

Main fatty acids in RL at the start

   

of fermentation (g/100 g of total FA)

   

C16:0

18.05

17.23

16.33

C18:0

1.90

1.79

1.79

cis-9 C18:1

23.92

25.19

26.81

cis-9,cis-12 C18:2

52.96

52.98

52.38

cis-9,cis-12,cis-15 C18:3

2.67

2.44

2.32

C = control feed; S5 = treatment with 50 g/kg of stoned olive pomace (SOP); S9 = treatment with 90 g/kg of SOP.

In vitroincubation with sheep ruminal fluid

The in vitro incubation was performed according to Tedeschi et al. [23] with several modification: Four sheep, conditioned with a basal diet formulated to shape rumen microflora and composed by grass hay (770 g/kg DM), soybean meal (55 g/kg DM), barley meal (175 g/kg DM), were used to provide rumen contents. Animals had continuous access to water and mineral blocks. After 4 weeks of adaptation period, about 1 litre of rumen contents was collected from each sheep using a rumen fluid sampling pump on the same day before the morning meal. The handling of the animals were according to Institutional Animal Care and Use Committee of Florence University (IACUC, 2004). The RL was immediately mixed with CO2 to avoid O2 contamination and transferred to the laboratory in a thermostatic box (39°C) under anaerobic condition. The RL was than filtered through four layers of cheese cloth into a flask under a continuous flux of CO2. An aliquot of the RL was buffered (1:3, v/v) by adding an artificial saliva solution [24]. Feed (2 g DM) were incubated in triplicate with 200 ml of inoculum. The incubator consisted of a thermostatic chamber (39°C) equipped with twenty-seven 300 ml glass fermentation vessels provided with two inlets (one to release gas through a valve and one for the pH probe) and connected to an electronic pressure transducer (pre-set at 65 kPa) and to an electronic gas valve. When the inside gas pressure reached the pre-set value, the valve was opened releasing about 2 ml of gas. The fermentation pattern was monitored by a PC software (Labview 5.0, National Instr., Austin, TX). Each vessel, containing substrate inoculated with rumen fluid saturated with CO2 to guarantee the anaerobic condition, was continuously stirred. Samples of RL were collected at 6, 12 and 24 h of incubation. According to Buccioni et al. [1] three vessels per treatment were used for rumen microbial characterization and FA analysis, as described below. Three aliquots of 1 ml of RL for each diet per sampling time combination were stored at -80°C until DNA extraction was performed.

Samples of RL (200 ml) immediately after the addition of buffer solution and before feed inoculation (as blank to control the quality) and samples of RL (200 ml) inoculated with feeds, at the start of fermentation (t = 0 min), were collected in triplicates to be analysed for FA profile. The fat content of RL blank was very low (0.01 g/l), as a consequence of the procedure adopted for the preparation of the inoculum; hence, the initial contribution of RL to FA composition of inoculum was negligible (data not shown). Table 5 shows the FA composition of RL inoculating the three diets at the beginning of fermentation. In the feeds the concentration of oleic acid (cis-9 C18:1, AO) increased according to the percentage of SOP inclusion in the diet.

Feeds proximate analysis

Samples of feeds were oven dried at 60°C for 24 h. The dry samples were analyzed for crude protein, ash and crude fat according to the 954.01, 954.05 and 920.39 procedures of AOAC (1990), respectively. Neutral detergent fiber, acid detergent fiber and acid detergent lignin were determined by using sequential analysis, with sodium sulfite, with heat stable amylase, and expressed inclusive of residual ash. The carbohydrate and protein differently degradable fractions (non protein nitrogen; soluble protein; neutral detergent insoluble protein; acid detergent insoluble protein) were estimated according to the Cornell Net Carbohydrates and Protein System CNCPS [25].

Rumen fatty acid analysis

To determine the FA, each sample (about 150 mg) was extracted according to Folch method [26] without drying the final solution containing the lipid extract which was directly methylated using a combination of methods according to Buccioni et al. [1] with the aim to avoid volatile fatty acid (VFA) loss. The first step consisted of an alkaline methylation with sodium methylate/methanol (1 ml of 0.5 M-Sodium Methoxide) to esterify glycerides. The second step involved an acid methylation with HCl/methanol (1.5 ml of 5% methanolic HCl, 10 min at 50°C) as catalyst to esterify NEFA. Fatty acid methylesters (FAME) were extracted using n-hexane with C9:0 and C23:0 methyl ester (Sigma Chemical Co., St. Louis, MO) as internal standards for quantification, and maintained in vials with hermetic closure to avoid the loss of volatile components. FAME were separated and identified by gaschromatography on a GC equipped with a capillary column (CP-select CB for FAME Varian, Middelburg, The Nederlands: 100 m × 0.25 mm i.d; film thickness 0.20 μm), according to Buccioni et al. [27]. The injector and flame ionization detector temperatures were 270°C and 300°C, respectively. The programmed temperature was 40°C for 4 min, increased to 120°C at a rate of 10°C/min, maintained at 120°C for 1 min, increased to 180°C at a rate of 5°C/min, maintained at 180°C for 18 min, increased to 200°C at a rate of 2°C/min, maintained at 200°C for 1 min, increased to 230°C at a rate of 2°C/min and maintained at this last temperature for 19 min. The split ratio was 1:100 and helium was the carrier gas with a flux of 1 ml/min. Standard mix (47792 Supelco, Chemical Co., St. Louis, MO) and published isomeric profiles [28] were used to identify the α-linolenic acid (α-LNA) isomers. Two bacterial acid methyl ester mix (47080-U Supelco, Chemical Co., St. Louis, MO; GLC110, Matreya, Pleasant Gap, PA) and individual standard for methyl ester of iso C14:0, anteiso C14:0, iso C15:0 and anteiso C17:0 (21-1211-11, 21-1210-11, 21-1312-11 and 21-1415-11, Larodan Malmo, SW) were used to identify branched FA profile. Inter and intra-assay coefficients of variation were calculated by using a reference standard butter (CRM 164, Community Boureau of Reference, Bruxelles, Belgium) and detection threshold of FA was 0.01 g/100 g of FA. All FA composition results are expressed as g/100 g of FA.

DNA extraction from rumen microbial samples

Genomic DNA was extracted from 1 ml of rumen microbial suspension using the Fast DNA SPIN kit for soil (Qbiogene, Carlsbad, CA, USA) with some modifications. Briefly, each sample was thawed and transferred to a 15 ml tube containing 4.5 ml of lysis buffer (500 mM-NaCl; 50 mM-Tris-HCl, pH 8.0; 50 mM-EDTA and 4% SDS) and incubated for 15 min at 70°C with gentle shaking by hand every 5 min. After centrifuging at 200 × g at 4°C for 5 min, 1 ml of the supernatant was transferred to a 2 ml centrifuge tube and centrifuged at 14,600 × g at 4°C for 5 min. The supernatant was removed and the pellet was dissolved in 978 μl of buffer sodium phosphate and 122 μl of MT buffer (both solutions are supplied by the Fast DNA SPIN kit for soil). Each sample was homogenized with a FastPrep cell disrupter instrument (Bio101, ThermoSavant, Qbiogene, Carlsbad, CA, USA) for 2 × 40 s at speed 6.0 and then processed according to the manufacturer's guidelines. This combination of methods was used to maximize the recovery of DNA from ruminal digesta. DNA was eluted in sterile water and its integrity was verified by agarose gel electrophoresis. The amount and the purity of DNA was measured at 260 and 280 nm using ND-1000 Spectrophotometer (NanoDrop Technologies, Labtech, Ringmer, UK).

PCR-DGGE analysis of the total bacterial community, Butyrivibrioand methanogens groups

Individual total DNA extracted from rumen samples was diluted to a concentration of 5 ng/μl and 2 μl of diluted DNA was used as template in PCR reactions. Amplification of the V6-V8 region of the 16S rRNA gene was carried out with the primer pair F968GC (5’-CGC CCG CCG CGC GCG GCG GGC GGG GCG GGG GCA CGG GGG GAA CGC GAA GAA CCT TAC-3’) and R1401 (5’-CGG TGT GTA CAA GAC CC-3’) [29] for total eubacterial PCR (fragment size ~470 bp) and with F968GC and Bfib (5’-TTC GGG CAT TYC CRA CT-3’) [30] for Butyrivibrio group-specific PCR (fragment size ~470 bp). In addition, primer pair F787GC (5’-CGC CCG CCG CGC CCC GCG CCC GTC CCG CCG CCC CCG CCC GAT TAG ATA CCC SBG TAG TCC-3’) and R1240 (5’-CCA TTG TAG CCC GCG T-3’) [31], targeting the V5-V7 region of the 16S rRNA gene (~480 bp), was used for ruminal methanogenic community profiling. Reactions were carried out using an iCycler Thermal Cycler (Bio-Rad Laboratories, Hertfordshire, UK) in 25 μl volumes containing 1X PCR buffer (67 mM-Tris-HCl, pH 8.8; 1.66 mM-(NH4)2SO4; 0.1% Tween-20), 1.5 mM-MgCl2, 250 μM-deoxynucleotide triphosphates (dNTPs), 400 nM each primer, and 1U of Polytaq (Polymed, Florence, Italy). Amplifications were performed under the following conditions: an initial denaturation of 94°C for 5 min followed by 35 cycles of 94°C for 20 s, 56°C (total bacteria and Butyrivibrio group) or 55°C (methanogens) for 30 s and 72°C for 45 s, and a final extension of 72°C for 10 min. After PCR, amplified products were verified by agarose gel electrophoresis. Subsequently, in order to perform polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) analysis, amplicons were loaded on a 6% polyacrylamide gel (acrylamide/bis 37.5:1), with a 50-60% (total bacteria and Butyrivibrio group) or 50-65% (methanogens) denaturing gradient (100% denaturant consisting of 40% v/v deionized formamide, 7 M-urea) and electrophoresis was performed in a Phor-U system (Ingeny International, Goes, NL). The gel was run for 17 h at 60°C and 75 V and, after electrophoresis, stained with SYBR® Gold (Molecular Probes, Eugene, OR) and scanned using ChemiDoc XRS (Bio-Rad Laboratories, Hertfordshire, UK).

The PCR-DGGE banding patterns obtained were analyzed using the software package GelCompar II Software v 4.6 (Applied Maths, Saint-Martens-Latem, Belgium). Normalization of bands within and between gels was performed by defining an active reference system. To summarize the species number of rumen bacterial communities, each band was considered as corresponding to a single microbial specie. Bands with a minimum area below 1% were discarded.

The banding patterns of PCR-DGGEs were further analyzed by hierarchical cluster analysis based on position and presence/absence of bands in the different profiles. The resultant binary matrices were translated into distance matrices using the Dice similarity coefficient and utilized to construct dendrogram using the unweighted pair group method using arithmetic average (UPGMA) algorithm.

Sequence analysis of PCR-DGGE fragments

A total of 30 bands were excised from the DGGE gels and were placed in 20 μl distilled water. The PCR products were eluted through freezing and thawing according to Throbäck et al. [32] and reamplified using the F968/R1401, F968/Bfib or F787/1240R primers without GC clamp, as described above. The fresh PCR products were then sequenced by dideoxy chain termination method at BMR Genomics sequencing service (BMR Genomics srl, Padova, Italy). Sequence chromatograms were visualized using the computer software Finch TV (ver. 1.4.0, Geospiza, Seattle, USA). Nucleotide sequences were compared against all sequences in GenBank release using BLASTN program [33] in order to identify the microorganisms corresponding to each selected band. Taxonomic identification was achieved by using different sequence similarity thresholds: a similarity ≥97% for a species level identification and 95%, 90%, 85%, 80% and 75% for assignment at the genus, family, order, class and phylum level, respectively [34].

For phylogenetic analysis sequences were aligned together with other sequences of equivalent length retrieved from the GenBank database, using the ClustalX 2.0.11 multiple sequence alignment software [35]. Distance calculation was performed according to Jukes and Cantor [36] followed by phylogenetic tree construction using the neighbor-joining algorithm [37] by means of TREECON 1.3b [38]. The robustness of each node was evaluated by bootstrap analysis with 1000 replicates.

Statistical analysis of fatty acids data

Data of FA concentration were analysed according to Buccioni et al. [1] and processed by General Linear Model of SAS [39] using the following linear model with fixed factors: diet and incubation time as well as their interaction.
y i j = μ + F 1 + T j + F i × T j + e i j

where yij is the observation; μ is the overall mean; Fi the feed (i =1 to 3); Tj the incubation time (j =1 to 3); Fi × Tj the interaction between feed and incubation time and eij the residual error. Multiple comparisons of means were made using Tukey’s adjustment. Main effect and differences were considered significant when P < 0.05.

Availability of supporting data

Nucleotide sequences from this study have been deposited in the GenBank database. Those from DGGE bands obtained with universal primer pair F968GC /R1401 targeting bacterial 16SrRNA gene have been deposited in the GenBank database under the accession numbers KF976364–KF976382. Those from DGGE bands obtained with primer pair F968GC/Bfib specific for the Butyrivibrio group have been deposited in GenBank under accession numbers KF976383-KF976387.

Band matching tables of Bacteria and Butyrivibrio DGGE profiles according to diet and time of sampling have been deposited to LabArchives, LLC (http://www.labarchives.com/) DOI: https://dx.doi.org/10.6070/H4HH6H16.

Abbreviations

α-LNA: 

α-linolenic acid

BH: 

Biohydrogenation

CALNA: 

Conjugated linolenic acid

CLA: 

Conjugated linoleic acids

FA: 

Fatty acids

FAME: 

Fatty acid methylesters

LA: 

Linoleic acid

OA: 

Oleic acid

PCR-DGGE: 

Polymerase chain reaction denaturing gradient gel electrophoresis

RA: 

Rumenic acid

RL: 

Rumen liquor

SA: 

Stearic acid

SOP: 

Stoned olive pomace

VA: 

Vaccenic acid

VFA: 

Volatile fatty acids

VLA: 

Vaccelenic acid

Declarations

Aknowledgments

This work was supported by the Agricultural Department or Regione Toscana- Italy (NUTRIFOROIL Project DD 6107/2013), and by University of Florence (Fondi di Ricerca di Ateneo 2012-13).

Authors’ Affiliations

(1)
Dipartimento di Scienze delle Produzioni Agro-alimentari e dell’Ambiente, Università di Firenze
(2)
Centro di Ricerca per l’Agrobiologia e la Pedologia, Consiglio per la Ricerca e la Sperimentazione in Agricoltura
(3)
Dipartimento di Scienze Agrarie, Alimentari e Agro-ambientali, Università di Pisa
(4)
Dipartimento di Biologia Applicata, Università di Perugia
(5)
Dipartimento di Scienze Economico-Estimative e degli Alimenti, Università di Perugia

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