Archives of Microbiology

, Volume 200, Issue 1, pp 137–145 | Cite as

Fecal microbiota of lambs fed purple prairie clover (Dalea purpurea Vent.) and alfalfa (Medicago sativa)

  • Qianqian Huang
  • Devin B. Holman
  • Trevor Alexander
  • Tianming Hu
  • Long Jin
  • Zhongjun Xu
  • Tim A. McAllister
  • Surya Acharya
  • Guoqi Zhao
  • Yuxi Wang
Original Paper

Abstract

The present study assessed the effect of purple prairie clover (PPC) and PPC condensed tannins (CT) on the fecal microbiota of lambs using high-throughput 16S rRNA gene pyrosequencing. A total of 18 individual lambs were randomly divided into three groups and fed either green chop alfalfa (Alf), a 40:60 (DM basis; Mix) mixture of Alf and PPC, or Mix supplemented with polyethylene glycol (Mix-P) for 18 days. Fecal samples were collected on days 13 through 18 using digital rectal retrieval. The DNA of fecal samples was extracted and the microbial 16S rRNA gene amplicons were sequenced using 454 pyrosequencing. Regardless of diet, the bacterial community was dominated by Firmicutes and Bacteroidetes with many sequences unclassified at the genus level. Forage type and CT had no effect on the fecal microbial composition at the phylum level or on α-diversity. Compared to the Alf diet, the Mix diet reduced the relative abundance of Akkermansia (P = 0.03) and Asteroleplasma (P = 0.05). Fecal microbial populations in Alf and Mix-P clustered separately from each other when assessed using unweighted UniFrac (P < 0.05). These results indicate that PPC CT up to 36 g/kg DM in the diet had no major effect on fecal microbial flora at the phyla level and exerted only minor effects on the genera composition of fecal microbiota in lambs.

Keywords

Purple prairie clover Condensed tannins 454 Pyrosequencing Gut microbiota 

Introduction

The mammalian gut microbiota comprises a rich and diverse community of bacteria, with bacterial populations in the lower gastrointestinal (GI) tract reaching numbers of 1011 colony forming unit (CFU)/g of digesta or greater (Hume 1997; Shterzer and Mizrahi 2015). The gut microbiota supplies vital nutrients to the host, stimulates immune function, prevents colonization by pathogens, converts metabolites to useable energy, and beneficially interacts with host cells (Flint et al. 2007). As a result, the alteration of its composition can have profound nutritional and health impacts on the host animal. The gut microbiota of ruminants is known to be affected by diet, gender, age, genetics, and environmental factors such as weather (Durso et al. 2010; Kim et al. 2014). In contrast to the rumen microbiota and factors affecting its composition, research on the microbiota in the hindgut of ruminants is more limited. However, the development of novel strategies for improving animal health and production performance requires a better understanding of these complex hindgut microbial populations.

Dietary tannins have been reported to alter gut microbial populations with the majority of research focusing on their effects on rumen microbiota (Jakhesara et al. 2010; Min et al. 2002; Vasta et al. 2010). A few studies have investigated their effects on hindgut microbial populations (Min et al. 2014; Smith and Mackie 2004). For example, an increase in the relative abundance of Enterobacteriaceae and Bacteroides species was observed in the GI tract of rats that were fed condensed tannins (CT) extracted from Acacia angustissima (Smith and Mackie 2004). It was also reported that CT in pine bark decreased the proportion of Gram-positive bacteria within the total bacterial population in the intestinal tract of goats (Min et al. 2014). Condensed tannins in purple prairie clover (PPC; Dalea purpurea Vent.), a legume widely distributed across North American grasslands, have been shown to have strong anti-Escherichia coli and anti-E. coli O157:H7 activity in vitro (Liu et al. 2013; Wang et al. 2013) and in vivo (Huang et al. 2015; Jin et al. 2015). Feeding ruminants a diet supplemented with PPC is a promising strategy to mitigate E. coli O157:H7 colonization and shedding in the ruminant GI tract. The hindgut in ruminants is the major site of E. coli and E. coli O157:H7 colonization (Grauke et al. 2002). The decreased fecal shedding of E. coli and E. coli O157:H7 in lambs fed PPC CT observed in previous studies suggest that CT may exert antimicrobial activity in the hindgut of ruminants, possibly affecting the entire gut microbiota (Huang et al. 2015; Jin et al. 2015).

In recent years, high-throughput 16S rRNA gene amplicon sequencing has been used to characterize the gut microbiota of mammals, including ruminants (Callaway et al. 2010; Dowd et al. 2008; Durso et al. 2010). To our knowledge, only two studies have examined the effects of tannins on the gut microbiota of goats using high-throughput sequencing (Jakhesara et al. 2010; Min et al. 2014). The objective of this study was to investigate the impact of feeding PPC and PPC CT on the hindgut microbiota of lambs using 16S rRNA gene pyrosequencing.

Materials and methods

Animals, dietary treatment, and experimental procedure

Detailed information about animals, diets, and treatment arrangements are described in Huang et al. (2015). Briefly, 18 Canadian Arcott lambs (12 males, 6 females; 37.2 ± 1.24 kg body weight (BW) that were 120 ± 10 days old were stratified by BW, age, and sex and divided into three groups which were randomly assigned to dietary treatments of 100% alfalfa (Alf), a mixture of alfalfa and PPC (Mix) in a ratio of 40:60 (DM basis), and Mix supplemented with polyethylene glycol (Mix-P). A polyethylene glycol (PEG; MW 6000; Sigma) solution (333 g/L) was sprayed on half of the Mix at the rate of 250 mL/kg DM prior to feeding. The amount of PEG applied to this diet was estimated by the ratio of 1.0 g (CT):2.0 g (PEG) to as means of deactivating the biological activity of CT (Makkar et al. 1995). Therefore, responses that occurred with the Mix diet, but not with the Mix-P diet, were attributed to the presence of CT.

Lambs were fed a diet containing 40% barley silage and 60% alfalfa hay in individual pens (pen size 1.2 × 2.5 m) located in climate-controlled rooms prior to assignment to experimental diets. Lambs were fed the experimental diets twice daily (08:00 and 16:00 h) ad libitum during the 12-day adaption period and to 90% of the ad libitum intake during the subsequent collection period. Fecal samples were collected daily on day 13 to day 18 from each lamb using digital rectal retrieval. Fecal samples were stored immediately at −80 °C in a sealed container and composited for each lamb over the 6-day period. Lambs had free access to freshwater and a mineral–vitamin block and were cared for according to the guidelines of the Canadian Council on Animal Care (CCAC 2009) during the entire experimental period. The experimental protocol was reviewed and approved by the Lethbridge Research and Development Centre Animal Care Committee.

DNA extraction, amplification, and 454 pyrosequencing

Total DNA was extracted from each fecal sample using a PowerSoil® DNA isolation kit (Mo Bio Laboratories, Inc., Carlsbad, CA) according to the manufacturer’s instructions. The quantification of DNA was determined by a Nanodrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE).

The universal eubacterial primers 27-F (AGRGTTTGATCMTGGCTCAG) and 519-R (GWATTACCGCGGCKGCTG) (Gunderson et al. 1986) were used to amplify the V1 to V3 region of the 16S rRNA gene. A unique 8-bp barcode was added to the forward primer to allow for pooling prior to sequencing. All amplification and sequencing steps were carried out at the Molecular Research LP (MR DNA; Shallowater, TX, USA). Briefly, 16S rRNA gene amplicons were generated using a HotStarTaq Plus Master Mix Kit (Qiagen) with the following PCR conditions: a 3 min initial denaturation at 94 °C followed by 28 cycles of 94 °C for 30 s, 53 °C for 40 s, and 72 °C for 1 min, with a final extension of 5 min at 72 °C. Amplicons from all samples were then mixed together in equal concentrations and purified with Agencourt Ampure beads (Agencourt Bioscience Corporation, MA, USA). Amplicons were then sequenced on a 454 Genome Sequencer FLX Titanium system (454 Life Sciences, Roche Diagnostics Corporation, Branford, CT).

Data processing and statistical analysis

Raw 16S rRNA gene sequences were processed and analyzed using the QIIME software package v. 1.9.1 (Caporaso et al. 2010b). Briefly, sequences were initially demultiplexed with the removal of primers and barcodes and quality filtered using the split libraries.py command which accomplished the removal of sequences having a length <200 bp, a Phred score of <30, and homopolymer runs of >6 bp. Chimeric sequences were removed using the UCHIME algorithm (Edgar et al. 2011) implemented in USEARCH v. 6.1544 (Edgar 2010) and sequences were clustered into OTUs using an open-reference picking protocol at a 97% similarity and performed by USEARCH (Edgar 2010) along with the SILVA database (v. 119, Quast et al. 2013). The UCLUST consensus taxonomy assigner with a minimum similarity of 0.9 and max accepts of 3 (Edgar 2010) was used to assign taxonomy and sequences were aligned using PyNAST (Caporaso et al. 2010a). Doubletons, that is, those OTUs found only twice or less in the entire dataset, were also removed prior to downstream analysis. Sequences were submitted to the NCBI Sequence Read Archive (SRA) under project accession number PRJNA296669 (http://www.ncbi.nlm.nih.gov/sra).

For subsequent alpha (within-sample) and beta (between-sample) diversity analysis, the OTU table was randomly subsampled and rarefied to 5000 sequences per sample. The diversity, richness, and evenness of each sample were calculated within QIIME using the Shannon index (Shannon 1948), phylogenetic diversity (PD whole tree) (Faith 1993), and equitability. Beta-diversity was assessed using unweighted and weighted UniFrac distances (Lozupone and Knight 2005) and visualized as principal coordinate analysis (PCoA) plots using Emperor (Vázquez-Baeza et al. 2013). Weighted UniFrac takes into account the relative abundance of OTUs, whereas unweighted UniFrac considers only community membership such as the presence/absence of OTUs (Navas-Molina et al. 2013). The unweighted and weighted UniFrac distances for the different diet groups were compared using ANOSIM (analysis of similarities) with 999 permutations. Differentially abundant OTUs were identified using the G test with the false discovery rate (FDR) correction (Benjamini and Hochberg 1995). All results were considered significant at P < 0.05.

The relative abundance of taxa and diversity indices among groups of lambs was statistically analyzed with analysis of variance using the Mixed procedure of SAS Institute Inc (2009) with diet as a main effect and individual lamb as a random factor. Differences were determined using LSMEANS with the PDIFF option in SAS Institute Inc (2009) with significance declared at P < 0.05 and a trend as a P value between 0.05 and 0.1.

Results

Lamb fecal microbiota

A total of 210,382 quality-filtered sequences with an average length of 455 bp were obtained from the 17 composite fecal samples. There were 14 different phyla and 99 unique genera among these samples (Tables 1, 2). Overall, the lamb fecal microbiota was dominated by the Firmicutes at the phylum level (77.4%), and at the genus level the RC 9 gut group and Campylobacter were relatively the most abundant. However, on average, 77.5% of sequences could not be classified to a particular genus, although 62.3% of these unclassified sequences were identified as belonging to the Peptostreptococcaceae and Ruminococcaceae families. There were also 45 OTUs that were found in all samples and of these, 36 were also classified at the family level as either Peptostreptococcaceae or Ruminococcaceae.
Table 1

The percentage of relative abundance of each bacterial phylum identified in the fecal microbiota of lambs fed either alfalfa (Alf), a mixture of purple prairie clover and alfalfa (Mix), or Mix supplemented with polyethylene glycol (Mix-P)

Phylum

Mix

Mix-P

Alf

SEM

P value

Firmicutes

75.0

80.3

76.4

3.14

0.45

Bacteroidetes

13.5

11

11.9

1.95

0.66

Proteobacteria

3.87

3.93

5.31

1.58

0.77

Tenericutes

1.01b

1.36ab

2.44a

0.44

0.04

Cyanobacteria

1.27

0.91

0.66

0.70

0.83

Planctomycetes

0.58

0.65

0.89

0.16

0.36

Verrucomicrobia

0.34

1.12

1.58

0.74

0.45

Lentisphaerae

0.2

0.21

0.39

0.1

0.34

Actinobacteria

0.16

0.24

0.17

0.04

0.37

Spirochetes

0.03

0.02

0.03

0.01

0.80

Synergistetes

0.01

0.01

0.0

0.01

0.56

TM7

0.01

0.13

0.12

0.07

0.43

Fibrobacteres

0.21

0.01

0.01

0.1

 0.31

SEM standard error of the mean

a,b Mean with different letters in a row differ (P < 0.05)

Table 2

Bacterial genera with a percent relative abundance greater than 0.01% in the feces of lambs fed either alfalfa (Alf), a mixture (Mix) of purple prairie clover (PPC) and alfalfa, or Mix supplemented with polyethylene glycol (Mix-P)

Genera

Mix

Mix-P

Alf

SEM

P value

RC9 gut group

5.74

4.55

4.64

1.26

0.76

Campylobacter

3.58

3.52

4.83

1.60

0.81

Ruminococcus

1.52

0.78

1.08

0.30

0.24

Bacteroides

1.76

0.89

1.03

0.35

0.20

Blautia

1.72

1.30

1.45

0.26

0.52

Turicibacter

1.48

1.78

1.05

0.53

0.63

Phocaeicola

1.31

0.66

0.77

0.38

0.44

Alistipes

1.13

1.29

0.96

0.3

0.75

Barnesiella

0.76ab

0.53b

1.41a

0.04

0.08

p-1088-a5 gut group

0.57

0.64

0.89

0.16

 0.35

Coprococcus

0.45

0.20

0.47

0.18

0.53

Mogibacterium

0.33

0.63

0.64

0.18

0.38

Alloprevotella

0.33

0.30

0.06

0.18

0.51

Solobacterium

0.29

0.90

0.82

0.47

0.63

Victivallis

0.19

0.21

0.39

0.10

0.34

Thalassospira

0.17

0.33

0.26

0.11

0.59

Butyrivibrio

0.14

0.19

0.35

0.07

0.16

Prevotella

0.10

0.14

0.10

0.08

0.90

Akkermansia

0.09b

0.24b

1.09a

0.26

0.03

Dorea

0.07

0.09

0.14

0.02

0.20

dgA-11 gut group

0.07

0.03

0.30

0.10

0.17

Marvinbryantia

0.06

0.15

0.19

0.08

0.54

Asteroleplasma

0.06b

0.03b

0.24a

0.06

0.05

SEM standard error of the mean

a,b,c Mean with different letters in a row differ (P < 0.05)

Among all samples (N = 18), the evenness of the microbiota was 0.78 ± 0.068 (mean ± SD) and the average number of OTUs per sample was 1235 ± 208. The Shannon index, which measures both community richness and evenness, was 5.58 ± 0.6, while the PD whole tree value, representing the phylogenetic diversity, was 67 ± 8.1. Nearly all sequences (>99%) were classified at the phylum level and 14 phyla accounted for the majority of 16S sequences among samples from all diet groups. Regardless of diet, Firmicutes and Bacteroidetes dominated the bacterial microbiota with these two phyla accounting for nearly 90% of all sequences. Proteobacteria and Tenericutes were the only two other phyla with a relative abundance greater than 1%.

The 16S rRNA gene sequences were assigned to 99 different genera, although 77.5% of these sequences could not be classified at the genus level. The relative abundance of genera that accounted for more than 0.01% of sequences among the different diet groups are presented in Table 2. The most relatively abundant genus overall was the RC9 gut group, which belongs to the Rikenellaceae family. Campylobacter, Blautia, Turicibacter, Bacteroides, Ruminococcus, and Alistipes were the only other genera accounting for more than 1% of all 16S rRNA gene sequences. Due to the fact that some Campylobacter species may be pathogenic in both humans and animals, BLASTn (https://blast.ncbi.nlm.nih.gov) was used to further classify the representative sequence of the most relatively abundant OTU (EU773268.1.1377) that were identified as Campylobacter. This OTU was exclusively identified as Campylobacter lanienae.

Effect of diet and CT on the lamb fecal microbiota

Comparisons of the evenness (equitability), richness, and diversity indices among the three diet groups revealed no significant differences (P > 0.05; Table 3), demonstrating that microbial diversity was not affected by diets. There was a significant effect of diet on the structure of the microbiota when assessed using unweighted UniFrac distances (Fig. 1a, P = 0.012; R value = 0.24). In contrast, when the effect of diet was determined using weighted UniFrac distances, no significant clustering by diet was revealed (Fig. 1b, P = 0.412, R value = 0). These results therefore suggest that diet affected the bacterial community membership rather than the relative abundance of prevalent OTUs.
Table 3

Richness, evenness, and diversity in the fecal microbiota of lambs fed either alfalfa (Alf), a mixture of purple prairie clover and alfalfa (Mix), or Mix supplemented with polyethylene glycol (Mix-P)

 

Mix

Mix-P

Alf

SEM

P value

Equitability

0.82

0.74

0.80

0.02

0.13

Number of OTUs

1325

1099

1297

79

0.13

Phylogenetic diversity (PD whole tree)

71

62

68

3.4

0.17

Shannon index

5.86

5.18

5.74

0.25

0.12

SEM standard error of the mean

Fig. 1

Principal coordinate analysis (PCoA) plot of the a unweighted UniFrac distances and b weighted UniFrac distances for lambs fed a diet with alfalfa (Alf), a mixture (Mix) of purple prairie clover (PPC) and alfalfa, or Mix supplemented with polyethylene glycol (Mix-P) on day 18 (n = 6). The percent variation explained by each principal coordinate is indicated on the axes

Dietary treatments had little effect on the fecal microbial composition at the phylum level. Although the Alf group had a higher relative abundance (P < 0.05) of Tenericutes compared to the Mix group, there were no differences between the Mix and Mix-P groups. However, the relative abundances of specific genera were affected by diet. The Mix and Mix-P groups had a lower (P < 0.05) relative abundance of Akkermansia and Asteroleplasma than the Alf group. The Alf group had a higher (P < 0.05) proportion of Barnesiella than the Mix-P group but not compared with the Mix diet group. Sequences unclassified at the genus level and belonging to the Peptococcaceae family and the NB1-n order were relatively less abundant in the Mix group than in the Alf group, but did not differ between the Mix and Mix-P groups. A total of 16 OTUs were also found to be differentially abundant among the three diet groups (Table 4; FDR <0.05). With a few exceptions, most of these OTUs were not abundant within the entire fecal population.
Table 4

Differentially abundant OTUs in the fecal microbiota of lambs fed either alfalfa (Alf), a mixture of purple prairie clover and alfalfa (Mix), or Mix supplemented with polyethylene glycol (Mix-P)

OTU name

Mix

Mix-P

Alf

FDR

Taxonomy

EU469726.1.1400

130

42.0

20.5

0.000

p__Verrucomicrobia; c__Opitutae; o__vadinHA64

EU466346.1.1380

50.4

1.67

0.833

0.000

p__Cyanobacteria; c__Melainabacteria; o__Gastranaerophilales

EU468816.1.1350

42.8

18.5

1.83

2.22E−07

p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Rikenellaceae; g__RC9 gut group

GQ448785.1.1394

31.0

5.00

1.00

1.58E−06

p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Bacteroidales Incertae Sedis; g__Phocaeicola

New.ReferenceOTU208

14.4

0.00

0.167

0.001

p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Rikenellaceae; g__RC9 gut group

EU779130.1.1402

13.2

1.33

0.00

0.019

p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Rikenellaceae; g__RC9 gut group

GQ448748.1.1375

12.8

0.000

1.33

0.027

p__Firmicutes; c__Clostridia; o__Clostridiales; f__Ruminococcaceae

EU464104.1.1353

97.4

132

23.7

0.000

p__Firmicutes; c__Clostridia; o__Clostridiales; f__Peptostreptococcaceae

New.ReferenceOTU106

4.400

16.3

0.00

0.011

p__Bacteroidetes; c__Bacteroidia; o_Bacteroidales; f__Rikenellaceae; g__RC9 gut group

JX218355.1.1491

0.600

20.5

0.00

5.27E−06

p__Firmicutes; c__Clostridia; o__Clostridiales; f__Ruminococcaceae

New.ReferenceOTU168

0.400

14.7

0.000

0.001

p__Firmicutes; c__Clostridia; o__Clostridiales; f__Ruminococcaceae

New..ReferenceOTU0

0.400

12.8

0.333

0.019

p__Cyanobacteria; c__Melainabacteria; o__Gastranaerophilales

FJ683809.1.1362

470

655

561

0.000

p__Firmicutes; c__Clostridia; o__Clostridiales; f__Peptostreptococcaceae

EU469273.1.1345

1.600

0.000

43.5

0.000

p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Rikenellaceae; g__RC9 gut group

EU470221.1.1361

0.000

1.00

14.3

0.005

p__Verrucomicrobia; c__Verrucomicrobiae; o__Verrucomicrobiales; f__Verrucomicrobiaceae; g__Akkermansia

New.ReferenceOTU5

0.600

0.333

30.5

7.87E−10

p__Tenericutes; c__Mollicutes; o__NB1-n

False discovery rate (FDR) <0.05

Discussion

Lamb fecal microbial community

To our knowledge, this is the first study to characterize the fecal bacterial community of lambs using high-throughput sequencing of the 16S rRNA gene. This approach provides superior coverage of the bacterial fecal microbiota compared to culture-based methods (Hamady and Knight 2009). In the present study, a total of 14 different phyla were identified among all fecal samples. Regardless of dietary treatment, Firmicutes and Bacteroidetes were the first and the second most prominent phyla, accounting for more than 90% of total sequences. The predominance of these two phyla in feces has previously been reported in the fecal microbiota of a number of different mammalian species including cattle (Kim et al. 2014; Shanks et al. 2011), humans (Ley et al. 2008), and pigs (Holman and Chénier 2014), as well as in the rumen of sheep (Morgavi et al. 2015). These findings attest to the importance of these phyla in the gut microbial ecosystem. The bacterial diversity observed in the ovine fecal microbiota was also comparable to that of cattle (Durso et al. 2010), horses (Steelman et al. 2012) and pigs (Holman and Chénier 2014).

A total of 99 genera were also identified in the fecal samples, with the RC9 gut group being the most abundant. These uncultured members of the Rickenellaceae family have also been recently identified as being abundant in the fecal microbiota of elephants (Ilmberger et al. 2014), horses (Rodriguez et al. 2015), and cattle (Li et al. 2014). Although 77.4% of sequences could not be assigned to a specific genus, the majority of these sequences were classified into one of two families: Peptostreptococcaceae or Ruminococcaceae. Among the 45 OTUs that were found in all fecal samples, 80% also belonged to either Peptostreptococcaceae or Ruminococcaceae and both of these families have been reported to be relatively abundant in the lower gastrointestinal tract and feces of cattle (Kim et al. 2014; Mao et al. 2015; Shanks et al. 2011). Notably, the Peptostreptococcaceae and Ruminococcaceae both contain several Clostridium species (Wunderlin et al. 2014) and therefore the large number of unclassified sequences within these families may explain why the proportion of sequences identified as Clostridium were relatively low compared to some reports in bovine feces (Callaway et al. 2010; Dowd et al. 2008). Ruminococcus, which was relatively abundant in the lamb fecal microbiota, is also a member of Ruminococcaceae.

In addition, the relative abundance of Prevotella among the classified genera was also low compared to previous reports of the cattle fecal microbiota (Kim and Wells 2016; Durso et al. 2010), although 1.2% of 16S rRNA gene sequences were classified as members of the Prevotellaceae family. The lower relative abundance of Prevotella in the present study may be attributable to factors such as host, diet, breed, age, or even climate. In the current study, lambs were fed a 100% forage diet during the whole experiment and it is noteworthy that the relative abundance of Prevotella has been reported to be negatively correlated with a diet rich in forage (Kim et al. 2014; Shanks et al. 2011).

Interestingly, Campylobacter was the second most relatively abundant genus in the ovine fecal microbiota. Some Campylobacter spp. such as C. jejuni and C. coli are frequently associated with dysentery in both human and animals; however, sheep can be asymptomatic carriers of these species (Açik and Cetinkaya 2006; Stanley and Jones 2003). Although 100 OTUs were classified as Campylobacter, the most abundant Campylobacter OTU accounted for 97.3% of these sequences. Classification of this OTU at this species level revealed that it was 100% identical to a Campylobacter lanienae strain. C. lanienae has previously been isolated from the feces of sheep (Oporto and Hurtado 2011) as well as cattle (Inglis et al. 2006) and abattoir workers (Logan et al. 2000). To date, this species has not been associated with disease in humans or animals and therefore may play a commensal role within the gut microflora of sheep.

Effect of diet and CT on fecal microbiota

The comparison of several diversity metrics revealed that PPC CT did not affect the diversity of the fecal bacterial community in lambs. The clustering by diet group was observed when the community structure was assessed using unweighted UniFrac distances (Fig. 1a), but not when using weighted UniFrac distances, suggesting that bacterial community membership rather than the proportion of specific taxa was driving changes in the fecal microbiota among the three diet cohorts. Specifically, the Alf and Mix-P fed lambs were separated from each other on the PCoA plot. The fact that PEG in the Mix-P deactivated CT suggests that the observed alterations of the gut microbiota in lambs was not solely due to CT. Non-CT phenolic compounds might also have contributed to bacterial differences, as polyphenols have been reported to alter gut bacteria in vitro through both inhibition and enhancement of the growth of specific bacterial species (Lee et al. 2006; Stoupi et al. 2010).

Only the Tenericutes phylum was differentially abundant among any of the three diet groups, with higher proportions in the Alf group compared with the Mix group. This phylum contained 1.6% of the total 16S rRNA gene sequences; however, all of these but Anaeroplasma were unclassified at the genus level. Similarly, of the genera with a relative abundance greater than 0.01%, only Barnesiella, Akkermansia, and Asteroleplasma were differentially abundant among the diet cohorts. Akkermansia, the mucin-degrading bacteria, are closely associated with immunity (Ganesh et al. 2013), obesity, and type 2 diabetes of hosts (Shin et al. 2014; Plovier et al. 2017). Increasing abundance of Akkermansia muciniphila could lower body fat mass, improve glucose homeostasis, and decrease adipose tissue inflammation in mice and human studies (Everard et al. 2013; Dao et al. 2016; Shin et al. 2014). Barnesiella also played an important role in gut microbiota, as it could ameliorate the efficacy of the most common alkylating immunomodulatory compound (Daillère et al. 2016) and prevent vancomycin-resistant Enterococcus faecium colonization (Ubeda et al. 2013). Research has shown that dietary supplementation of CT from green tea and sorghum and phenolic extract from cranberry increased the proportion of Akkermansia and Barnesiella in rat and mice model (Axling et al. 2012; Dudonné et al. 2015; Lloyd et al. 2016). However, there is no information available about the tannin effect on these genera of bacteria in ruminant intestines. In this study, the relative abundances of Akkermansia and Barnesiella in the feces of lambs fed Mix and Mix-P diet were lower than in lambs fed Alf diet. This suggested that the PPC plant may contain some compounds that could inhibit the growth of these bacteria through an unknown mechanism. The fact that the abundances of the two genera of bacteria were similar between Mix- and Pix-P-fed lambs implies that CT in PPC had no effect on them. Further research is needed to elucidate the mode of action.

In all cases, the Mix and Mix-P groups did not differ from each other in terms of the relative abundance of taxa and therefore it appears that CT from PPC had relatively little effect on fecal microbiota in lambs. This is in disagreement with the results of previous studies that investigated the effect of CT from Acacia angustissima, as Smith and Mackie (2004) identified changes in the populations of fecal bacteria in rats, with an increase in Enterobacteriaceae and Bacteroidetes. Min et al. (2014) also found that inclusion of pine bark CT at concentrations of 16 and 32 g/kg DM caused a shift in the fecal microbiota of adult goats. The CT concentration used in these studies are comparable, all around 20–30 g/kg DM, suggesting that the discrepancy among them is likely due to the differences in the CT chemical structure, as it is well known that the nutritional effects of tannins greatly depend on their great structural diversity (Mueller-Harvey 2006). Further study showed that unlike CT in other forages such as L. pedunculatus and sainfoin, CT from PPC are mainly composed of procyanidin that possesses less biological activity than prodelphinidin (Huang et al. 2017). Condensed tannins in PPC have been shown to lower fecal shedding of E. coli and E. coli O157:H7 in cattle and sheep by a traditional culture-dependent technique (Huang et al. 2015; Jin et al. 2015). However, significant difference in the relative abundance of Escherichia among three diets in this study was not observed. It is noticed that only 0.2% of the total 16S rRNA gene sequences were classified into Escherichia genus in this study, and therefore the low proportion of Escherichia and the great diversity among animals within groups might have contributed to these inconsistent results.

The lack of effects of CT on the fecal microbial community in this study contrasts with the inhibitory effects of CT on rumen microorganisms as revealed by traditional culture-dependent methods (Bae et al. 1993; Jones et al. 1994; McAllister et al. 1993; Min et al. 2005). In vivo experiments have also shown that proteolytic populations (Streptococcus bovis, Clostridium proteoclasticum, Butyrivibrio fibrisolvens, and Eubacterium sp.) were reduced in the sheep rumen by L. corniculatus CT, but these changes did not affect the ruminal microbial protein synthesis or the flow of microbial protein to the abomasum (Min et al. 2002, 2003). Jakhesara et al. (2010) reported that CT from babul pod chuni (Acacia nilotica) at a dose of 35 g/kg DM altered the microbiota in the rumen of goats, increasing the number of Bacteroidetes, Clostridia, Proteobacteria, and Actinobacteria and decreasing Metazoa, Euryarchaeota, and Cyanobacteria. The reduced CT activity against hindgut microbial activity as compared to that against rumen microbial activity in this study could partly be attributed to the different chemical structure of CT used, as well as the possibility that much of the activity of CT may have lost as they bind to proteins, carbohydrates, and minerals in the foregut. Overall, this study showed that PPC CT fed at about 36 g/kg diet had no major effect on the hindgut microbial flora at the phyla level, but altered some of the microbial populations at the genera level. This may indicate that deeper sequencing to the species level would be necessary to fully understand the effect of CT on the fecal microbial community of lambs.

Conclusions

Although the fecal microbiota of lambs fed alfalfa and PPC forage was relatively rich and diverse, it was dominated largely by Bacteroidetes and Firmicutes at the phylum level. There were also a large number of 16S rRNA gene sequences that could not be assigned to a particular genus. This may reflect the fact that the bacteria in the hindgut of sheep have not been as well characterized as other animals such as swine or cattle. Dietary CT from PPC forage at up to 36 g/kg DM did not affect fecal microbiota at the phyla level, but did alter some of the genera within the fecal bacterial population. This finding suggests that the PPC CT at the level administered had minimal impact on hindgut bacterial communities.

Notes

Acknowledgements

This study was partially funded by the Ontario Ministry of Agriculture, Food and Rural Affairs and Agriculture and Agri-Food Canada (AAFC). Qianqian Huang acknowledges the China Scholarship Council for awarding scholarship to conduct this research at Lethbridge Research and Development Centre (LeRDC) of AAFC. The authors thank the LeRDC sheep barn staff and B. Baker, D. Messenger, and F. van Herk for technical assistance. The LeRDC contribution number is 38716083.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Qianqian Huang
    • 1
    • 2
    • 3
  • Devin B. Holman
    • 2
  • Trevor Alexander
    • 2
  • Tianming Hu
    • 3
  • Long Jin
    • 2
  • Zhongjun Xu
    • 2
  • Tim A. McAllister
    • 2
  • Surya Acharya
    • 2
  • Guoqi Zhao
    • 1
  • Yuxi Wang
    • 2
  1. 1.College of Animal Science and TechnologyYangzhou UniversityYangzhouChina
  2. 2.Lethbridge Research CentreAgriculture and Agri-Food CanadaLethbridgeCanada
  3. 3.College of Animal Science and TechnologyNorthwest A&F UniversityYanglingChina

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