Shift of hindgut microbiota and microbial short chain fatty acids profiles in dairy calves from birth to pre-weaning

Shift of hindgut microbiota and microbial short chain fatty acids profiles in dairy calves from... Abstract This study aimed to characterize mucosa- and digesta-associated microbiota in the hindgut (cecum, colon and rectum) of newborn (NB, n = 6), day 7 (n = 6), day 21 (n = 6) and day 42 (n = 6) Holstein bull calves using amplicon sequencing. The hindgut microbiota was diverse at birth, and mucosa-attached microbial community had higher individual variation than that of digesta-associated community. In total, 16 phyla were identified with Firmicutes, Bacteroidetes and Proteobacteria being the dominant microbial taxa in the hindgut. Quantitative real-time PCR analysis showed a significant age effect on the proportion of mucosa-attached Escherichia coli, Bifidobacterium, Clostridium cluster XIVa and Faecalibacterium prausnitzii. Especially, high abundance of mucosa-associated Escherichia was detected during the first week of life, suggesting higher chance of the pathogenic infection during this stage. The relative abundances of predicted microbial genes involved in amino acid metabolism, carbohydrate metabolism and energy metabolism were enriched, indicating the importance of hindgut microbiota in fermentation during the pre-weaned period. Moreover, the significant correlation between short-chain fatty acid concentration and mucosa-attached carbohydrate utilizing (Coprococcus 1, Blautia, Lachnospiraceae NC2004 group, etc.) and health-related bacteria (Escherichia-Shigella and Salmonella) suggests the importance of hindgut microbiota in the fermentation and health of dairy calves during pre-weaned period. pre-weaned dairy calf, hindgut microbiota, 454 sequencing, fermentation INTRODUCTION The dairy industry in the North America has been consistently challenged with high mortality (8%–10%) and morbidity (∼38.5%) rates, which lead to on-farm economic losses and detrimental effects on the later life performance of dairy cattle (Donovan et al.1998; USDA 2010). It has also been estimated that about 50% of the pre-weaned calf deaths are caused by enteric infections (USDA 2010), which is usually caused by pathogenic organisms (Cho and Yoon 2014). Therefore, the improved gut health is one of the ways to minimize the pathogen colonization and to reduce the prevalence of enteric infections. It is known that microbes colonize the gastrointestinal tract (GIT) of mammals soon after birth and they play important roles in host immune system development, metabolism, and health of human and mouse (Gaboriau-Routhiau et al.2009; White et al.2013; Arrieta et al.2014; Subramanian et al.2015). Research on the humans and mice hindgut microbiota has revealed that the short-chain fatty acids (SCFA) including acetate, propionate and butyrate are the main microbial fermentation products (Topping and Clifton 2001) that serve as the energy source to peripheral tissue and colonic epithelial cells (Bergman 1990; Hamer et al.2009). In addition, butyrate (one of the SCFAs) has been reported to enhance the gut barrier functions (VanHook 2015). Recent research has also revealed that dysbiosis (imbalance) of the hindgut microbiota is associated with inflammatory bowel disease in human and mouse (Du et al.2015; Kabeerdoss et al.2015), further highlighting the importance of the hindgut microbiota contributing to the host functions. To date, there is limited knowledge on the hindgut microbiota and its microbial fermentation profiles in ruminants, especially in neonatal dairy calves. The GIT of a calf undergoes rapid anatomical, physiological and functional development before weaning, and pre-weaned ruminants (pre-ruminants) are usually considered functionally similar to monogastric animals (Heinrichs 2005) due to their underdeveloped rumen. When the rumen is not developed, the plant fiber, oligosaccharide and resistant starch are indigestible by host enzymes and can usually reach the colon, where they are fermented by the gut microbiota (Macfarlane and Englyst 1986; Saulnier, Kolida and Gibson 2009). In addition, the degradation of undigested proteins and fermentation of amino acids in the hindgut can produce branched-chain fatty acids, such as isobutyrate and isovalerate (Jha and Berrocoso 2016). Therefore, we hypothesized that prior to the complete development of the rumen, hindgut microbial fermentation plays an important role in providing energy to the pre-weaned calves. Previous studies on the gut microbiota of the pre-weaned calves reported that the microbial composition in the feces and the rumen varied with calf age (Uyeno, Sekiguchi and Kamagata 2010; Li et al.2012; Jami et al.2013; Oikonomou et al.2013; Klein-Jöbstl et al.2014) and weaning process (Meale et al.2016). Another study has revealed regional variations in the microbial composition along the GIT of 3-week-old pre-weaned calves, with cecum and colon microbiota similar to that of rumen (Malmuthuge, Griebel and Guan 2014). Additionally, the activity of xylanases and amylases has been detected in the cecum and colon of 28-day-old pre-weaned goats (Jiao et al.2015), indicating an active microbial fermentation in the hindgut of pre-ruminants. Yet, the understanding of the hindgut microbiota and the fermentation process is very limited in the pre-weaned dairy calves. In this study, we characterized the hindgut microbial composition and fermentation parameters during the pre-weaning period and explored the association between the hindgut microbiota and microbial fermentation from birth to 6 weeks of life. MATERIALS AND METHODS Animal study and sample collection Animal experiments were conducted at the Dairy Research and Technology Centre, University of Alberta, following the protocols approved by the Livestock Animal Care committee of the University of Alberta (protocol no., AUP00001012). All procedures were conducted following the guidelines of the Canadian Council on Animal Care, and the detailed information on the animal trial has been reported previously (Liang et al.2014). Briefly, calves were received 4 L of colostrum/day during the first 3 days after birth, and 4 L of whole milk/day from the fourth day onwards. Calves had ad libitum access to calf starter (23% crude protein and 4% ether extract, 19.5% neutral detergent fiber, 27.1% starch; Wetaskiwin Co-Op Country Junction, Wetaskiwin, AB, Canada) from day 14 to day 42 postpartum. Calves involved in this study did not have respiratory or enteric diseases, and no antibiotic treatment was given during the experimental period. In the study, 24 Holstein bull calves were humanely sacrificed at four different time points: at birth (NB; n = 6), at day 7 (D7; n = 6), at day 21 (D21; n = 6), and at day 42 (D42; n = 6) to obtain tissue and digesta samples from three different hindgut regions (cecum, colon and rectum). To prevent luminal content flowing out from the GIT following euthanasia, esophagus and rectum were first ligated and then each segment was identified and separated using table ties to prevent the potential cross contamination. The whole cecum, 10-cm-long colon (defined as 30 cm distal to the ileo-cecal junction) and 5-cm-long rectum (proximal to the anus) were collected, snap-frozen in liquid nitrogen and stored at –80°C until further analysis. The sampling locations were kept constant for all calves using the predefined anatomical land marks. DNA isolation Genomic DNA was extracted from tissue and digesta samples, respectively, using the modified repeated bead-beating and column method (Yu and Morrison 2004). For newborn samples, the whole tissue was processed due to lack of content. Digesta (∼0.5 g) and tissue (0.1–0.2 g) samples were processed from the frozen sample (Material S1, Supporting Information) and mixed with 1-mL cell lysis buffer (4% sodium dodecyl sulfate, 500 mL NaCl, 50 mM EDTA and 50 mM Tris-HCl), and were subjected to bead beating at 4800 rpm for 3 min using the BioSpec Mini-BeadBeater 8 (BioSpec, Bartlesville, OK). Lysed cells were then incubated at 70°C for 15 min, and the supernatant was collected for further process. Bead beating and incubation steps were repeated once, and all supernatants were combined. Genomic DNA was precipitated using 10 M ammonium acetate and isopropanol following by the purification using QIAamp Fast DNA Stool Mini Kit (QIAGEN Inc. CA, USA). Quantity and quality of the extracted DNA were assessed with a NanoDrop 1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). Estimation of total bacteria and selected bacterial groups in the hindgut of pre-weaned calves using quantitative real-time PCR Quantitative real-time PCR (qPCR) was performed to estimate the copy number of 16S rRNA genes of total bacteria, Bifidobacterium, Escherichia coli, Faecalibacterium prausnitzii and Clostridium cluster XIVa using universal bacterial primers and group-specific bacterial primers (Table S1, Supporting Information) with SYBR green chemistry (fast SYBR green master mix; Applied Biosystems, Foster City, CA, USA) on a StepOnePlus real-time PCR system (Applied Biosystems). The standard curves for total bacteria, Bifidobacterium, E. coli, F. prausnitzii and Clostridium cluster XIVa were generated using plasmid DNA containing the insert of Butyrivibrio hungatei for total bacteria and the cloned purified PCR products of B. longum, E. coli K12 (Malmuthuge et al.2015), F. prausnitzii A2-165 and Roseburia hominis A2-183, respectively (Ramirez-Farias et al.2009). The copy number of 16S rRNA gene of mucosa-attached and digesta-associated bacteria (copy number/g sample) was calculated using the equation described by Li et al. (2009). In addition, the proportion of Bifidobacterium, E. coli, F. prausnitzii and Clostridium cluster XIVa was calculated by dividing the copy number of each bacterial group with the copy number of total bacteria. Profiling of the hindgut microbiota using amplicon sequencing Amplification of V1–V3 hypervariable region of the 16S rRNA gene for amplicon sequencing was performed through a nested PCR-based approach (Material S2, Supporting Information). Briefly, the total bacterial full-length 16S rRNA gene was first enriched through PCR amplification with 27F and 1492R primers (27F 5΄-AGAGTTTGATCMTGGCTCAG-3΄, 1492R: 5΄-TACGGYTACCTTGTTACGACTT-3΄) (Lane 1991). Then, 10 times diluted PCR products was subjected to a second amplification with 27F and 515R primers (27F-CS1F: ACACTGACGACATGGTTCTACAGAGTTTGATCMTGGCTCAG, 515R-CS2R: TACGGTAGCAGAGACTTGGTCTCCGCGGCKGCTGGCAC) (Kroes, Lepp and Relman 1999) containing pyrotags. The amplicon DNA with targeted size (∼ 500 bp) was purified from 1% agarose gel using the QIAEX II gel extraction kit (Qiagen Science, MD, USA). The quality and quantity of purified PCR products were evaluated using a NanoDrop 1000 (NanoDrop Technologies) to ensure that the concentration of DNA from all samples was higher than 25 ng/μL. The amplicons were sequenced at Genome Quebec at McGill University (Montreal, QC, Canada) using 454-sequencing of Roche GS-FLX system with Titanium chemistry. Taxonomic identification and microbial function prediction Sequence data were analyzed using the QIIME (Quantitative Insight into Microbial Ecology) package, version 1.9 (Caporaso et al.2010). Firstly, low quality (Phred score <20) and short reads (<100 bp) were filtered out from the demultiplexed raw sequences. Then, the chimeric sequences were removed using ChimeraSlayer (Haas et al.2011) and the remaining sequences were subjected to operational taxonomic units (OTUs) identification based on 97% similarity using closed reference OTU picking function. Taxonomic characterization was performed using the SILVA database (SILVA Release 123, July 2015 release). Alpha diversity indices (Chao 1, Shannon and observed species) and Good's coverage were calculated using alpha rarefaction script within QIIME. Principal coordinate analysis (PCoA) of the microbial profiles was conducted using UniFrac distance metrices. Analysis of similarity (ANOSIM) was used to test the statistical differences among the observed microbial profiles based on sample type, age and region in the hindgut. The ‘biom file’ generated with assign taxonomy.py was used to predict the functions of the hindgut microbiota with Tax4Fun (A software package that could predict microbial function based on 16S rRNA datasets) (Aßhauer et al.2015), which is a computational approach to predict the metagenomic function with 16S rRNA marker gene and the reference genomes without using metagenomic and metatranscriptomic techniques (Aßhauer et al.2015). The functions were summarized at hierarchy level 2 of KEGG pathways. Measurement of SCFA concentration in the hindgut of pre-weaned calves About 0.1 g of digesta sample was weighed and transferred to a 5-mL tube and vortex vigorously until it was fully dissolved in 25% phosphoric acid (4:1; v:v). The concentrations of acetate, propionate, butyrate, isobutyrate, isovalerate and valerate were measured using gas chromatography, as described by Guan et al. (2008). The SCFA concentrations were presented as μmol/g fresh weight of digesta. Statistical analyses Data were analyzed using R (version 3.3.1) and SAS (version 9.4) packages. The effect of age, hindgut region and sample type on the relative abundance of detected bacterial groups was assessed using non-parametric Kruskal-Wallis test statistical method in R. The effects of the above-mentioned factors on copy number of the 16S rRNA gene of total bacteria, specific bacterial groups and SCFA concentration were analyzed using PROC MIXED and repeated measure experimental design in SAS (SAS 9.4, SAS Inc., Cary, NC, USA). The repeated measurement was the hindgut region (cecum, colon, rectum), and the experimental unit was individual calf. Compound symmetry covariance structure was selected as the best fit by the Bayesian information criteria. Analysis was performed using the following statistical model: Y = μ + Ti + Rj + TiRj + eij, where, T = age, R = hindgut region, e = residual error, Y = bacterial copy number (total bacteria, E. coli, Bifidobacterium, F. prausnitzii and Clostridium cluster XIVa), concentration of SCFA (acetate, propionate, butyrate, isobutyrate, isovalerate, valerate and total SCFA), OTUs, Observed_species, Chao 1 and Shannon index. Differences in the least square means were declared at P < 0.05. Bacterial genera with the relative abundance >0.1% and present in more than half number of the total animals at least in one age group were used to perform correlation analysis. Spearman's rank correlations were performed between the relative abundance of mucosa- and digesta-associated bacterial genera and the concentration of SCFAs (acetate, propionate, butyrate and total SCFA) as well as the proportion of 16S rRNA gene copy numbers (E. coli, Bifidobacterium, F. prausnitzii, Clostridium cluster XIVa, total bacteria) and SCFAs to understand the relationships between the hindgut bacteria and fermentation parameter. Significant correlations were declared at ρ < 0.5 or ρ > 0.5, and P-value < 0.01. Nucleotide sequence accession numbers All the sequences were deposited at NCBI Sequence Read Archive and are publicly accessible under the accession number SRP102324. The files could be found in the following link: https://trace.ncbi.nlm.nih.gov/Traces/sra_sub/sub.cgi?subid=887915&from=list&action=show:submission RESULTS The hindgut microbial community of the pre-weaned calves differed among different age groups Amplicon sequencing of the mucosa-attached microbiota generated 390 726 high-quality sequences (5426 ± 210 for cecum, 5486 ± 200 for colon and 5468 ± 199 for rectum) that were assigned to a total of 37 858 OTUs based on 97% nucleotide sequence similarity. The Good's coverage ranged between 0.917 and 0.918 (Table S2, Supporting Information) for the mucosa-attached microbial community. Similarly, 257 722 sequences (5072 ± 234 for cecum, 5067 ± 241 for colon, 5078 ± 252 for rectum) were generated for digesta-associated community that were assigned to a total of 31 300 OTUs. Good's coverage of digesta-associated microbial communities ranged from 0.894 to 0.896 (Table S2, Supporting Information). PCoA revealed that the bacterial profiles generated from mucosa-attached microbiota tended to separate (ANOSIM R = 0.34, P < 0.01) from digesta-associated communities, regardless of calf age and hindgut region (Fig. 1). Therefore, further analyses of the age and the hindgut region effects were performed separately for each microbial community. Mucosa-attached bacterial profiles formed distinct clusters according to calf age (ANOSIM R = 0.64, P < 0.01) (Fig. S1a, Supporting Information), in which profiles of NB and D7 separated from those of D21 and D42. On the other hand, the digesta-associated bacterial profiles tended to separate according to calf age (R = 0.22, P < 0.01) (Fig. S1b, Supporting Information). However, both microbial profiles did not differ among the hindgut regions (ANOSIM R = −0.03, P = 0.98 for mucosa-attached community; R = –0.04, P = 0.99 for digesta-associated community) (Fig. S1c and d, Supporting Information). Figure 1. View largeDownload slide Comparison of mucosa-attached and digesta-associated bacterial profiles with Principal Coordinate Analysis (PCoA). PCoA plot was generated using unweighted UniFrac for D7, D21 and D42 old calves. Mucosa-attached bacteria (square) and digesta-associated bacteria (dot) are plotted along the first two principal component axis (PC1 and PC2), with blue, red and purple representing different age groups. The two components explained 15.62% and 8.10% of the variance. Figure 1. View largeDownload slide Comparison of mucosa-attached and digesta-associated bacterial profiles with Principal Coordinate Analysis (PCoA). PCoA plot was generated using unweighted UniFrac for D7, D21 and D42 old calves. Mucosa-attached bacteria (square) and digesta-associated bacteria (dot) are plotted along the first two principal component axis (PC1 and PC2), with blue, red and purple representing different age groups. The two components explained 15.62% and 8.10% of the variance. When the diversity indices of the hindgut mucosa-attached microbiota were compared, the lowest number of OTUs, observed species, Chao 1 and Shannon index were observed at D7 when compared to other age groups. In addition, number of OTUs, observed species, Chao 1 and Shannon index were all significantly higher at D21 and D42 than D7 and NB (Table 1). For digesta-associated communities, lower observed species, Chao 1, Shannon index and number of OTUs were observed at D7, with no significant differences were observed among other age groups. There were no regional effects observed in the diversity of mucosa- and digesta-associated microbial communities (Table 1). Table 1. Operational taxonomic units (OTUs), bacterial diversity and richness along the hindgut of the pre-weaned calves.     Age  Hindgut region  P-value    Diversity matrix  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  OTUs  475b  429a  602c  597c  13  518  523  536  12  <0.01  0.58  attached  Observed_species  316b  254a  385c  376c  13  334  330  335  11  <0.01  0.95  bacteria  Chao 1  607b  503a  741c  707c  26  638  623  656  22  <0.01  0.58    Shannon index  6.06b  5.31a  6.60b  6.42b  0.15  6.07  6.06  6.16  0.13  <0.01  0.86  Digesta-  OTUs  NA  527a  624ab  687b  18  591  627  625  15  <0.01  0.68  associated  Observed_species  NA  334a  383ab  429b  11  369  395  388  11  <0.01  0.56  bacteria  Chao 1  NA  666a  769ab  864b  23  730  805  773  24  <0.01  0.40    Shannon index  NA  6.16a  6.51ab  6.91b  0.10  6.39  6.65  6.59  0.10  <0.01  0.49      Age  Hindgut region  P-value    Diversity matrix  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  OTUs  475b  429a  602c  597c  13  518  523  536  12  <0.01  0.58  attached  Observed_species  316b  254a  385c  376c  13  334  330  335  11  <0.01  0.95  bacteria  Chao 1  607b  503a  741c  707c  26  638  623  656  22  <0.01  0.58    Shannon index  6.06b  5.31a  6.60b  6.42b  0.15  6.07  6.06  6.16  0.13  <0.01  0.86  Digesta-  OTUs  NA  527a  624ab  687b  18  591  627  625  15  <0.01  0.68  associated  Observed_species  NA  334a  383ab  429b  11  369  395  388  11  <0.01  0.56  bacteria  Chao 1  NA  666a  769ab  864b  23  730  805  773  24  <0.01  0.40    Shannon index  NA  6.16a  6.51ab  6.91b  0.10  6.39  6.65  6.59  0.10  <0.01  0.49  NA—not applicable (lack of digesta from newborn calves for DNA extraction and amplicon sequencing) a,b,c means with different superscripts are significantly different among age groups at P < 0.01. View Large Comparison of the microbial profiles using UniFrac dissimilarity When the microbial profiles were compared using UniFrac dissimilarity index calculated based on pairwise comparisons of individual microbial profile of different groups (age, region or sample type), the mucosa-attached microbiota had a higher UniFrac dissimilarity among individuals than the digest-associated bacterial community (P < 0.01, Fig. 2). The UniFrac dissimilarity of the mucosa-attached microbial community was significantly affected by age (P < 0.01), in which the highest UniFrac dissimilarity among individuals was observed at D7 (Fig. 2). The UniFrac dissimilarity among newborn calves was higher than those at D21 and D42 but was lower than that of D7 (Fig. 2). When the similarity among individuals was compared for digesta-associated communities, a lower UniFrac dissimilarity was observed at D42 than that at D7 and D21, respectively (Fig. 2). Figure 2. View largeDownload slide Microbial uniFrac dissimilarity within groups of pre-weaned calves. Box plot showing within-group similarity, and this value was calculated based on the average of the pairwise dissimilarity between each paired sample within different groups (sample type, age and region) using unweighted UniFrac metric. The X-axis indicates different groups (sample type, age or region), and Y-axis represents the degree of uniFrac dissimilarity. The boxes represent the interquartile range (IQR) between the first and third quartiles and (25th and 75th percentage, respectively), and the vertical line inside the box is the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples with the dissimilarity value exceeding the range are represented as the circle besides the box. Different letters (a, b and c) represent uniFrac dissimilarity values that are different between groups at P < 0.05 using t-test analysis within sample type and age. Figure 2. View largeDownload slide Microbial uniFrac dissimilarity within groups of pre-weaned calves. Box plot showing within-group similarity, and this value was calculated based on the average of the pairwise dissimilarity between each paired sample within different groups (sample type, age and region) using unweighted UniFrac metric. The X-axis indicates different groups (sample type, age or region), and Y-axis represents the degree of uniFrac dissimilarity. The boxes represent the interquartile range (IQR) between the first and third quartiles and (25th and 75th percentage, respectively), and the vertical line inside the box is the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples with the dissimilarity value exceeding the range are represented as the circle besides the box. Different letters (a, b and c) represent uniFrac dissimilarity values that are different between groups at P < 0.05 using t-test analysis within sample type and age. Taxonomic composition of the newborn calf hindgut microbiota In total, 16 bacterial phyla were identified (Dataset S1a, Supporting Information) from NB hindgut microbial communities. Seven out of 16 phyla were defined as the detected bacterial phyla (the relative abundance >0.1% and present in more than half number of the total animals at least in one age group) in the NB hindgut (Fig. 3a). Proteobacteria (33.85 ± 3.75%), Firmicutes (33.32 ± 2.73%) and Bacteroidetes (28.34 ± 2.74%) accounted for the majority of the detected bacterial phyla in the hindgut at birth. At family level, 87 families were identified and 24 families were considered as detected using the same cut-off defined above (Fig. 3b). Enterobacteriaceae was the most abundant bacterial family (19.09 ± 2.38%) at birth, followed by Bacteroidaceae (18.83 ± 2.04%), Ruminococcaceae (13.66 ± 1.01%), Lachnospiraceae (10.23 ± 1.28%), Burkholderiaceae (6.23 ± 2.32%), Prevotellaceae (5.88 ± 0.52%) and Lactobacillaceae (5.26 ± 1.25%) (Dataset S1b, Supporting Information). At genus level, 250 genera were identified (Dataset S1c, Supporting Information) and 61 genera were defined as detected genera (Fig. 3c). Among them, Bacteroides (18.83 ± 1.98%) and Escherichia-Shigella (13.52 ± 1.66%) were the most abundant bacterial genera in the hindgut of newborn calves. Figure 3. View largeDownload slide Microbial composition in the hindgut of newborn calves (NB). (a) Microbial composition of NB calf at phylum level. Bars represent the relative abundance of the identified bacterial phyla (the relative abundance >0.1% and present in more than half number of the total animals at least in one age group) in different regions (cecum, colon and rectum) of hindgut. (b) Microbial composition of NB calf at family level. Bars represent the relative abundance of detectable bacterial family (the average relative abundance of the family >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. (c) Microbial composition of NB calf at genus level. Bars represent the relative abundance of detectable bacterial genera (the average relative abundance of the genus >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. Figure 3. View largeDownload slide Microbial composition in the hindgut of newborn calves (NB). (a) Microbial composition of NB calf at phylum level. Bars represent the relative abundance of the identified bacterial phyla (the relative abundance >0.1% and present in more than half number of the total animals at least in one age group) in different regions (cecum, colon and rectum) of hindgut. (b) Microbial composition of NB calf at family level. Bars represent the relative abundance of detectable bacterial family (the average relative abundance of the family >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. (c) Microbial composition of NB calf at genus level. Bars represent the relative abundance of detectable bacterial genera (the average relative abundance of the genus >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. Taxonomic composition of the hindgut mucosa-attached microbiota and shifts during pre-weaning In total, 16 phyla were identified from mucosa-attached communities of the hindgut (Dataset S2a, Supporting Information) and seven were considered as detected phyla (Table S3a, Supporting Information) in the hindgut of pre-weaned calves. The three predominant phyla in the hindgut mucosa-attached microbiota of pre-weaned calves were Bacteroidetes (35.96 ± 1.48%), Firmicutes (42.24 ± 1.81%) and Proteobacteria (14.92 ± 2.08%) (Dataset S2a, Supporting Information). The relative abundance of Proteobacteria was higher at NB (33.85 ± 2.08%) and D7 (20.52 ± 2.08%) compared to that at D21 (2.41 ± 2.08%) and D42 (2.91 ± 2.08%) (P < 0.01). In contrast to Proteobacteria, Firmicutes increased significantly (P < 0.01) at D21 (55.49 ± 1.81%) and D42 (49.26 ± 1.81%) compared with NB (33.32 ± 1.81%) and D7 (30.89 ± 1.81%). Bacteroidetes had the lowest relative abundance at NB (28.34 ± 1.48%), and started to increase after D7. The relative abundance of Fusobacteria was numerically higher at D7 (8.95 ± 1.00%) compared to that of NB (1.87 ± 1.00%), D21 (3.09 ± 1.00%) and D42 (6.60 ± 1.00%) calves (Table S3a, Supporting Information). From 120 identified families (Dataset S2b, Supporting Information), 24 were considered as detected families (Table S3b, Supporting Information). Bacteroidaceae was the predominant family in the hindgut mucosa-attached microbiota, with the highest relative abundance at D7 (26.26 ± 1.43%) compared with NB (18.83 ± 1.43%), D21 (15.65 ± 1.43%) and D42 (9.75 ± 1.43%) (P < 0.01). Enterobacteriaceae had a higher relative abundance at NB (19.09 ± 1.04%) and D7 (13.73 ± 1.04%) calves than that at D21 (1.10 ± 1.04%) and D42 (1.22 ± 1.04%) calves (P < 0.01). The relative abundance of Lactobacillaceae had a similar changing pattern as that of Enterobacteriaceae, higher at NB (5.26 ± 0.08%) and D7 (7.73 ± 0.08%) than those at D21(0.25 ± 0.08%) and D42 (0.28 ± 0.08%) calves (P < 0.01). On the contrary, the relative abundance of Ruminococcaceae was lower at NB (13.66 ± 1.06%) and D7 (10.86 ± 1.06%) compared to that at D21(27.37 ± 1.06%) and D42 (19.63 ± 1.06%) (P < 0.01). Similarly, Lanchnospiraceae had lower relative abundance at NB (10.23 ± 0.89%) and D7 (9.00 ± 0.89%) in comparison to that at D21 (23.46 ± 0.89%) and D42 (18.15 ± 0.89%) (P < 0.01), respectively. In addition, the relative abundance of Burkholderiaceae was the highest at NB (6.23 ± 0.04%) compared with that at D7 (0.13 ± 0.04%), D21(0.04 ± 0.04%) and D42 (0.37 ± 0.04%) (P < 0.01) (Table S3b, Supporting Information). At genus level, 349 genera were identified from the mucosa-attached microbial community and 61 genera were considered as detectable. Genera Bacteroides, Prevotella 9, Blautia, Lachnoclostridium, Lachnospiraceae UCG-004, Roseburia, Tuzzerella 4, Ruminococcus 2, Fusobacterium and Escherichia-Shigella were present in all the animals (Dataset S2c and Table S3c, Supporting Information). The relative abundance of Lactobacillus was higher at NB (5.26 ± 0.08%) and D7 (7.73 ± 0.08%) than that at D21 (0.25 ± 0.08%) and D42 (0.28 ± 0.08%) (P < 0.01) calves. The relative abundance of Escherichia-Shigella was higher in NB (13.52 ± 0.72%) and D7 (9.69 ± 0.72%) calves than in D21 (0.74 ± 0.72%) and D42 (0.92 ± 0.72%) (P < 0.01) calves. Similarly, Salmonella was higher at NB (2.64 ± 0.09%) and D7 (1.81 ± 0.09%) compared with D21 (0.16 ± 0.09%) and D42 (0.16 ± 0.09%) (P < 0.01). Faecalibacterium, Lachnospiraceae NC2004 group, Ruminococcaceae UCG-014 and Blautia had highest relative abundance at D21, comparing with other age groups (Table 2). Table 2. Mucosa-attached carbohydrate-utilizing and intestinal health-related bacterial genera.     Age      Phylum  Genus  NB  D7  D21  D42  SEM  P-value  Bacteroidetes  Bacteroides  18.83a  26.26b  15.65a  9.75c  1.43  <0.01  Firmicutes  Lactobacillus  5.26a  7.73a  0.25b  0.28b  0.08  <0.01    Anaerostipes  0.09ab  0.03a  0.13b  0.18b  0.02  <0.01    Blautia  2.66a  1.31a  10.55b  6.00c  0.51  <0.01    Coprococcus 1  0.05a  0.08a  0.50b  0.22c  0.03  <0.01    Coprococcus 3  0.00a  0.01a  0.04a  0.31b  0.00  <0.01    Lachnoclostridium  2.76a  2.32a  2.36a  1.65b  0.14  <0.01    Lachnospiraceae NC2004 group  0.04a  0.04a  0.19b  0.12c  0.01  <0.01    Lachnospiraceae ND3007 group  0.02a  0.00a  0.02a  0.15b  0.00  <0.01    Lachnospiraceae NK4A136 group  0.13a  0.08a  0.64b  1.09c  0.08  <0.01    Lachnospiraceae UCG-004  0.59  0.66  0.72  0.54  0.05  0.12    Lachnospiraceae UCG-008  0.19a  0.17a  0.65b  0.68b  0.06  <0.01    Pseudobutyrivibrio  0.13a  0.07a  0.57b  0.43c  0.03  <0.01    Roseburia  0.98a  0.68a  1.82b  2.23b  0.19  <0.01    Faecalibacterium  6.01a  4.54a  14.56b  7.68a  0.83  <0.01    Ruminiclostridium 5  0.04a  0.01a  0.18b  0.15b  0.01  <0.01    Ruminiclostridium 6  0.03a  0.01a  0.41b  0.44b  0.01  <0.01    Ruminiclostridium 9  0.00a  0.00a  0.11b  0.10b  0.00  <0.01    Ruminococcaceae UCG-002  0.03a  0.03a  0.14b  0.11b  0.01  <0.01    Ruminococcaceae UCG-005  0.49a  0.06b  4.31c  4.95c  0.06  <0.01    Ruminococcaceae UCG-010  0.02a  0.05a  0.10a  0.21b  0.02  <0.01    Ruminococcaceae UCG-014  0.40a  0.31a  1.59b  0.85c  0.11  <0.01    Ruminococcus 1  0.18a  0.19a  0.57b  1.00c  0.08  <0.01    Ruminococcus 2  4.61a  2.89b  1.53c  0.74c  0.27  <0.01    Erysipelatoclostridium  0.34a  0.48a  0.03b  0.04b  0.03  <0.01    Erysipelotrichaceae UCG-003  0.39a  0.07b  0.98c  0.49a  0.06  <0.01    Megasphaera  0.75a  0.47a  0.17b  0.08b  0.06  <0.01  Proteobacteria  Escherichia-Shigella  13.52a  9.69b  0.74c  0.92c  0.72  <0.01    Salmonella  2.64a  1.81b  0.16c  0.10c  0.09  <0.01      Age      Phylum  Genus  NB  D7  D21  D42  SEM  P-value  Bacteroidetes  Bacteroides  18.83a  26.26b  15.65a  9.75c  1.43  <0.01  Firmicutes  Lactobacillus  5.26a  7.73a  0.25b  0.28b  0.08  <0.01    Anaerostipes  0.09ab  0.03a  0.13b  0.18b  0.02  <0.01    Blautia  2.66a  1.31a  10.55b  6.00c  0.51  <0.01    Coprococcus 1  0.05a  0.08a  0.50b  0.22c  0.03  <0.01    Coprococcus 3  0.00a  0.01a  0.04a  0.31b  0.00  <0.01    Lachnoclostridium  2.76a  2.32a  2.36a  1.65b  0.14  <0.01    Lachnospiraceae NC2004 group  0.04a  0.04a  0.19b  0.12c  0.01  <0.01    Lachnospiraceae ND3007 group  0.02a  0.00a  0.02a  0.15b  0.00  <0.01    Lachnospiraceae NK4A136 group  0.13a  0.08a  0.64b  1.09c  0.08  <0.01    Lachnospiraceae UCG-004  0.59  0.66  0.72  0.54  0.05  0.12    Lachnospiraceae UCG-008  0.19a  0.17a  0.65b  0.68b  0.06  <0.01    Pseudobutyrivibrio  0.13a  0.07a  0.57b  0.43c  0.03  <0.01    Roseburia  0.98a  0.68a  1.82b  2.23b  0.19  <0.01    Faecalibacterium  6.01a  4.54a  14.56b  7.68a  0.83  <0.01    Ruminiclostridium 5  0.04a  0.01a  0.18b  0.15b  0.01  <0.01    Ruminiclostridium 6  0.03a  0.01a  0.41b  0.44b  0.01  <0.01    Ruminiclostridium 9  0.00a  0.00a  0.11b  0.10b  0.00  <0.01    Ruminococcaceae UCG-002  0.03a  0.03a  0.14b  0.11b  0.01  <0.01    Ruminococcaceae UCG-005  0.49a  0.06b  4.31c  4.95c  0.06  <0.01    Ruminococcaceae UCG-010  0.02a  0.05a  0.10a  0.21b  0.02  <0.01    Ruminococcaceae UCG-014  0.40a  0.31a  1.59b  0.85c  0.11  <0.01    Ruminococcus 1  0.18a  0.19a  0.57b  1.00c  0.08  <0.01    Ruminococcus 2  4.61a  2.89b  1.53c  0.74c  0.27  <0.01    Erysipelatoclostridium  0.34a  0.48a  0.03b  0.04b  0.03  <0.01    Erysipelotrichaceae UCG-003  0.39a  0.07b  0.98c  0.49a  0.06  <0.01    Megasphaera  0.75a  0.47a  0.17b  0.08b  0.06  <0.01  Proteobacteria  Escherichia-Shigella  13.52a  9.69b  0.74c  0.92c  0.72  <0.01    Salmonella  2.64a  1.81b  0.16c  0.10c  0.09  <0.01  a,b,c means with different superscripts are significantly different among age groups at P < 0.01. Values represents mean of three hindgut regions. View Large Taxonomic composition of the hindgut digesta-associated microbiota and shifts during pre-weaning period In total, 15 phyla were identified from digesta-associated microbiota (Dataset S2d, Supporting Information), with six of them being detected (Table S3d, Supporting Information). Regardless of the hindgut region, Firmicutes was the most predominant phylum detected in digesta-associated microbial community of all ages (D7—61.76 ± 1.55%; D21—73.75 ± 1.55%; D42—73.90 ± 1.55%) (P = 0.01). Bacteroidetes was the second most abundant phylum in all the age groups (D7—20.81 ± 0.89%, D21—20.94 ± 0.89%, D42—21.36 ± 0.89%). Proteobacteria was the third predominant phylum in digesta-associated microbiota community, and the relative abundance was 7.37% (± 0.66%) at D7, 1.92% (± 0.66%) at D21 and 2.05% (± 0.66%) at D42 (P < 0.01), respectively (Table S3d, Supporting Information). At family level, 83 families were identified (Dataset S2e, Supporting Information) and 20 of them were considered as detected. Digesta-associated Lactobacillaceae was the predominant family (22.36 ± 0.90% at D7; 20.01 ± 1.37% at D21; 21.01 ± 1.37% at D42) (P = 0.90). In addition, Lachnospiraceae, Bacteroidaceae and Ruminococcaceae were also the predominant families. Among all the detected families, the relative abundances of Bacteroidaceae (9.28 ± 0.59% at D7; 4.64 ± 0.59% at D21; 4.51 ± 0.59% at D42) (P < 0.01), Enterobacteriaceae (4.99 ± 0.45% at D7; 1.35 ± 0.45% at D21; 1.39 ± 0.45% at D42) (P < 0.01) and Bifidobacteriaceae (1.06 ± 0.14% at D7; 0.18 ± 0.14% at D21; 0.15 ± 0.14% at D42) (P = 0.06) were higher at D7 compared with D21 and D42. On the other hand, the relative abundances of Lachnospiraceae (17.46 ± 1.03% at D7; 25.07 ± 1.03% at D21; 23.85 ± 1.03% at D42) (P < 0.01) and Ruminococcaceae (15.59 ± 0.84% at D7; 20.10 ± 0.84% at D21; 19.67 ± 0.84% at D42) (P = 0.03) were higher at D21 and D42 compared with those at D7 (Table S3e, Supporting Information). At genus level, 50 genera were considered as detected out of the 249 identified genera. Genera Collinsella, Blautia, Lachnoclostridium, Lachnospiraceae UCG-004, Lachnospiraceae UCG-008, Roseburia, Tyzzerella 4, Intestinibacter, Faecalibacterium, Subdoligranulum and Erysipelotrichaceae UCG-003 were present in all samples (Dataset S2f and Table S3f, Supporting Information) with Lactobacillus (22.36 ± 1.37% at D7; 20.01 ± 1.37% at D21; 21.01 ± 1.37% at D42) (P = 0.90) being the most abundant genus. In addition, the relative abundances of Bacteroides (9.28 ± 0.59% at D7; 4.64 ± 0.59% at D21; 4.51 ± 0.59% at D42) (P < 0.01), Megasphaera (2.72 ± 0.24% at D7; 0.32 ± 0.24% at D21; 0.26 ± 0.24% at D42) (P < 0.01), Escherichia-Shigella (3.67 ± 0.33% at D7; 0.98 ± 0.33% at D21; 0.98 ± 0.33% at D42) (P < 0.01) and Salmonella (0.51 ± 0.05% at D7; 0.13 ± 0.05% at D21; 0.12 ± 0.05% at D42) (P = 0.03) were highest at D7. Moreover, the relative abundances of Blautia (5.50 ± 0.80% for D7, 13.42 ± 0.80% for D21, 11.87 ± 0.80% for D42) (P < 0.01), Coprococcus 1 (0.06 ± 0.02% for D7, 0.18 ± 0.02% for D21, 0.13 ± 0.02% for D42) (P < 0.01), Lachnospiraceae NK4A136 group (0.14 ± 0.03% for D7, 0.34 ± 0.03% for D21, 0.29 ± 0.03% for D42) (P < 0.01), Lachnospiraceae UCG-008 (0.55 ± 0.04% for D7, 0.71 ± 0.04% for D21, 0.81 ± 0.04% for D42) (P < 0.01), Pseudobutyrivibrio (0.29 ± 0.05% for D7, 0.73 ± 0.05% for D21, 0.65 ± 0.05% for D42) (P < 0.01), Ruminiclostridium 5 (0.07 ± 0.02% for D7, 0.21 ± 0.02% for D21, 0.18 ± 0.02% for D42) (P < 0.01), Ruminiclostridium 6 (0.13 ± 0.06% for D7, 0.36 ± 0.06% for D21, 0.33 ± 0.06% for D42) (P < 0.01) and Ruminococcus 1(0.14 ± 0.02% for D7, 0.22 ± 0.02% for D21, 0.27 ± 0.02% for D42) (P < 0.01) (P = 0.01) were higher at D21 and D42 than those at D7 (Table 3). Table 3. Digesta-associated carbohydrate-utilizing and intestinal health-related bacterial genera.     Age      Phylum  Genus  D7  D21  D42  SEM  P-value  Actinobacteria  Bifidobacterium  1.06a  0.17b  0.14b  0.14  0.04  Bacteroidetes  Bacteroides  9.28a  4.64b  4.51b  0.59  <0.01  Firmicutes  Lactobacillus  22.36  20.01  21.01  1.37  0.90    Anaerostipes  0.12  0.14  0.14  0.01  0.38    Blautia  5.50a  13.42b  11.87b  0.80  <0.01    Coprococcus 1  0.06a  0.18b  0.13b  0.02  <0.01    Lachnoclostridium  3.62  3.18  3.11  0.19  0.73    Lachnospiraceae NC2004 group  0.15  0.19  0.16  0.02  0.41    Lachnospiraceae NK4A136 group  0.14a  0.34b  0.29b  0.03  <0.01    Lachnospiraceae UCG-004  0.53  0.51  0.53  0.05  0.39    Lachnospiraceae UCG-008  0.55a  0.71ab  0.81b  0.04  <0.01    Pseudobutyrivibrio  0.29a  0.73b  0.65b  0.05  <0.01    Roseburia  1.45  0.83  1.08  0.13  0.31    Faecalibacterium  5.97  3.79  3.53  0.47  0.46    Ruminiclostridium 5  0.07a  0.21b  0.18b  0.02  <0.01    Ruminiclostridium 6  0.13a  0.36b  0.33b  0.06  <0.01    Ruminococcaceae NK4A214 group  0.14  0.08  0.14  0.01  0.06    Ruminococcaceae UCG-005  1.16a  4.76ab  6.66b  0.79  <0.01    Ruminococcaceae UCG-010  0.13  0.12  0.10  0.02  0.26    Ruminococcaceae UCG-014  1.14a  4.30b  2.69ab  0.53  <0.01    Ruminococcus 1  0.14a  0.22b  0.27b  0.02  0.01    Ruminococcus 2  1.52  1.21  0.80  0.15  0.44    Erysipelatoclostridium  0.44a  0.17b  0.13b  0.06  0.02    Erysipelotrichaceae UCG-003  0.46a  2.23b  1.48ab  0.24  <0.01    Megasphaera  2.72a  0.32b  0.26b  0.24  <0.01  Proteobacteria  Escherichia-Shigella  3.67a  0.98b  0.98b  0.33  <0.01    Salmonella  0.51a  0.13b  0.12b  0.05  0.03      Age      Phylum  Genus  D7  D21  D42  SEM  P-value  Actinobacteria  Bifidobacterium  1.06a  0.17b  0.14b  0.14  0.04  Bacteroidetes  Bacteroides  9.28a  4.64b  4.51b  0.59  <0.01  Firmicutes  Lactobacillus  22.36  20.01  21.01  1.37  0.90    Anaerostipes  0.12  0.14  0.14  0.01  0.38    Blautia  5.50a  13.42b  11.87b  0.80  <0.01    Coprococcus 1  0.06a  0.18b  0.13b  0.02  <0.01    Lachnoclostridium  3.62  3.18  3.11  0.19  0.73    Lachnospiraceae NC2004 group  0.15  0.19  0.16  0.02  0.41    Lachnospiraceae NK4A136 group  0.14a  0.34b  0.29b  0.03  <0.01    Lachnospiraceae UCG-004  0.53  0.51  0.53  0.05  0.39    Lachnospiraceae UCG-008  0.55a  0.71ab  0.81b  0.04  <0.01    Pseudobutyrivibrio  0.29a  0.73b  0.65b  0.05  <0.01    Roseburia  1.45  0.83  1.08  0.13  0.31    Faecalibacterium  5.97  3.79  3.53  0.47  0.46    Ruminiclostridium 5  0.07a  0.21b  0.18b  0.02  <0.01    Ruminiclostridium 6  0.13a  0.36b  0.33b  0.06  <0.01    Ruminococcaceae NK4A214 group  0.14  0.08  0.14  0.01  0.06    Ruminococcaceae UCG-005  1.16a  4.76ab  6.66b  0.79  <0.01    Ruminococcaceae UCG-010  0.13  0.12  0.10  0.02  0.26    Ruminococcaceae UCG-014  1.14a  4.30b  2.69ab  0.53  <0.01    Ruminococcus 1  0.14a  0.22b  0.27b  0.02  0.01    Ruminococcus 2  1.52  1.21  0.80  0.15  0.44    Erysipelatoclostridium  0.44a  0.17b  0.13b  0.06  0.02    Erysipelotrichaceae UCG-003  0.46a  2.23b  1.48ab  0.24  <0.01    Megasphaera  2.72a  0.32b  0.26b  0.24  <0.01  Proteobacteria  Escherichia-Shigella  3.67a  0.98b  0.98b  0.33  <0.01    Salmonella  0.51a  0.13b  0.12b  0.05  0.03  a,b,c means with different superscripts are significantly different among age groups at P < 0.05. Values represents mean of three hindgut regions. View Large Comparison between mucosa- and digesta-associated bacterial communities Among all the bacterial genera detected in the hindgut, 45 of them were present in both mucosa- and digesta-associated communities. Among the common bacterial genera, 30 genera were significantly different between two communities. Bacterial genera that were highly abundant in mucosa-attached community included Bacteroides, Parabacteroides, Alloprevotella, Prevotella 9, Faecalibacterium, Ruminococcus 2, Fusobacterium, Salmonella and Escherichia-Shigella, while bacterial genera Atopobium, Collinsella, Coriobacteriaceae UCG-002, Alistipes, Lactobacillus, Christensenellaceae R-7 group, Blautia, Dorea, Lachnoclostridium, Lachnospiraceae NC2004 group, Lachnospiraceae UCG-008, Pseudobutyrivibrio, Intestinibacter, Peptoclostridium, Romboutsia, Ruminiclostridium 5, Ruminococcaceae UCG-005, Ruminococcaceae UCG-014, Subdoligranulum, Erysipelotrichaceae UCG-003 and Megasphaera were highly abundant in the digesta-associated community (Table S4, Supporting Information). In addition, Rhodococcus, Moryella, Bifidobacterium, Ruminococcaceae NK4A214 group and Akkermansia were only detected in the digesta-associated microbiota, while Acidaminococcus, Sutterella, Phascolarctobacterium, Ruminiclostridium 9, Streptococcus, Lachnospiraceae ND3007 group, Pseudomonas, Ruminococcaceae UCG-002, Pantoea, Coprococcus 3, Anaerovibrio, Odoribacter, Edaphobacter, Citrobacter, Burkholderia and Prevotella 7 were only identified in mucosa-attached microbiota community (Table S4, Supporting Information). Estimation of bacterial densities in the hindgut of pre-weaned calves Estimation of selected bacteria using qPCR showed a significant age effect on the proportion of mucosa-attached E. coli, Bifidobacterium, Clostridium cluster XIVa and F. prausnitzii (Table 4). The proportion of Bifidobacterium was the highest at D7 (59.90 ± 4.33%) compared to that of other age groups regardless of the hindgut region. Escherichia coli had the highest proportion at D7 (3.57 ± 0.42%) following lower abundance at D21 (1.30 ± 0.37%) and D42 (0.75 ± 0.36%) with no difference observed between D21 and D42. The proportion of Clostridium cluster XIVa was the highest at D21 (15.83 ± 1.28%) compared to all other age groups. In the digesta-associated community, the effect of age was noted on the proportion of E. coli and Clostridium cluster XIVa (Table 4). Similar to mucosa-attached bacteria, the proportion of E. coli was the highest at D7 (0.07 ± 0.01%), while the proportion of Clostridium cluster XIVa was higher at D21 (2.90 ± 0.32%) and D42 compared with that at D7 (2.75 ± 0.29%). Table 4. Quantification of five bacterial groups in the hindgut during pre-weaned period.     Age  Hindgut region  P-value    Bacterial groups  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  Total bacteria  2.43 × 109  1.21 × 1010  1.58 × 1010  5.49 × 1010  1.93 × 109  1.10 × 1010  4.47 × 1010  8.30 × 109  1.67 × 109  0.24  0.24  attached  Escherichia colix  2.02a  3.57b  1.30ac  0.75c  0.42  2.11  1.70  1.92  0.37  <0.01  0.73  bacteria  Bifidobacteriumx  36.29a  59.90b  35.16a  10.62c  4.33  40.00  32.80  33.69  3.75  <0.01  0.34    Clostridium cluster XIVax  0.92a  4.28ab  15.83c  9.36d  1.28  7.42  6.38  8.99  1.11  <0.01  0.25    Faecalibacterium prausnitziix  0.41a  1.09ab  1.76b  0.93a  0.24  1.12  0.76  1.25  0.21  <0.01  0.23  Digesta-  Total bacteria  NA  2.02 × 1013  1.21 × 1013  1.91 × 1013  5.51 × 1012  1.31 × 1013  1.53 × 1013  2.31 × 1013  5.51 × 1012  0.53  0.39  associated  Escherichia colix  NA  0.07a  0.02b  0.01b  0.01  0.04  0.02  0.03  0.01  0.02  0.69  bacteria  Bifidobacteriumx  NA  1.51  1.85  2.51  0.33  2.20  1.88  1.79  0.32  0.08  0.62    Clostridium cluster XIVax  NA  1.64a  2.90b  2.75b  0.35  2.67  2.16  2.47  0.35  0.02  0.56    Faecalibacterium prausnitziix  NA  0.11  0.06  0.06  0.05  0.08  0.09  0.07  0.67  0.07  0.80      Age  Hindgut region  P-value    Bacterial groups  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  Total bacteria  2.43 × 109  1.21 × 1010  1.58 × 1010  5.49 × 1010  1.93 × 109  1.10 × 1010  4.47 × 1010  8.30 × 109  1.67 × 109  0.24  0.24  attached  Escherichia colix  2.02a  3.57b  1.30ac  0.75c  0.42  2.11  1.70  1.92  0.37  <0.01  0.73  bacteria  Bifidobacteriumx  36.29a  59.90b  35.16a  10.62c  4.33  40.00  32.80  33.69  3.75  <0.01  0.34    Clostridium cluster XIVax  0.92a  4.28ab  15.83c  9.36d  1.28  7.42  6.38  8.99  1.11  <0.01  0.25    Faecalibacterium prausnitziix  0.41a  1.09ab  1.76b  0.93a  0.24  1.12  0.76  1.25  0.21  <0.01  0.23  Digesta-  Total bacteria  NA  2.02 × 1013  1.21 × 1013  1.91 × 1013  5.51 × 1012  1.31 × 1013  1.53 × 1013  2.31 × 1013  5.51 × 1012  0.53  0.39  associated  Escherichia colix  NA  0.07a  0.02b  0.01b  0.01  0.04  0.02  0.03  0.01  0.02  0.69  bacteria  Bifidobacteriumx  NA  1.51  1.85  2.51  0.33  2.20  1.88  1.79  0.32  0.08  0.62    Clostridium cluster XIVax  NA  1.64a  2.90b  2.75b  0.35  2.67  2.16  2.47  0.35  0.02  0.56    Faecalibacterium prausnitziix  NA  0.11  0.06  0.06  0.05  0.08  0.09  0.07  0.67  0.07  0.80  NA—not applicable x means bacterial groups were expressed as ratio, ratio = (16S rRNA gene copy number of each bacterial groups/total bacterial 16S rRNA gene copy number) ×100. a,b,c means with different superscripts are significantly different at P < 0.05. View Large Predicted function of the hindgut microbiota in pre-weaned calves using Tax4Fun Tax4Fun-based functional prediction revealed top 10 microbial functions of the mucosa- and digesta-associated hindgut communities. These functions include ‘metabolism of cofactors and vitamins’, ‘energy metabolism’, ‘carbohydrate metabolism’, ‘amino acid metabolism’, ‘translation’, ‘replication and repair’, ‘nucleotide metabolism’, ‘signal transduction’, ‘metabolism of other amino acids’ and ‘membrane transport’ (Fig. 4a and b). In the mucosa-attached bacterial community, functions related to ‘nucleotide metabolism’, ‘translation’, ‘replication and repair’ and ‘amino acid metabolism’ were higher at D21 and D42 compared with those at NB and D7. On the other hand, ‘signal transduction’ and ‘carbohydrate metabolism’ were higher at NB and D7 compared to D21 and D42 (Fig. 4a). In the digesta-associated bacteria, the functions of ‘replication and repair’, ‘signal transduction’, ‘translation’, ‘metabolism of other amino acids’ were higher at D21 and D42 in comparison to D7. However, ‘energy metabolism’, ‘metabolism of cofactors and vitamins’ and ‘carbohydrate metabolism’ were higher at D7 when compared to D21 and D42 (Fig. 4b). Figure 4. View largeDownload slide Predicted microbial functions using Tax4fun. (a) Comparisons of the top 10 predicted microbial predominant gene pathways for mucosa-attached bacterial community among different age groups in the hindgut. (b) Comparisons of the 10 predicted microbial predominant gene pathways for digesta-associated bacterial community among different age groups in the hindgut. Star means significant difference among different age groups. Figure 4. View largeDownload slide Predicted microbial functions using Tax4fun. (a) Comparisons of the top 10 predicted microbial predominant gene pathways for mucosa-attached bacterial community among different age groups in the hindgut. (b) Comparisons of the 10 predicted microbial predominant gene pathways for digesta-associated bacterial community among different age groups in the hindgut. Star means significant difference among different age groups. Microbial SCFA detected in the hindgut of pre-weaned dairy calves Concentrations of total SCFA, acetate, propionate, butyrate, isobutyrate and isovalerate were significantly different depending on the calf age (Table 5). Concentration of acetate, butyrate and total SCFA increased from D7 onwards, with the highest concentration at D21 regardless of gut region. Propionate and isobutyrate concentration were significantly higher at D21 and D42 compared to those at D7 (Table 5). In addition, concentrations of butyrate, isobutyrate, isovalerate and valerate were significantly different among the hindgut regions, with the highest concentration detected in the rectum. Moreover, the molar proportion of acetate, propionate, butyrate, isobutyrate, isovalerate and valerate was also significantly different among the hindgut regions regardless of calf age. Table 5. SCFA concentration (μmol/g) and molar proportion in the hindgut of pre-weaned dairy calves.   Age  Region  P-value  SCFA  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Acetate  18.22a  56.71b  44.39c  4.18  40.13  40.58  38.62  4.05  <0.01  0.93  Propionate  5.47a  13.87b  12.47b  1.31  9.33  9.72  12.77  1.26  <0.01  0.09  Butyrate  3.45a  8.46b  5.95c  0.92  5.00x  5.01x  7.84y  0.89  <0.01  0.03  Isobutyrate  0.30a  1.12b  0.82b  0.15  0.51x  0.45x  1.27y  0.15  <0.01  <0.01  Isovalerate  0.71a  1.67ab  0.88b  0.27  0.67x  0.69x  1.89y  0.26  0.02  <0.01  Valerate  0.42  0.94  1.06  0.21  0.61x  0.58x  1.23y  0.20  0.06  0.03  Total SCFA  28.57a  82.77b  65.57c  6.25  56.25  57.03  63.62  6.08  <0.01  0.59  Acetate  0.67  0.69  0.67  0.02  0.70x  0.70x  0.61y  0.02  0.81  <0.01  Propionate  0.17  0.17  0.19  0.01  0.17x  0.17x  0.20y  0.01  0.77  0.03  Butyrate  0.10  0.10  0.09  0.01  0.09x  0.08xy  0.11y  0.01  0.62  0.01  Isobutyrate  0.01  0.01  0.01  0.00  0.01x  0.01x  0.02y  0.00  0.22  <0.01  Isovalerate  0.03a  0.02b  0.01c  0.00  0.02x  0.01y  0.03z  0.00  0.03  0.01  Valerate  0.01  0.01  0.02  0.00  0.01x  0.01x  0.02y  0.00  0.08  0.02    Age  Region  P-value  SCFA  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Acetate  18.22a  56.71b  44.39c  4.18  40.13  40.58  38.62  4.05  <0.01  0.93  Propionate  5.47a  13.87b  12.47b  1.31  9.33  9.72  12.77  1.26  <0.01  0.09  Butyrate  3.45a  8.46b  5.95c  0.92  5.00x  5.01x  7.84y  0.89  <0.01  0.03  Isobutyrate  0.30a  1.12b  0.82b  0.15  0.51x  0.45x  1.27y  0.15  <0.01  <0.01  Isovalerate  0.71a  1.67ab  0.88b  0.27  0.67x  0.69x  1.89y  0.26  0.02  <0.01  Valerate  0.42  0.94  1.06  0.21  0.61x  0.58x  1.23y  0.20  0.06  0.03  Total SCFA  28.57a  82.77b  65.57c  6.25  56.25  57.03  63.62  6.08  <0.01  0.59  Acetate  0.67  0.69  0.67  0.02  0.70x  0.70x  0.61y  0.02  0.81  <0.01  Propionate  0.17  0.17  0.19  0.01  0.17x  0.17x  0.20y  0.01  0.77  0.03  Butyrate  0.10  0.10  0.09  0.01  0.09x  0.08xy  0.11y  0.01  0.62  0.01  Isobutyrate  0.01  0.01  0.01  0.00  0.01x  0.01x  0.02y  0.00  0.22  <0.01  Isovalerate  0.03a  0.02b  0.01c  0.00  0.02x  0.01y  0.03z  0.00  0.03  0.01  Valerate  0.01  0.01  0.02  0.00  0.01x  0.01x  0.02y  0.00  0.08  0.02  a,b,c means with different superscripts are significantly different among age groups at P < 0.05. x,y means with different superscripts are significantly different among regions at P < 0.05. View Large Relationship between bacteria and fermentation parameters To explore the potential roles of bacteria in the hindgut fermentation, the relationship between SCFA (acetate, propionate, butyrate and total SCFA) concentrations and the relative abundance of mucosa-, digesta-associated bacterial genera was explored using Spearman's rank correlations. Acetate concentration was positively correlated with the relative abundance of carbohydrate-utilizing bacteria, including Anaerostipes (ρ = 0.59, P < 0.01), Blautia (ρ = 0.68, P < 0.01), Coprococcus 1 (ρ = 0.67, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.56, P < 0.01), Pseudobutyrivibrio (ρ = 0.63, P < 0.01), Ruminiclostridium 5 (ρ = 0.68, P < 0.01), Ruminiclostridium 6 (ρ = 0.72, P < 0.01) and Ruminiclostridium 9 (ρ = 0.55, P < 0.01). In addition, propionate concentration was positively correlated with the relative abundance of mucosa-attached Coprococcus 1 (ρ = 0.56, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.54, P < 0.01), Ruminiclostridium 6 (ρ = 0.50, P < 0.01). Moreover, butyrate concentration was positively correlated with mucosa-attached Coprococcus 1 (ρ = 0.54, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.63, P < 0.01), Faecalibacterium (ρ = 0.63, P < 0.01) and Ruminiclostridium 5 (ρ = 0.54, P < 0.01). Furthermore, total SCFA concentration was positively correlated with the relative abundance of mucosa-attached Anaerostipes (ρ = 0.53, P < 0.01), Blautia (ρ = 0.61, P < 0.01), Coprococcus 1 (ρ = 0.61, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.57, P < 0.01), Pseudobutyrivibrio (ρ = 0.56, P < 0.01), Ruminiclostridium 5 (ρ = 0.62, P < 0.01), Ruminiclostridium 6 (ρ = 0.63, P < 0.01) and Ruminiclostridium 9 (ρ = 0.50, P < 0.01). Additionally, acetate was negatively correlated with the relative abundance of Escherichia-Shigella (ρ = –0.57, P < 0.01) and Salmonella (ρ = −0.53, P < 0.01). Moreover, we identified negative correlations between mucosa-attached Bifidobacterium with acetate (ρ = –0.50, P < 0.01) and propionate (ρ = –0.57, P < 0.01) and positive correlations between mucosa-attached Clostridium cluster XIVa with acetate (ρ = 0.52, P < 0.01) and total SCFA (ρ = 0.50, P < 0.01) (Fig. 5). Figure 5. View largeDownload slide Relationship between mucosa-attached bacteria and SCFA concentration. Significant correlations were found between SCFA concentrations and the relative abundance of mucosa-attached Coriobacteriaceae UCG-002, Prevotella 9, Rikenellaceae RC9 gut group, Anaerostipes, Blautia, Coprococcus 1, Lachnospiraceae NC2004 group, Pseudobutyrivibrio, Faecalibacterium, Ruminiclostridium 5, Ruminiclostridium 6, Ruminiclostridium 9, Ruminococcaceae UCG-005 and Erysipelotrichaceae UCG-003 and the density of mucosa-attached Bifidobacterium, Clostridium cluster XIVa and total bacteria by Spearman's rank correlation. Figure 5. View largeDownload slide Relationship between mucosa-attached bacteria and SCFA concentration. Significant correlations were found between SCFA concentrations and the relative abundance of mucosa-attached Coriobacteriaceae UCG-002, Prevotella 9, Rikenellaceae RC9 gut group, Anaerostipes, Blautia, Coprococcus 1, Lachnospiraceae NC2004 group, Pseudobutyrivibrio, Faecalibacterium, Ruminiclostridium 5, Ruminiclostridium 6, Ruminiclostridium 9, Ruminococcaceae UCG-005 and Erysipelotrichaceae UCG-003 and the density of mucosa-attached Bifidobacterium, Clostridium cluster XIVa and total bacteria by Spearman's rank correlation. DISCUSSION During early life of ruminants, milk bypasses the undeveloped rumen, nutrients are digested and absorbed in the lower GIT, and the non-digestible dietary substrates are fermented in the hindgut. Therefore, the microbial colonization in the hindgut of dairy calves during the pre-weaned period plays an important role in nutrient and energy harvest. The profiling of the microbiota revealed the colonization of a diverse and dense microbial population at both mucosal surface and in the lumen of hindgut starting from the calves was born. This study is the first to report the presence of highly diverse microbiota in the hindgut of NB calves within 30 min after birth without any feeding (colostrum consumption). This suggests that the hindgut microbiota begin to colonize possibly during the birth process. The transmission process of maternal microbiota to NB calves may be similar to the findings reported for human NB infant gut microbiota, which could originate from amniotic fluid (DiGiulio 2012), meconium (Moles et al.2013) and fetal membranes (van den Berg 2006). The significant individual variation among the NB calves (Fig. S2, Supporting Information) may be due to the variations in the transmission process from the cow and birth environment (uterus, vaginal canal and fetal membranes). The predominant identified families including Bacteroidaceae, Lanchnospiraceae, Lactobacillaceae and Enterobacteriaceae in the hindgut of NB calves resembled the dominant families in 1-day-old piglets (Frese et al.2015). In addition, the presence of Lactobacillus as a predominant genus and higher relative abundance of facultative anaerobic Enterobacteriaceae family at birth and D7 is similar to fecal microbiota of vaginally delivered babies (Matamoros et al.2013) and in the human infants’ gut during early life (Arrieta et al.2014). The roles of facultative anaerobes, such as Enterobacteriaceae spp., are to create the anaerobic environment by utilizing available oxygen during the immediate neonatal period for the establishment of obligate anaerobes (Favier et al.2002). In addition, family Enterobacteriaceae also contains many potential pathogenic bacteria belong to genera Escherichia (Moxley and Francsis 1986) and Salmonella (Zhang et al.2003). The observed high abundance of mucosa-attached Escherichia-Shigella and Salmonella during the first week suggests that the calves are more susceptible to infections due to the greater abundance of opportunistic pathogens during this period. On the other hand, the higher abundance of the mucosa-attached Ruminococcus at D21 compared with D7 was observed. A recent study has reported that Ruminococcus gnavus E1 can modulate the expression of mucins-related gene and increase mucin production (Graziani et al.2016), suggesting that species belong to Ruminococcus may play a role in increasing host resistance to pathogenic bacterial invasion through reinforced barrier functions at D21. Moreover, the observed high relative abundance of obligate anaerobic Bacteroides in the hindgut of NB calf could be due to the availability of substrates after birth, such as mucus glycans. It has been reported that Bacteroides spp. including Bacteroides thetaiotaomicron and Bacteroides fragilis could utilize host mucus glycans (Marcobal et al.2011). Based on these findings, it suggests that the hindgut mucosa-associated microbiota of pre-weaned claves has similar microbial composition to that of the monogastric animals, with the capability to adapt to the anaerobic environment and potentially utilize the available substrates to define their colonization niches. Similar to adult cattle, the Firmicutes, Bacteroidetes and Proteobacteria dominated the digesta-associated hindgut microbiota of pre-weaned calves. The relative abundance of these three dominant phyla is in agreement with the reported main phyla in the fecal microbiota within the first 7 weeks of life in dairy calves (Oikonomou et al.2013). This suggests that the microbial composition in the fecal sample is representative of the digesta-associated microbiota in the hindgut. However, Bacteroidetes was dominated in the mucosa-attached community of 3-week-old calves (Malmuthuge et al.2014), whereas Firmicutes was found to be the predominant and Bacteroidetes was the second most abundant phylum in the hindgut of D21 calves in our study. Such discrepancy may be due to the use of different animals, different farm and management environments, diets and the different primers used to amplify 16S rRNA gene. The segregation of mucosa- and digesta-associated bacterial profiles confirmed the previous findings in mouse (Swidsinski et al.2005), pre-weaned dairy calves (Malmuthuge et al.2012; Malmuthuge et al.2014) and dairy cows (Mao et al.2015; Liu et al.2016). Previous findings have revealed that mucosa-attached microbiota is more diverse but has a lower microbial density (Malmuthuge et al.2015; Mao et al.2015) when compared to digesta-associated microbiota in ruminants, suggesting that the compositional difference in these two microbial communities is a common biological phenomenon. We also observed a high individual variation (higher UniFrac dissimilarity) within the mucosa-attached microbiota than that of the digesta-associated community, suggesting such segregation of these communities occurs soon after birth and their ecological niches could be an essential factor that drives the divergence. Therefore, it is vital to study both communities to generate the full understanding of the gut microbiome and their roles in the hindgut during early life. In addition to different microbial communities between two sample types (mucosa and digesta), we also observed compositional changes among age groups. The mucosa-attached bacterial community was significantly affected by the age, which might be influenced by host physiological changes (e.g. development of host immune system, epithelial integrity and growth) as well as diet during the pre-weaned period. It is noticeable that the effect of age in this study is confounded with the dietary changes. The decrease of digesta-associated Bacteroides at D21 and D42 compared to D7, similar to the reported trend in the rumen of pre-weaned calves (Li et al.2012; Rey et al.2014), could be due to the increase of age and the increased consumption of calf starter. Similarly, higher relative abundance of digesta-associated carbohydrate-utilizing bacterial genera (Blautia, Ruminococcus, Coprococcus 1, Lachnospiraceae NK4A136 group, Pseudobutyrivibrio, Ruminiclostridium 5 and Ruminiclostridium 6) at D21 compared with D7 are also due to increased intake of starter from D14, which provides available carbohydrates to stimulate the colonization of those bacterial groups. It is known that genus Bifidobacterium is highly abundant in the infants’ gut (Turroni et al.2009; Fanaro et al.2003) and our previous study revealed that the proportion of Bifidobacterium was high in the small intestine during the first 12 h of life, especially when colostrum was fed within the first 12 h of life (Malmuthuge et al.2015). In this study, the abundance of mucosa-attached Bifidobacterium (detected by qPCR) was higher at D7 than the older calves (D21 and D42), indicating the consumption of milk that is rich in oligosaccharides (Sela et al.2008; Lozupone et al.2013) could lead to higher population of this genus. In addition, the Bifidobacterium has been reported to form biofilm, which plays an important role in the prevention of pathogen invasion and stimulate the host immune functions (Hidalgo-Cantabrana et al.2013). Moreover, the abundance of Bifidobacterium has been reported to be highly correlated with the expression of genes and microRNAs that regulate host immune function in the small intestine of the same calves (Liang et al.2014). Therefore, it is important to know how the diversity of mucosa-attached Bifidobacterium could be impact by the age and how this could influence the host functions. It is noticeable that although high copy numbers of Bifidobacterium 16S rRNA genes were detected in both mucosa and digesta-associated communities, the amplicon sequencing only detected the digesta-associated Bifidobacterium. The universal bacterial primers (such as 27F and 1492R used in this study) are usually fail to amplify this genus (Malmuthuge et al.2014) because the forward primer (27F) has a few mismatches with 16S rRNA gene sequence of Bifidobacterial genus (Frank et al.2008), which leads to a lower amplification of Bifidobacterial sequences, resulting in a lower relative abundance. Therefore, future studies are needed to characterize the Bifidobacterium in the hindgut of dairy calves using Bifidobacterium-specific primers. It has been demonstrated that mucosa-attached bacteria could affect host immune system development, metabolism and health (Moxley and Francis 1986; Ivanov et al.2009). A recent study also reported that SCFA can affect the intestinal cells turnover (Park et al.2016). We speculate that the shifts in SCFA could also impact on the mucosal-attached bacteria population in addition to their impact on host tissues since the measured SCFA concentration in the lumen is the result of microbial production and host tissue absorption. The observed significant correlation between SCFA concentration and the relative abundance of mucosa-attached bacteria suggests a potential cross-talk between lumen microbial metabolites and mucosa-attached microbiota. For example, the observed negative correlation between the mucosa-attached Escherichia-Shigella abundance and acetate concentration (ρ = –0.57, P < 0.01) in the study may support our above speculation. The decreased mucosa-attached Escherichia from D7 to D21 vs D42 may be caused by the increased acetate concentration in the gut after D7, as acetate has been reported to inhibit the growth of E. coli (Fukuda et al.2011). It was surprising that no significant correlation was found between the relative abundance of digesta-associated bacteria and SCFA concentration in this study, suggesting that future analysis using the quantitative approach is needed to verify the relationship between lumen microbes and SCFA and to verify whether the lumen SCFA is important in the potential cross-talk between microbes. The higher SCFA concentrations at D21 compared with D42 and D7 (including acetate, butyrate and total SCFA) in the hindgut indicate the stronger fermentation ability of hindgut microbiota at D21 compared with D7 and D42. This could be explained by the increased development of rumen from D21 to D42 with increased solid feed intake (Malmuthuge 2016), leading to less substance available to the hindgut microbiota fermentation. The lower SCFA concentration at D7 compared with D21 and D42 also indicates the less developed and/or functional gut at this stage. However, the limitation of this study is that the daily starter intake was not recorded and it is strongly recommended to include intake measure for the future studies to link the gut microbiota and their fermentation profiles. Butyrate plays important roles in gut physiology, immune system and inflammatory response (Wang et al.2012; Arpaia et al.2013; Nastasi et al.2015). It can enhance intestinal barrier function by increasing the expression of tight junction protein related genes (claudion-1, Zonula, Occludens-1) (Wang et al.2012). Moreover, butyrate and propionate have been reported to regulate T cells production and function (Arpaia et al.2013), as well as inhibiting lipopolysaccharide-induced expression of proinflammatory cytokines IL-6 and IL-12p40 (Nastasi et al.2015). Therefore, the lower concentration of SCFA in the hindgut at D7 suggests potential lower immune function, and the importance to enhance gut health at this stage. Microbial amino acid metabolism, carbohydrate metabolism and energy metabolism are crucial functions in the hindgut, which provide energy to the host (McNeil 1984). The higher predicted microbial energy metabolism at D7 indicates that microbiota during early life tends to harvest more energy from the lumen substance for their own growth and proliferation. In addition, the significant increase in predicted amino acid metabolism of mucosa-attached bacteria at D21 and D42 suggests that bacteria tended to derive more energy from amino acid fermentation with the increase of age of calves. The observed temporal variations in the predicted microbial functions of the hindgut bacteria suggest potential temporal variations in the energy harvesting mechanisms with the changes associated with host diet. It is noticeable that the functional prediction based on 16s rRNA gene is biased and future metagenomics and metatranscriptomics are needed to assess the function of hindgut microbiome. However, the predicted function could provide preliminary information of the hindgut microbial functions of pre-weaned calves. CONCLUSION This is the first study to explore the mucosa-attached and digesta-associated microbial composition along the cecum, colon and rectum using amplicon sequencing during the pre-weaning period of dairy calves. The results showed the effect of age on both communities, while no regional effect was detected. It is important to note that calf age is confounded by the changes in dietary regimes (e.g. colostrum, whole milk and calf starter feeding), the management (e.g. housing). The potential rumen development can also influence the microbial composition in the hindgut of dairy calves during pre-weaned period. The changing pattern of the relative abundance of SCFA-producing bacterial genera including Christensenellaceae R-7 group, Blautia, Coprococcus 1, Lachnospiraceae NK4A136 group, Lachnospiraceae UCG-008, Pseudobutyrivibrio, Ruminiclostridium 5, Ruminiclostridium 6 and Ruminococcus 1 with the increase of age was accompanied by the variation of SCFA concentration in the gut, indicating the importance of hindgut microbiota on energy harvest. The higher relative abundance of potential pathogenic bacteria Escherichia-Shigella and Salmonella during the first week indicate that calves may be more susceptible to intestinal infections. However, further studies are needed to explore the functional roles of hindgut microbiota through metagenomics or metatranstriptomics-based approaches. Such knowledge may provide a comprehensive understanding of the importance of hindgut microbiota and microbial manipulation strategies for dairy industry. Overall, this preliminary study has provided fundamental knowledge on hindgut microbial profile of pre-weaned calves under the regular management practice, which is a stepping stone for future nutritional intervention and disease challenge studies to define the role of hindgut microbiota in animal production and health. SUPPLEMENTARY DATA Supplementary data are available at FEMSEC online. Acknowledgements The authors would like to thank Y. Chen, B. Yang, F. Li, O. Wang, X. Xie, A. L. Neves, and B. Ghoshal for assistance in sequencing preparation and data analysis, and acknowledge G. Liang, M. 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Shift of hindgut microbiota and microbial short chain fatty acids profiles in dairy calves from birth to pre-weaning

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Abstract

Abstract This study aimed to characterize mucosa- and digesta-associated microbiota in the hindgut (cecum, colon and rectum) of newborn (NB, n = 6), day 7 (n = 6), day 21 (n = 6) and day 42 (n = 6) Holstein bull calves using amplicon sequencing. The hindgut microbiota was diverse at birth, and mucosa-attached microbial community had higher individual variation than that of digesta-associated community. In total, 16 phyla were identified with Firmicutes, Bacteroidetes and Proteobacteria being the dominant microbial taxa in the hindgut. Quantitative real-time PCR analysis showed a significant age effect on the proportion of mucosa-attached Escherichia coli, Bifidobacterium, Clostridium cluster XIVa and Faecalibacterium prausnitzii. Especially, high abundance of mucosa-associated Escherichia was detected during the first week of life, suggesting higher chance of the pathogenic infection during this stage. The relative abundances of predicted microbial genes involved in amino acid metabolism, carbohydrate metabolism and energy metabolism were enriched, indicating the importance of hindgut microbiota in fermentation during the pre-weaned period. Moreover, the significant correlation between short-chain fatty acid concentration and mucosa-attached carbohydrate utilizing (Coprococcus 1, Blautia, Lachnospiraceae NC2004 group, etc.) and health-related bacteria (Escherichia-Shigella and Salmonella) suggests the importance of hindgut microbiota in the fermentation and health of dairy calves during pre-weaned period. pre-weaned dairy calf, hindgut microbiota, 454 sequencing, fermentation INTRODUCTION The dairy industry in the North America has been consistently challenged with high mortality (8%–10%) and morbidity (∼38.5%) rates, which lead to on-farm economic losses and detrimental effects on the later life performance of dairy cattle (Donovan et al.1998; USDA 2010). It has also been estimated that about 50% of the pre-weaned calf deaths are caused by enteric infections (USDA 2010), which is usually caused by pathogenic organisms (Cho and Yoon 2014). Therefore, the improved gut health is one of the ways to minimize the pathogen colonization and to reduce the prevalence of enteric infections. It is known that microbes colonize the gastrointestinal tract (GIT) of mammals soon after birth and they play important roles in host immune system development, metabolism, and health of human and mouse (Gaboriau-Routhiau et al.2009; White et al.2013; Arrieta et al.2014; Subramanian et al.2015). Research on the humans and mice hindgut microbiota has revealed that the short-chain fatty acids (SCFA) including acetate, propionate and butyrate are the main microbial fermentation products (Topping and Clifton 2001) that serve as the energy source to peripheral tissue and colonic epithelial cells (Bergman 1990; Hamer et al.2009). In addition, butyrate (one of the SCFAs) has been reported to enhance the gut barrier functions (VanHook 2015). Recent research has also revealed that dysbiosis (imbalance) of the hindgut microbiota is associated with inflammatory bowel disease in human and mouse (Du et al.2015; Kabeerdoss et al.2015), further highlighting the importance of the hindgut microbiota contributing to the host functions. To date, there is limited knowledge on the hindgut microbiota and its microbial fermentation profiles in ruminants, especially in neonatal dairy calves. The GIT of a calf undergoes rapid anatomical, physiological and functional development before weaning, and pre-weaned ruminants (pre-ruminants) are usually considered functionally similar to monogastric animals (Heinrichs 2005) due to their underdeveloped rumen. When the rumen is not developed, the plant fiber, oligosaccharide and resistant starch are indigestible by host enzymes and can usually reach the colon, where they are fermented by the gut microbiota (Macfarlane and Englyst 1986; Saulnier, Kolida and Gibson 2009). In addition, the degradation of undigested proteins and fermentation of amino acids in the hindgut can produce branched-chain fatty acids, such as isobutyrate and isovalerate (Jha and Berrocoso 2016). Therefore, we hypothesized that prior to the complete development of the rumen, hindgut microbial fermentation plays an important role in providing energy to the pre-weaned calves. Previous studies on the gut microbiota of the pre-weaned calves reported that the microbial composition in the feces and the rumen varied with calf age (Uyeno, Sekiguchi and Kamagata 2010; Li et al.2012; Jami et al.2013; Oikonomou et al.2013; Klein-Jöbstl et al.2014) and weaning process (Meale et al.2016). Another study has revealed regional variations in the microbial composition along the GIT of 3-week-old pre-weaned calves, with cecum and colon microbiota similar to that of rumen (Malmuthuge, Griebel and Guan 2014). Additionally, the activity of xylanases and amylases has been detected in the cecum and colon of 28-day-old pre-weaned goats (Jiao et al.2015), indicating an active microbial fermentation in the hindgut of pre-ruminants. Yet, the understanding of the hindgut microbiota and the fermentation process is very limited in the pre-weaned dairy calves. In this study, we characterized the hindgut microbial composition and fermentation parameters during the pre-weaning period and explored the association between the hindgut microbiota and microbial fermentation from birth to 6 weeks of life. MATERIALS AND METHODS Animal study and sample collection Animal experiments were conducted at the Dairy Research and Technology Centre, University of Alberta, following the protocols approved by the Livestock Animal Care committee of the University of Alberta (protocol no., AUP00001012). All procedures were conducted following the guidelines of the Canadian Council on Animal Care, and the detailed information on the animal trial has been reported previously (Liang et al.2014). Briefly, calves were received 4 L of colostrum/day during the first 3 days after birth, and 4 L of whole milk/day from the fourth day onwards. Calves had ad libitum access to calf starter (23% crude protein and 4% ether extract, 19.5% neutral detergent fiber, 27.1% starch; Wetaskiwin Co-Op Country Junction, Wetaskiwin, AB, Canada) from day 14 to day 42 postpartum. Calves involved in this study did not have respiratory or enteric diseases, and no antibiotic treatment was given during the experimental period. In the study, 24 Holstein bull calves were humanely sacrificed at four different time points: at birth (NB; n = 6), at day 7 (D7; n = 6), at day 21 (D21; n = 6), and at day 42 (D42; n = 6) to obtain tissue and digesta samples from three different hindgut regions (cecum, colon and rectum). To prevent luminal content flowing out from the GIT following euthanasia, esophagus and rectum were first ligated and then each segment was identified and separated using table ties to prevent the potential cross contamination. The whole cecum, 10-cm-long colon (defined as 30 cm distal to the ileo-cecal junction) and 5-cm-long rectum (proximal to the anus) were collected, snap-frozen in liquid nitrogen and stored at –80°C until further analysis. The sampling locations were kept constant for all calves using the predefined anatomical land marks. DNA isolation Genomic DNA was extracted from tissue and digesta samples, respectively, using the modified repeated bead-beating and column method (Yu and Morrison 2004). For newborn samples, the whole tissue was processed due to lack of content. Digesta (∼0.5 g) and tissue (0.1–0.2 g) samples were processed from the frozen sample (Material S1, Supporting Information) and mixed with 1-mL cell lysis buffer (4% sodium dodecyl sulfate, 500 mL NaCl, 50 mM EDTA and 50 mM Tris-HCl), and were subjected to bead beating at 4800 rpm for 3 min using the BioSpec Mini-BeadBeater 8 (BioSpec, Bartlesville, OK). Lysed cells were then incubated at 70°C for 15 min, and the supernatant was collected for further process. Bead beating and incubation steps were repeated once, and all supernatants were combined. Genomic DNA was precipitated using 10 M ammonium acetate and isopropanol following by the purification using QIAamp Fast DNA Stool Mini Kit (QIAGEN Inc. CA, USA). Quantity and quality of the extracted DNA were assessed with a NanoDrop 1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). Estimation of total bacteria and selected bacterial groups in the hindgut of pre-weaned calves using quantitative real-time PCR Quantitative real-time PCR (qPCR) was performed to estimate the copy number of 16S rRNA genes of total bacteria, Bifidobacterium, Escherichia coli, Faecalibacterium prausnitzii and Clostridium cluster XIVa using universal bacterial primers and group-specific bacterial primers (Table S1, Supporting Information) with SYBR green chemistry (fast SYBR green master mix; Applied Biosystems, Foster City, CA, USA) on a StepOnePlus real-time PCR system (Applied Biosystems). The standard curves for total bacteria, Bifidobacterium, E. coli, F. prausnitzii and Clostridium cluster XIVa were generated using plasmid DNA containing the insert of Butyrivibrio hungatei for total bacteria and the cloned purified PCR products of B. longum, E. coli K12 (Malmuthuge et al.2015), F. prausnitzii A2-165 and Roseburia hominis A2-183, respectively (Ramirez-Farias et al.2009). The copy number of 16S rRNA gene of mucosa-attached and digesta-associated bacteria (copy number/g sample) was calculated using the equation described by Li et al. (2009). In addition, the proportion of Bifidobacterium, E. coli, F. prausnitzii and Clostridium cluster XIVa was calculated by dividing the copy number of each bacterial group with the copy number of total bacteria. Profiling of the hindgut microbiota using amplicon sequencing Amplification of V1–V3 hypervariable region of the 16S rRNA gene for amplicon sequencing was performed through a nested PCR-based approach (Material S2, Supporting Information). Briefly, the total bacterial full-length 16S rRNA gene was first enriched through PCR amplification with 27F and 1492R primers (27F 5΄-AGAGTTTGATCMTGGCTCAG-3΄, 1492R: 5΄-TACGGYTACCTTGTTACGACTT-3΄) (Lane 1991). Then, 10 times diluted PCR products was subjected to a second amplification with 27F and 515R primers (27F-CS1F: ACACTGACGACATGGTTCTACAGAGTTTGATCMTGGCTCAG, 515R-CS2R: TACGGTAGCAGAGACTTGGTCTCCGCGGCKGCTGGCAC) (Kroes, Lepp and Relman 1999) containing pyrotags. The amplicon DNA with targeted size (∼ 500 bp) was purified from 1% agarose gel using the QIAEX II gel extraction kit (Qiagen Science, MD, USA). The quality and quantity of purified PCR products were evaluated using a NanoDrop 1000 (NanoDrop Technologies) to ensure that the concentration of DNA from all samples was higher than 25 ng/μL. The amplicons were sequenced at Genome Quebec at McGill University (Montreal, QC, Canada) using 454-sequencing of Roche GS-FLX system with Titanium chemistry. Taxonomic identification and microbial function prediction Sequence data were analyzed using the QIIME (Quantitative Insight into Microbial Ecology) package, version 1.9 (Caporaso et al.2010). Firstly, low quality (Phred score <20) and short reads (<100 bp) were filtered out from the demultiplexed raw sequences. Then, the chimeric sequences were removed using ChimeraSlayer (Haas et al.2011) and the remaining sequences were subjected to operational taxonomic units (OTUs) identification based on 97% similarity using closed reference OTU picking function. Taxonomic characterization was performed using the SILVA database (SILVA Release 123, July 2015 release). Alpha diversity indices (Chao 1, Shannon and observed species) and Good's coverage were calculated using alpha rarefaction script within QIIME. Principal coordinate analysis (PCoA) of the microbial profiles was conducted using UniFrac distance metrices. Analysis of similarity (ANOSIM) was used to test the statistical differences among the observed microbial profiles based on sample type, age and region in the hindgut. The ‘biom file’ generated with assign taxonomy.py was used to predict the functions of the hindgut microbiota with Tax4Fun (A software package that could predict microbial function based on 16S rRNA datasets) (Aßhauer et al.2015), which is a computational approach to predict the metagenomic function with 16S rRNA marker gene and the reference genomes without using metagenomic and metatranscriptomic techniques (Aßhauer et al.2015). The functions were summarized at hierarchy level 2 of KEGG pathways. Measurement of SCFA concentration in the hindgut of pre-weaned calves About 0.1 g of digesta sample was weighed and transferred to a 5-mL tube and vortex vigorously until it was fully dissolved in 25% phosphoric acid (4:1; v:v). The concentrations of acetate, propionate, butyrate, isobutyrate, isovalerate and valerate were measured using gas chromatography, as described by Guan et al. (2008). The SCFA concentrations were presented as μmol/g fresh weight of digesta. Statistical analyses Data were analyzed using R (version 3.3.1) and SAS (version 9.4) packages. The effect of age, hindgut region and sample type on the relative abundance of detected bacterial groups was assessed using non-parametric Kruskal-Wallis test statistical method in R. The effects of the above-mentioned factors on copy number of the 16S rRNA gene of total bacteria, specific bacterial groups and SCFA concentration were analyzed using PROC MIXED and repeated measure experimental design in SAS (SAS 9.4, SAS Inc., Cary, NC, USA). The repeated measurement was the hindgut region (cecum, colon, rectum), and the experimental unit was individual calf. Compound symmetry covariance structure was selected as the best fit by the Bayesian information criteria. Analysis was performed using the following statistical model: Y = μ + Ti + Rj + TiRj + eij, where, T = age, R = hindgut region, e = residual error, Y = bacterial copy number (total bacteria, E. coli, Bifidobacterium, F. prausnitzii and Clostridium cluster XIVa), concentration of SCFA (acetate, propionate, butyrate, isobutyrate, isovalerate, valerate and total SCFA), OTUs, Observed_species, Chao 1 and Shannon index. Differences in the least square means were declared at P < 0.05. Bacterial genera with the relative abundance >0.1% and present in more than half number of the total animals at least in one age group were used to perform correlation analysis. Spearman's rank correlations were performed between the relative abundance of mucosa- and digesta-associated bacterial genera and the concentration of SCFAs (acetate, propionate, butyrate and total SCFA) as well as the proportion of 16S rRNA gene copy numbers (E. coli, Bifidobacterium, F. prausnitzii, Clostridium cluster XIVa, total bacteria) and SCFAs to understand the relationships between the hindgut bacteria and fermentation parameter. Significant correlations were declared at ρ < 0.5 or ρ > 0.5, and P-value < 0.01. Nucleotide sequence accession numbers All the sequences were deposited at NCBI Sequence Read Archive and are publicly accessible under the accession number SRP102324. The files could be found in the following link: https://trace.ncbi.nlm.nih.gov/Traces/sra_sub/sub.cgi?subid=887915&from=list&action=show:submission RESULTS The hindgut microbial community of the pre-weaned calves differed among different age groups Amplicon sequencing of the mucosa-attached microbiota generated 390 726 high-quality sequences (5426 ± 210 for cecum, 5486 ± 200 for colon and 5468 ± 199 for rectum) that were assigned to a total of 37 858 OTUs based on 97% nucleotide sequence similarity. The Good's coverage ranged between 0.917 and 0.918 (Table S2, Supporting Information) for the mucosa-attached microbial community. Similarly, 257 722 sequences (5072 ± 234 for cecum, 5067 ± 241 for colon, 5078 ± 252 for rectum) were generated for digesta-associated community that were assigned to a total of 31 300 OTUs. Good's coverage of digesta-associated microbial communities ranged from 0.894 to 0.896 (Table S2, Supporting Information). PCoA revealed that the bacterial profiles generated from mucosa-attached microbiota tended to separate (ANOSIM R = 0.34, P < 0.01) from digesta-associated communities, regardless of calf age and hindgut region (Fig. 1). Therefore, further analyses of the age and the hindgut region effects were performed separately for each microbial community. Mucosa-attached bacterial profiles formed distinct clusters according to calf age (ANOSIM R = 0.64, P < 0.01) (Fig. S1a, Supporting Information), in which profiles of NB and D7 separated from those of D21 and D42. On the other hand, the digesta-associated bacterial profiles tended to separate according to calf age (R = 0.22, P < 0.01) (Fig. S1b, Supporting Information). However, both microbial profiles did not differ among the hindgut regions (ANOSIM R = −0.03, P = 0.98 for mucosa-attached community; R = –0.04, P = 0.99 for digesta-associated community) (Fig. S1c and d, Supporting Information). Figure 1. View largeDownload slide Comparison of mucosa-attached and digesta-associated bacterial profiles with Principal Coordinate Analysis (PCoA). PCoA plot was generated using unweighted UniFrac for D7, D21 and D42 old calves. Mucosa-attached bacteria (square) and digesta-associated bacteria (dot) are plotted along the first two principal component axis (PC1 and PC2), with blue, red and purple representing different age groups. The two components explained 15.62% and 8.10% of the variance. Figure 1. View largeDownload slide Comparison of mucosa-attached and digesta-associated bacterial profiles with Principal Coordinate Analysis (PCoA). PCoA plot was generated using unweighted UniFrac for D7, D21 and D42 old calves. Mucosa-attached bacteria (square) and digesta-associated bacteria (dot) are plotted along the first two principal component axis (PC1 and PC2), with blue, red and purple representing different age groups. The two components explained 15.62% and 8.10% of the variance. When the diversity indices of the hindgut mucosa-attached microbiota were compared, the lowest number of OTUs, observed species, Chao 1 and Shannon index were observed at D7 when compared to other age groups. In addition, number of OTUs, observed species, Chao 1 and Shannon index were all significantly higher at D21 and D42 than D7 and NB (Table 1). For digesta-associated communities, lower observed species, Chao 1, Shannon index and number of OTUs were observed at D7, with no significant differences were observed among other age groups. There were no regional effects observed in the diversity of mucosa- and digesta-associated microbial communities (Table 1). Table 1. Operational taxonomic units (OTUs), bacterial diversity and richness along the hindgut of the pre-weaned calves.     Age  Hindgut region  P-value    Diversity matrix  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  OTUs  475b  429a  602c  597c  13  518  523  536  12  <0.01  0.58  attached  Observed_species  316b  254a  385c  376c  13  334  330  335  11  <0.01  0.95  bacteria  Chao 1  607b  503a  741c  707c  26  638  623  656  22  <0.01  0.58    Shannon index  6.06b  5.31a  6.60b  6.42b  0.15  6.07  6.06  6.16  0.13  <0.01  0.86  Digesta-  OTUs  NA  527a  624ab  687b  18  591  627  625  15  <0.01  0.68  associated  Observed_species  NA  334a  383ab  429b  11  369  395  388  11  <0.01  0.56  bacteria  Chao 1  NA  666a  769ab  864b  23  730  805  773  24  <0.01  0.40    Shannon index  NA  6.16a  6.51ab  6.91b  0.10  6.39  6.65  6.59  0.10  <0.01  0.49      Age  Hindgut region  P-value    Diversity matrix  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  OTUs  475b  429a  602c  597c  13  518  523  536  12  <0.01  0.58  attached  Observed_species  316b  254a  385c  376c  13  334  330  335  11  <0.01  0.95  bacteria  Chao 1  607b  503a  741c  707c  26  638  623  656  22  <0.01  0.58    Shannon index  6.06b  5.31a  6.60b  6.42b  0.15  6.07  6.06  6.16  0.13  <0.01  0.86  Digesta-  OTUs  NA  527a  624ab  687b  18  591  627  625  15  <0.01  0.68  associated  Observed_species  NA  334a  383ab  429b  11  369  395  388  11  <0.01  0.56  bacteria  Chao 1  NA  666a  769ab  864b  23  730  805  773  24  <0.01  0.40    Shannon index  NA  6.16a  6.51ab  6.91b  0.10  6.39  6.65  6.59  0.10  <0.01  0.49  NA—not applicable (lack of digesta from newborn calves for DNA extraction and amplicon sequencing) a,b,c means with different superscripts are significantly different among age groups at P < 0.01. View Large Comparison of the microbial profiles using UniFrac dissimilarity When the microbial profiles were compared using UniFrac dissimilarity index calculated based on pairwise comparisons of individual microbial profile of different groups (age, region or sample type), the mucosa-attached microbiota had a higher UniFrac dissimilarity among individuals than the digest-associated bacterial community (P < 0.01, Fig. 2). The UniFrac dissimilarity of the mucosa-attached microbial community was significantly affected by age (P < 0.01), in which the highest UniFrac dissimilarity among individuals was observed at D7 (Fig. 2). The UniFrac dissimilarity among newborn calves was higher than those at D21 and D42 but was lower than that of D7 (Fig. 2). When the similarity among individuals was compared for digesta-associated communities, a lower UniFrac dissimilarity was observed at D42 than that at D7 and D21, respectively (Fig. 2). Figure 2. View largeDownload slide Microbial uniFrac dissimilarity within groups of pre-weaned calves. Box plot showing within-group similarity, and this value was calculated based on the average of the pairwise dissimilarity between each paired sample within different groups (sample type, age and region) using unweighted UniFrac metric. The X-axis indicates different groups (sample type, age or region), and Y-axis represents the degree of uniFrac dissimilarity. The boxes represent the interquartile range (IQR) between the first and third quartiles and (25th and 75th percentage, respectively), and the vertical line inside the box is the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples with the dissimilarity value exceeding the range are represented as the circle besides the box. Different letters (a, b and c) represent uniFrac dissimilarity values that are different between groups at P < 0.05 using t-test analysis within sample type and age. Figure 2. View largeDownload slide Microbial uniFrac dissimilarity within groups of pre-weaned calves. Box plot showing within-group similarity, and this value was calculated based on the average of the pairwise dissimilarity between each paired sample within different groups (sample type, age and region) using unweighted UniFrac metric. The X-axis indicates different groups (sample type, age or region), and Y-axis represents the degree of uniFrac dissimilarity. The boxes represent the interquartile range (IQR) between the first and third quartiles and (25th and 75th percentage, respectively), and the vertical line inside the box is the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples with the dissimilarity value exceeding the range are represented as the circle besides the box. Different letters (a, b and c) represent uniFrac dissimilarity values that are different between groups at P < 0.05 using t-test analysis within sample type and age. Taxonomic composition of the newborn calf hindgut microbiota In total, 16 bacterial phyla were identified (Dataset S1a, Supporting Information) from NB hindgut microbial communities. Seven out of 16 phyla were defined as the detected bacterial phyla (the relative abundance >0.1% and present in more than half number of the total animals at least in one age group) in the NB hindgut (Fig. 3a). Proteobacteria (33.85 ± 3.75%), Firmicutes (33.32 ± 2.73%) and Bacteroidetes (28.34 ± 2.74%) accounted for the majority of the detected bacterial phyla in the hindgut at birth. At family level, 87 families were identified and 24 families were considered as detected using the same cut-off defined above (Fig. 3b). Enterobacteriaceae was the most abundant bacterial family (19.09 ± 2.38%) at birth, followed by Bacteroidaceae (18.83 ± 2.04%), Ruminococcaceae (13.66 ± 1.01%), Lachnospiraceae (10.23 ± 1.28%), Burkholderiaceae (6.23 ± 2.32%), Prevotellaceae (5.88 ± 0.52%) and Lactobacillaceae (5.26 ± 1.25%) (Dataset S1b, Supporting Information). At genus level, 250 genera were identified (Dataset S1c, Supporting Information) and 61 genera were defined as detected genera (Fig. 3c). Among them, Bacteroides (18.83 ± 1.98%) and Escherichia-Shigella (13.52 ± 1.66%) were the most abundant bacterial genera in the hindgut of newborn calves. Figure 3. View largeDownload slide Microbial composition in the hindgut of newborn calves (NB). (a) Microbial composition of NB calf at phylum level. Bars represent the relative abundance of the identified bacterial phyla (the relative abundance >0.1% and present in more than half number of the total animals at least in one age group) in different regions (cecum, colon and rectum) of hindgut. (b) Microbial composition of NB calf at family level. Bars represent the relative abundance of detectable bacterial family (the average relative abundance of the family >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. (c) Microbial composition of NB calf at genus level. Bars represent the relative abundance of detectable bacterial genera (the average relative abundance of the genus >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. Figure 3. View largeDownload slide Microbial composition in the hindgut of newborn calves (NB). (a) Microbial composition of NB calf at phylum level. Bars represent the relative abundance of the identified bacterial phyla (the relative abundance >0.1% and present in more than half number of the total animals at least in one age group) in different regions (cecum, colon and rectum) of hindgut. (b) Microbial composition of NB calf at family level. Bars represent the relative abundance of detectable bacterial family (the average relative abundance of the family >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. (c) Microbial composition of NB calf at genus level. Bars represent the relative abundance of detectable bacterial genera (the average relative abundance of the genus >0.1%, and presented in at least half of the animals) in different regions (cecum, colon and rectum) of hindgut. Taxonomic composition of the hindgut mucosa-attached microbiota and shifts during pre-weaning In total, 16 phyla were identified from mucosa-attached communities of the hindgut (Dataset S2a, Supporting Information) and seven were considered as detected phyla (Table S3a, Supporting Information) in the hindgut of pre-weaned calves. The three predominant phyla in the hindgut mucosa-attached microbiota of pre-weaned calves were Bacteroidetes (35.96 ± 1.48%), Firmicutes (42.24 ± 1.81%) and Proteobacteria (14.92 ± 2.08%) (Dataset S2a, Supporting Information). The relative abundance of Proteobacteria was higher at NB (33.85 ± 2.08%) and D7 (20.52 ± 2.08%) compared to that at D21 (2.41 ± 2.08%) and D42 (2.91 ± 2.08%) (P < 0.01). In contrast to Proteobacteria, Firmicutes increased significantly (P < 0.01) at D21 (55.49 ± 1.81%) and D42 (49.26 ± 1.81%) compared with NB (33.32 ± 1.81%) and D7 (30.89 ± 1.81%). Bacteroidetes had the lowest relative abundance at NB (28.34 ± 1.48%), and started to increase after D7. The relative abundance of Fusobacteria was numerically higher at D7 (8.95 ± 1.00%) compared to that of NB (1.87 ± 1.00%), D21 (3.09 ± 1.00%) and D42 (6.60 ± 1.00%) calves (Table S3a, Supporting Information). From 120 identified families (Dataset S2b, Supporting Information), 24 were considered as detected families (Table S3b, Supporting Information). Bacteroidaceae was the predominant family in the hindgut mucosa-attached microbiota, with the highest relative abundance at D7 (26.26 ± 1.43%) compared with NB (18.83 ± 1.43%), D21 (15.65 ± 1.43%) and D42 (9.75 ± 1.43%) (P < 0.01). Enterobacteriaceae had a higher relative abundance at NB (19.09 ± 1.04%) and D7 (13.73 ± 1.04%) calves than that at D21 (1.10 ± 1.04%) and D42 (1.22 ± 1.04%) calves (P < 0.01). The relative abundance of Lactobacillaceae had a similar changing pattern as that of Enterobacteriaceae, higher at NB (5.26 ± 0.08%) and D7 (7.73 ± 0.08%) than those at D21(0.25 ± 0.08%) and D42 (0.28 ± 0.08%) calves (P < 0.01). On the contrary, the relative abundance of Ruminococcaceae was lower at NB (13.66 ± 1.06%) and D7 (10.86 ± 1.06%) compared to that at D21(27.37 ± 1.06%) and D42 (19.63 ± 1.06%) (P < 0.01). Similarly, Lanchnospiraceae had lower relative abundance at NB (10.23 ± 0.89%) and D7 (9.00 ± 0.89%) in comparison to that at D21 (23.46 ± 0.89%) and D42 (18.15 ± 0.89%) (P < 0.01), respectively. In addition, the relative abundance of Burkholderiaceae was the highest at NB (6.23 ± 0.04%) compared with that at D7 (0.13 ± 0.04%), D21(0.04 ± 0.04%) and D42 (0.37 ± 0.04%) (P < 0.01) (Table S3b, Supporting Information). At genus level, 349 genera were identified from the mucosa-attached microbial community and 61 genera were considered as detectable. Genera Bacteroides, Prevotella 9, Blautia, Lachnoclostridium, Lachnospiraceae UCG-004, Roseburia, Tuzzerella 4, Ruminococcus 2, Fusobacterium and Escherichia-Shigella were present in all the animals (Dataset S2c and Table S3c, Supporting Information). The relative abundance of Lactobacillus was higher at NB (5.26 ± 0.08%) and D7 (7.73 ± 0.08%) than that at D21 (0.25 ± 0.08%) and D42 (0.28 ± 0.08%) (P < 0.01) calves. The relative abundance of Escherichia-Shigella was higher in NB (13.52 ± 0.72%) and D7 (9.69 ± 0.72%) calves than in D21 (0.74 ± 0.72%) and D42 (0.92 ± 0.72%) (P < 0.01) calves. Similarly, Salmonella was higher at NB (2.64 ± 0.09%) and D7 (1.81 ± 0.09%) compared with D21 (0.16 ± 0.09%) and D42 (0.16 ± 0.09%) (P < 0.01). Faecalibacterium, Lachnospiraceae NC2004 group, Ruminococcaceae UCG-014 and Blautia had highest relative abundance at D21, comparing with other age groups (Table 2). Table 2. Mucosa-attached carbohydrate-utilizing and intestinal health-related bacterial genera.     Age      Phylum  Genus  NB  D7  D21  D42  SEM  P-value  Bacteroidetes  Bacteroides  18.83a  26.26b  15.65a  9.75c  1.43  <0.01  Firmicutes  Lactobacillus  5.26a  7.73a  0.25b  0.28b  0.08  <0.01    Anaerostipes  0.09ab  0.03a  0.13b  0.18b  0.02  <0.01    Blautia  2.66a  1.31a  10.55b  6.00c  0.51  <0.01    Coprococcus 1  0.05a  0.08a  0.50b  0.22c  0.03  <0.01    Coprococcus 3  0.00a  0.01a  0.04a  0.31b  0.00  <0.01    Lachnoclostridium  2.76a  2.32a  2.36a  1.65b  0.14  <0.01    Lachnospiraceae NC2004 group  0.04a  0.04a  0.19b  0.12c  0.01  <0.01    Lachnospiraceae ND3007 group  0.02a  0.00a  0.02a  0.15b  0.00  <0.01    Lachnospiraceae NK4A136 group  0.13a  0.08a  0.64b  1.09c  0.08  <0.01    Lachnospiraceae UCG-004  0.59  0.66  0.72  0.54  0.05  0.12    Lachnospiraceae UCG-008  0.19a  0.17a  0.65b  0.68b  0.06  <0.01    Pseudobutyrivibrio  0.13a  0.07a  0.57b  0.43c  0.03  <0.01    Roseburia  0.98a  0.68a  1.82b  2.23b  0.19  <0.01    Faecalibacterium  6.01a  4.54a  14.56b  7.68a  0.83  <0.01    Ruminiclostridium 5  0.04a  0.01a  0.18b  0.15b  0.01  <0.01    Ruminiclostridium 6  0.03a  0.01a  0.41b  0.44b  0.01  <0.01    Ruminiclostridium 9  0.00a  0.00a  0.11b  0.10b  0.00  <0.01    Ruminococcaceae UCG-002  0.03a  0.03a  0.14b  0.11b  0.01  <0.01    Ruminococcaceae UCG-005  0.49a  0.06b  4.31c  4.95c  0.06  <0.01    Ruminococcaceae UCG-010  0.02a  0.05a  0.10a  0.21b  0.02  <0.01    Ruminococcaceae UCG-014  0.40a  0.31a  1.59b  0.85c  0.11  <0.01    Ruminococcus 1  0.18a  0.19a  0.57b  1.00c  0.08  <0.01    Ruminococcus 2  4.61a  2.89b  1.53c  0.74c  0.27  <0.01    Erysipelatoclostridium  0.34a  0.48a  0.03b  0.04b  0.03  <0.01    Erysipelotrichaceae UCG-003  0.39a  0.07b  0.98c  0.49a  0.06  <0.01    Megasphaera  0.75a  0.47a  0.17b  0.08b  0.06  <0.01  Proteobacteria  Escherichia-Shigella  13.52a  9.69b  0.74c  0.92c  0.72  <0.01    Salmonella  2.64a  1.81b  0.16c  0.10c  0.09  <0.01      Age      Phylum  Genus  NB  D7  D21  D42  SEM  P-value  Bacteroidetes  Bacteroides  18.83a  26.26b  15.65a  9.75c  1.43  <0.01  Firmicutes  Lactobacillus  5.26a  7.73a  0.25b  0.28b  0.08  <0.01    Anaerostipes  0.09ab  0.03a  0.13b  0.18b  0.02  <0.01    Blautia  2.66a  1.31a  10.55b  6.00c  0.51  <0.01    Coprococcus 1  0.05a  0.08a  0.50b  0.22c  0.03  <0.01    Coprococcus 3  0.00a  0.01a  0.04a  0.31b  0.00  <0.01    Lachnoclostridium  2.76a  2.32a  2.36a  1.65b  0.14  <0.01    Lachnospiraceae NC2004 group  0.04a  0.04a  0.19b  0.12c  0.01  <0.01    Lachnospiraceae ND3007 group  0.02a  0.00a  0.02a  0.15b  0.00  <0.01    Lachnospiraceae NK4A136 group  0.13a  0.08a  0.64b  1.09c  0.08  <0.01    Lachnospiraceae UCG-004  0.59  0.66  0.72  0.54  0.05  0.12    Lachnospiraceae UCG-008  0.19a  0.17a  0.65b  0.68b  0.06  <0.01    Pseudobutyrivibrio  0.13a  0.07a  0.57b  0.43c  0.03  <0.01    Roseburia  0.98a  0.68a  1.82b  2.23b  0.19  <0.01    Faecalibacterium  6.01a  4.54a  14.56b  7.68a  0.83  <0.01    Ruminiclostridium 5  0.04a  0.01a  0.18b  0.15b  0.01  <0.01    Ruminiclostridium 6  0.03a  0.01a  0.41b  0.44b  0.01  <0.01    Ruminiclostridium 9  0.00a  0.00a  0.11b  0.10b  0.00  <0.01    Ruminococcaceae UCG-002  0.03a  0.03a  0.14b  0.11b  0.01  <0.01    Ruminococcaceae UCG-005  0.49a  0.06b  4.31c  4.95c  0.06  <0.01    Ruminococcaceae UCG-010  0.02a  0.05a  0.10a  0.21b  0.02  <0.01    Ruminococcaceae UCG-014  0.40a  0.31a  1.59b  0.85c  0.11  <0.01    Ruminococcus 1  0.18a  0.19a  0.57b  1.00c  0.08  <0.01    Ruminococcus 2  4.61a  2.89b  1.53c  0.74c  0.27  <0.01    Erysipelatoclostridium  0.34a  0.48a  0.03b  0.04b  0.03  <0.01    Erysipelotrichaceae UCG-003  0.39a  0.07b  0.98c  0.49a  0.06  <0.01    Megasphaera  0.75a  0.47a  0.17b  0.08b  0.06  <0.01  Proteobacteria  Escherichia-Shigella  13.52a  9.69b  0.74c  0.92c  0.72  <0.01    Salmonella  2.64a  1.81b  0.16c  0.10c  0.09  <0.01  a,b,c means with different superscripts are significantly different among age groups at P < 0.01. Values represents mean of three hindgut regions. View Large Taxonomic composition of the hindgut digesta-associated microbiota and shifts during pre-weaning period In total, 15 phyla were identified from digesta-associated microbiota (Dataset S2d, Supporting Information), with six of them being detected (Table S3d, Supporting Information). Regardless of the hindgut region, Firmicutes was the most predominant phylum detected in digesta-associated microbial community of all ages (D7—61.76 ± 1.55%; D21—73.75 ± 1.55%; D42—73.90 ± 1.55%) (P = 0.01). Bacteroidetes was the second most abundant phylum in all the age groups (D7—20.81 ± 0.89%, D21—20.94 ± 0.89%, D42—21.36 ± 0.89%). Proteobacteria was the third predominant phylum in digesta-associated microbiota community, and the relative abundance was 7.37% (± 0.66%) at D7, 1.92% (± 0.66%) at D21 and 2.05% (± 0.66%) at D42 (P < 0.01), respectively (Table S3d, Supporting Information). At family level, 83 families were identified (Dataset S2e, Supporting Information) and 20 of them were considered as detected. Digesta-associated Lactobacillaceae was the predominant family (22.36 ± 0.90% at D7; 20.01 ± 1.37% at D21; 21.01 ± 1.37% at D42) (P = 0.90). In addition, Lachnospiraceae, Bacteroidaceae and Ruminococcaceae were also the predominant families. Among all the detected families, the relative abundances of Bacteroidaceae (9.28 ± 0.59% at D7; 4.64 ± 0.59% at D21; 4.51 ± 0.59% at D42) (P < 0.01), Enterobacteriaceae (4.99 ± 0.45% at D7; 1.35 ± 0.45% at D21; 1.39 ± 0.45% at D42) (P < 0.01) and Bifidobacteriaceae (1.06 ± 0.14% at D7; 0.18 ± 0.14% at D21; 0.15 ± 0.14% at D42) (P = 0.06) were higher at D7 compared with D21 and D42. On the other hand, the relative abundances of Lachnospiraceae (17.46 ± 1.03% at D7; 25.07 ± 1.03% at D21; 23.85 ± 1.03% at D42) (P < 0.01) and Ruminococcaceae (15.59 ± 0.84% at D7; 20.10 ± 0.84% at D21; 19.67 ± 0.84% at D42) (P = 0.03) were higher at D21 and D42 compared with those at D7 (Table S3e, Supporting Information). At genus level, 50 genera were considered as detected out of the 249 identified genera. Genera Collinsella, Blautia, Lachnoclostridium, Lachnospiraceae UCG-004, Lachnospiraceae UCG-008, Roseburia, Tyzzerella 4, Intestinibacter, Faecalibacterium, Subdoligranulum and Erysipelotrichaceae UCG-003 were present in all samples (Dataset S2f and Table S3f, Supporting Information) with Lactobacillus (22.36 ± 1.37% at D7; 20.01 ± 1.37% at D21; 21.01 ± 1.37% at D42) (P = 0.90) being the most abundant genus. In addition, the relative abundances of Bacteroides (9.28 ± 0.59% at D7; 4.64 ± 0.59% at D21; 4.51 ± 0.59% at D42) (P < 0.01), Megasphaera (2.72 ± 0.24% at D7; 0.32 ± 0.24% at D21; 0.26 ± 0.24% at D42) (P < 0.01), Escherichia-Shigella (3.67 ± 0.33% at D7; 0.98 ± 0.33% at D21; 0.98 ± 0.33% at D42) (P < 0.01) and Salmonella (0.51 ± 0.05% at D7; 0.13 ± 0.05% at D21; 0.12 ± 0.05% at D42) (P = 0.03) were highest at D7. Moreover, the relative abundances of Blautia (5.50 ± 0.80% for D7, 13.42 ± 0.80% for D21, 11.87 ± 0.80% for D42) (P < 0.01), Coprococcus 1 (0.06 ± 0.02% for D7, 0.18 ± 0.02% for D21, 0.13 ± 0.02% for D42) (P < 0.01), Lachnospiraceae NK4A136 group (0.14 ± 0.03% for D7, 0.34 ± 0.03% for D21, 0.29 ± 0.03% for D42) (P < 0.01), Lachnospiraceae UCG-008 (0.55 ± 0.04% for D7, 0.71 ± 0.04% for D21, 0.81 ± 0.04% for D42) (P < 0.01), Pseudobutyrivibrio (0.29 ± 0.05% for D7, 0.73 ± 0.05% for D21, 0.65 ± 0.05% for D42) (P < 0.01), Ruminiclostridium 5 (0.07 ± 0.02% for D7, 0.21 ± 0.02% for D21, 0.18 ± 0.02% for D42) (P < 0.01), Ruminiclostridium 6 (0.13 ± 0.06% for D7, 0.36 ± 0.06% for D21, 0.33 ± 0.06% for D42) (P < 0.01) and Ruminococcus 1(0.14 ± 0.02% for D7, 0.22 ± 0.02% for D21, 0.27 ± 0.02% for D42) (P < 0.01) (P = 0.01) were higher at D21 and D42 than those at D7 (Table 3). Table 3. Digesta-associated carbohydrate-utilizing and intestinal health-related bacterial genera.     Age      Phylum  Genus  D7  D21  D42  SEM  P-value  Actinobacteria  Bifidobacterium  1.06a  0.17b  0.14b  0.14  0.04  Bacteroidetes  Bacteroides  9.28a  4.64b  4.51b  0.59  <0.01  Firmicutes  Lactobacillus  22.36  20.01  21.01  1.37  0.90    Anaerostipes  0.12  0.14  0.14  0.01  0.38    Blautia  5.50a  13.42b  11.87b  0.80  <0.01    Coprococcus 1  0.06a  0.18b  0.13b  0.02  <0.01    Lachnoclostridium  3.62  3.18  3.11  0.19  0.73    Lachnospiraceae NC2004 group  0.15  0.19  0.16  0.02  0.41    Lachnospiraceae NK4A136 group  0.14a  0.34b  0.29b  0.03  <0.01    Lachnospiraceae UCG-004  0.53  0.51  0.53  0.05  0.39    Lachnospiraceae UCG-008  0.55a  0.71ab  0.81b  0.04  <0.01    Pseudobutyrivibrio  0.29a  0.73b  0.65b  0.05  <0.01    Roseburia  1.45  0.83  1.08  0.13  0.31    Faecalibacterium  5.97  3.79  3.53  0.47  0.46    Ruminiclostridium 5  0.07a  0.21b  0.18b  0.02  <0.01    Ruminiclostridium 6  0.13a  0.36b  0.33b  0.06  <0.01    Ruminococcaceae NK4A214 group  0.14  0.08  0.14  0.01  0.06    Ruminococcaceae UCG-005  1.16a  4.76ab  6.66b  0.79  <0.01    Ruminococcaceae UCG-010  0.13  0.12  0.10  0.02  0.26    Ruminococcaceae UCG-014  1.14a  4.30b  2.69ab  0.53  <0.01    Ruminococcus 1  0.14a  0.22b  0.27b  0.02  0.01    Ruminococcus 2  1.52  1.21  0.80  0.15  0.44    Erysipelatoclostridium  0.44a  0.17b  0.13b  0.06  0.02    Erysipelotrichaceae UCG-003  0.46a  2.23b  1.48ab  0.24  <0.01    Megasphaera  2.72a  0.32b  0.26b  0.24  <0.01  Proteobacteria  Escherichia-Shigella  3.67a  0.98b  0.98b  0.33  <0.01    Salmonella  0.51a  0.13b  0.12b  0.05  0.03      Age      Phylum  Genus  D7  D21  D42  SEM  P-value  Actinobacteria  Bifidobacterium  1.06a  0.17b  0.14b  0.14  0.04  Bacteroidetes  Bacteroides  9.28a  4.64b  4.51b  0.59  <0.01  Firmicutes  Lactobacillus  22.36  20.01  21.01  1.37  0.90    Anaerostipes  0.12  0.14  0.14  0.01  0.38    Blautia  5.50a  13.42b  11.87b  0.80  <0.01    Coprococcus 1  0.06a  0.18b  0.13b  0.02  <0.01    Lachnoclostridium  3.62  3.18  3.11  0.19  0.73    Lachnospiraceae NC2004 group  0.15  0.19  0.16  0.02  0.41    Lachnospiraceae NK4A136 group  0.14a  0.34b  0.29b  0.03  <0.01    Lachnospiraceae UCG-004  0.53  0.51  0.53  0.05  0.39    Lachnospiraceae UCG-008  0.55a  0.71ab  0.81b  0.04  <0.01    Pseudobutyrivibrio  0.29a  0.73b  0.65b  0.05  <0.01    Roseburia  1.45  0.83  1.08  0.13  0.31    Faecalibacterium  5.97  3.79  3.53  0.47  0.46    Ruminiclostridium 5  0.07a  0.21b  0.18b  0.02  <0.01    Ruminiclostridium 6  0.13a  0.36b  0.33b  0.06  <0.01    Ruminococcaceae NK4A214 group  0.14  0.08  0.14  0.01  0.06    Ruminococcaceae UCG-005  1.16a  4.76ab  6.66b  0.79  <0.01    Ruminococcaceae UCG-010  0.13  0.12  0.10  0.02  0.26    Ruminococcaceae UCG-014  1.14a  4.30b  2.69ab  0.53  <0.01    Ruminococcus 1  0.14a  0.22b  0.27b  0.02  0.01    Ruminococcus 2  1.52  1.21  0.80  0.15  0.44    Erysipelatoclostridium  0.44a  0.17b  0.13b  0.06  0.02    Erysipelotrichaceae UCG-003  0.46a  2.23b  1.48ab  0.24  <0.01    Megasphaera  2.72a  0.32b  0.26b  0.24  <0.01  Proteobacteria  Escherichia-Shigella  3.67a  0.98b  0.98b  0.33  <0.01    Salmonella  0.51a  0.13b  0.12b  0.05  0.03  a,b,c means with different superscripts are significantly different among age groups at P < 0.05. Values represents mean of three hindgut regions. View Large Comparison between mucosa- and digesta-associated bacterial communities Among all the bacterial genera detected in the hindgut, 45 of them were present in both mucosa- and digesta-associated communities. Among the common bacterial genera, 30 genera were significantly different between two communities. Bacterial genera that were highly abundant in mucosa-attached community included Bacteroides, Parabacteroides, Alloprevotella, Prevotella 9, Faecalibacterium, Ruminococcus 2, Fusobacterium, Salmonella and Escherichia-Shigella, while bacterial genera Atopobium, Collinsella, Coriobacteriaceae UCG-002, Alistipes, Lactobacillus, Christensenellaceae R-7 group, Blautia, Dorea, Lachnoclostridium, Lachnospiraceae NC2004 group, Lachnospiraceae UCG-008, Pseudobutyrivibrio, Intestinibacter, Peptoclostridium, Romboutsia, Ruminiclostridium 5, Ruminococcaceae UCG-005, Ruminococcaceae UCG-014, Subdoligranulum, Erysipelotrichaceae UCG-003 and Megasphaera were highly abundant in the digesta-associated community (Table S4, Supporting Information). In addition, Rhodococcus, Moryella, Bifidobacterium, Ruminococcaceae NK4A214 group and Akkermansia were only detected in the digesta-associated microbiota, while Acidaminococcus, Sutterella, Phascolarctobacterium, Ruminiclostridium 9, Streptococcus, Lachnospiraceae ND3007 group, Pseudomonas, Ruminococcaceae UCG-002, Pantoea, Coprococcus 3, Anaerovibrio, Odoribacter, Edaphobacter, Citrobacter, Burkholderia and Prevotella 7 were only identified in mucosa-attached microbiota community (Table S4, Supporting Information). Estimation of bacterial densities in the hindgut of pre-weaned calves Estimation of selected bacteria using qPCR showed a significant age effect on the proportion of mucosa-attached E. coli, Bifidobacterium, Clostridium cluster XIVa and F. prausnitzii (Table 4). The proportion of Bifidobacterium was the highest at D7 (59.90 ± 4.33%) compared to that of other age groups regardless of the hindgut region. Escherichia coli had the highest proportion at D7 (3.57 ± 0.42%) following lower abundance at D21 (1.30 ± 0.37%) and D42 (0.75 ± 0.36%) with no difference observed between D21 and D42. The proportion of Clostridium cluster XIVa was the highest at D21 (15.83 ± 1.28%) compared to all other age groups. In the digesta-associated community, the effect of age was noted on the proportion of E. coli and Clostridium cluster XIVa (Table 4). Similar to mucosa-attached bacteria, the proportion of E. coli was the highest at D7 (0.07 ± 0.01%), while the proportion of Clostridium cluster XIVa was higher at D21 (2.90 ± 0.32%) and D42 compared with that at D7 (2.75 ± 0.29%). Table 4. Quantification of five bacterial groups in the hindgut during pre-weaned period.     Age  Hindgut region  P-value    Bacterial groups  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  Total bacteria  2.43 × 109  1.21 × 1010  1.58 × 1010  5.49 × 1010  1.93 × 109  1.10 × 1010  4.47 × 1010  8.30 × 109  1.67 × 109  0.24  0.24  attached  Escherichia colix  2.02a  3.57b  1.30ac  0.75c  0.42  2.11  1.70  1.92  0.37  <0.01  0.73  bacteria  Bifidobacteriumx  36.29a  59.90b  35.16a  10.62c  4.33  40.00  32.80  33.69  3.75  <0.01  0.34    Clostridium cluster XIVax  0.92a  4.28ab  15.83c  9.36d  1.28  7.42  6.38  8.99  1.11  <0.01  0.25    Faecalibacterium prausnitziix  0.41a  1.09ab  1.76b  0.93a  0.24  1.12  0.76  1.25  0.21  <0.01  0.23  Digesta-  Total bacteria  NA  2.02 × 1013  1.21 × 1013  1.91 × 1013  5.51 × 1012  1.31 × 1013  1.53 × 1013  2.31 × 1013  5.51 × 1012  0.53  0.39  associated  Escherichia colix  NA  0.07a  0.02b  0.01b  0.01  0.04  0.02  0.03  0.01  0.02  0.69  bacteria  Bifidobacteriumx  NA  1.51  1.85  2.51  0.33  2.20  1.88  1.79  0.32  0.08  0.62    Clostridium cluster XIVax  NA  1.64a  2.90b  2.75b  0.35  2.67  2.16  2.47  0.35  0.02  0.56    Faecalibacterium prausnitziix  NA  0.11  0.06  0.06  0.05  0.08  0.09  0.07  0.67  0.07  0.80      Age  Hindgut region  P-value    Bacterial groups  NB  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Mucosa-  Total bacteria  2.43 × 109  1.21 × 1010  1.58 × 1010  5.49 × 1010  1.93 × 109  1.10 × 1010  4.47 × 1010  8.30 × 109  1.67 × 109  0.24  0.24  attached  Escherichia colix  2.02a  3.57b  1.30ac  0.75c  0.42  2.11  1.70  1.92  0.37  <0.01  0.73  bacteria  Bifidobacteriumx  36.29a  59.90b  35.16a  10.62c  4.33  40.00  32.80  33.69  3.75  <0.01  0.34    Clostridium cluster XIVax  0.92a  4.28ab  15.83c  9.36d  1.28  7.42  6.38  8.99  1.11  <0.01  0.25    Faecalibacterium prausnitziix  0.41a  1.09ab  1.76b  0.93a  0.24  1.12  0.76  1.25  0.21  <0.01  0.23  Digesta-  Total bacteria  NA  2.02 × 1013  1.21 × 1013  1.91 × 1013  5.51 × 1012  1.31 × 1013  1.53 × 1013  2.31 × 1013  5.51 × 1012  0.53  0.39  associated  Escherichia colix  NA  0.07a  0.02b  0.01b  0.01  0.04  0.02  0.03  0.01  0.02  0.69  bacteria  Bifidobacteriumx  NA  1.51  1.85  2.51  0.33  2.20  1.88  1.79  0.32  0.08  0.62    Clostridium cluster XIVax  NA  1.64a  2.90b  2.75b  0.35  2.67  2.16  2.47  0.35  0.02  0.56    Faecalibacterium prausnitziix  NA  0.11  0.06  0.06  0.05  0.08  0.09  0.07  0.67  0.07  0.80  NA—not applicable x means bacterial groups were expressed as ratio, ratio = (16S rRNA gene copy number of each bacterial groups/total bacterial 16S rRNA gene copy number) ×100. a,b,c means with different superscripts are significantly different at P < 0.05. View Large Predicted function of the hindgut microbiota in pre-weaned calves using Tax4Fun Tax4Fun-based functional prediction revealed top 10 microbial functions of the mucosa- and digesta-associated hindgut communities. These functions include ‘metabolism of cofactors and vitamins’, ‘energy metabolism’, ‘carbohydrate metabolism’, ‘amino acid metabolism’, ‘translation’, ‘replication and repair’, ‘nucleotide metabolism’, ‘signal transduction’, ‘metabolism of other amino acids’ and ‘membrane transport’ (Fig. 4a and b). In the mucosa-attached bacterial community, functions related to ‘nucleotide metabolism’, ‘translation’, ‘replication and repair’ and ‘amino acid metabolism’ were higher at D21 and D42 compared with those at NB and D7. On the other hand, ‘signal transduction’ and ‘carbohydrate metabolism’ were higher at NB and D7 compared to D21 and D42 (Fig. 4a). In the digesta-associated bacteria, the functions of ‘replication and repair’, ‘signal transduction’, ‘translation’, ‘metabolism of other amino acids’ were higher at D21 and D42 in comparison to D7. However, ‘energy metabolism’, ‘metabolism of cofactors and vitamins’ and ‘carbohydrate metabolism’ were higher at D7 when compared to D21 and D42 (Fig. 4b). Figure 4. View largeDownload slide Predicted microbial functions using Tax4fun. (a) Comparisons of the top 10 predicted microbial predominant gene pathways for mucosa-attached bacterial community among different age groups in the hindgut. (b) Comparisons of the 10 predicted microbial predominant gene pathways for digesta-associated bacterial community among different age groups in the hindgut. Star means significant difference among different age groups. Figure 4. View largeDownload slide Predicted microbial functions using Tax4fun. (a) Comparisons of the top 10 predicted microbial predominant gene pathways for mucosa-attached bacterial community among different age groups in the hindgut. (b) Comparisons of the 10 predicted microbial predominant gene pathways for digesta-associated bacterial community among different age groups in the hindgut. Star means significant difference among different age groups. Microbial SCFA detected in the hindgut of pre-weaned dairy calves Concentrations of total SCFA, acetate, propionate, butyrate, isobutyrate and isovalerate were significantly different depending on the calf age (Table 5). Concentration of acetate, butyrate and total SCFA increased from D7 onwards, with the highest concentration at D21 regardless of gut region. Propionate and isobutyrate concentration were significantly higher at D21 and D42 compared to those at D7 (Table 5). In addition, concentrations of butyrate, isobutyrate, isovalerate and valerate were significantly different among the hindgut regions, with the highest concentration detected in the rectum. Moreover, the molar proportion of acetate, propionate, butyrate, isobutyrate, isovalerate and valerate was also significantly different among the hindgut regions regardless of calf age. Table 5. SCFA concentration (μmol/g) and molar proportion in the hindgut of pre-weaned dairy calves.   Age  Region  P-value  SCFA  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Acetate  18.22a  56.71b  44.39c  4.18  40.13  40.58  38.62  4.05  <0.01  0.93  Propionate  5.47a  13.87b  12.47b  1.31  9.33  9.72  12.77  1.26  <0.01  0.09  Butyrate  3.45a  8.46b  5.95c  0.92  5.00x  5.01x  7.84y  0.89  <0.01  0.03  Isobutyrate  0.30a  1.12b  0.82b  0.15  0.51x  0.45x  1.27y  0.15  <0.01  <0.01  Isovalerate  0.71a  1.67ab  0.88b  0.27  0.67x  0.69x  1.89y  0.26  0.02  <0.01  Valerate  0.42  0.94  1.06  0.21  0.61x  0.58x  1.23y  0.20  0.06  0.03  Total SCFA  28.57a  82.77b  65.57c  6.25  56.25  57.03  63.62  6.08  <0.01  0.59  Acetate  0.67  0.69  0.67  0.02  0.70x  0.70x  0.61y  0.02  0.81  <0.01  Propionate  0.17  0.17  0.19  0.01  0.17x  0.17x  0.20y  0.01  0.77  0.03  Butyrate  0.10  0.10  0.09  0.01  0.09x  0.08xy  0.11y  0.01  0.62  0.01  Isobutyrate  0.01  0.01  0.01  0.00  0.01x  0.01x  0.02y  0.00  0.22  <0.01  Isovalerate  0.03a  0.02b  0.01c  0.00  0.02x  0.01y  0.03z  0.00  0.03  0.01  Valerate  0.01  0.01  0.02  0.00  0.01x  0.01x  0.02y  0.00  0.08  0.02    Age  Region  P-value  SCFA  D7  D21  D42  SEM  Cecum  Colon  Rectum  SEM  Age  Region  Acetate  18.22a  56.71b  44.39c  4.18  40.13  40.58  38.62  4.05  <0.01  0.93  Propionate  5.47a  13.87b  12.47b  1.31  9.33  9.72  12.77  1.26  <0.01  0.09  Butyrate  3.45a  8.46b  5.95c  0.92  5.00x  5.01x  7.84y  0.89  <0.01  0.03  Isobutyrate  0.30a  1.12b  0.82b  0.15  0.51x  0.45x  1.27y  0.15  <0.01  <0.01  Isovalerate  0.71a  1.67ab  0.88b  0.27  0.67x  0.69x  1.89y  0.26  0.02  <0.01  Valerate  0.42  0.94  1.06  0.21  0.61x  0.58x  1.23y  0.20  0.06  0.03  Total SCFA  28.57a  82.77b  65.57c  6.25  56.25  57.03  63.62  6.08  <0.01  0.59  Acetate  0.67  0.69  0.67  0.02  0.70x  0.70x  0.61y  0.02  0.81  <0.01  Propionate  0.17  0.17  0.19  0.01  0.17x  0.17x  0.20y  0.01  0.77  0.03  Butyrate  0.10  0.10  0.09  0.01  0.09x  0.08xy  0.11y  0.01  0.62  0.01  Isobutyrate  0.01  0.01  0.01  0.00  0.01x  0.01x  0.02y  0.00  0.22  <0.01  Isovalerate  0.03a  0.02b  0.01c  0.00  0.02x  0.01y  0.03z  0.00  0.03  0.01  Valerate  0.01  0.01  0.02  0.00  0.01x  0.01x  0.02y  0.00  0.08  0.02  a,b,c means with different superscripts are significantly different among age groups at P < 0.05. x,y means with different superscripts are significantly different among regions at P < 0.05. View Large Relationship between bacteria and fermentation parameters To explore the potential roles of bacteria in the hindgut fermentation, the relationship between SCFA (acetate, propionate, butyrate and total SCFA) concentrations and the relative abundance of mucosa-, digesta-associated bacterial genera was explored using Spearman's rank correlations. Acetate concentration was positively correlated with the relative abundance of carbohydrate-utilizing bacteria, including Anaerostipes (ρ = 0.59, P < 0.01), Blautia (ρ = 0.68, P < 0.01), Coprococcus 1 (ρ = 0.67, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.56, P < 0.01), Pseudobutyrivibrio (ρ = 0.63, P < 0.01), Ruminiclostridium 5 (ρ = 0.68, P < 0.01), Ruminiclostridium 6 (ρ = 0.72, P < 0.01) and Ruminiclostridium 9 (ρ = 0.55, P < 0.01). In addition, propionate concentration was positively correlated with the relative abundance of mucosa-attached Coprococcus 1 (ρ = 0.56, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.54, P < 0.01), Ruminiclostridium 6 (ρ = 0.50, P < 0.01). Moreover, butyrate concentration was positively correlated with mucosa-attached Coprococcus 1 (ρ = 0.54, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.63, P < 0.01), Faecalibacterium (ρ = 0.63, P < 0.01) and Ruminiclostridium 5 (ρ = 0.54, P < 0.01). Furthermore, total SCFA concentration was positively correlated with the relative abundance of mucosa-attached Anaerostipes (ρ = 0.53, P < 0.01), Blautia (ρ = 0.61, P < 0.01), Coprococcus 1 (ρ = 0.61, P < 0.01), Lachnospiraceae NC2004 group (ρ = 0.57, P < 0.01), Pseudobutyrivibrio (ρ = 0.56, P < 0.01), Ruminiclostridium 5 (ρ = 0.62, P < 0.01), Ruminiclostridium 6 (ρ = 0.63, P < 0.01) and Ruminiclostridium 9 (ρ = 0.50, P < 0.01). Additionally, acetate was negatively correlated with the relative abundance of Escherichia-Shigella (ρ = –0.57, P < 0.01) and Salmonella (ρ = −0.53, P < 0.01). Moreover, we identified negative correlations between mucosa-attached Bifidobacterium with acetate (ρ = –0.50, P < 0.01) and propionate (ρ = –0.57, P < 0.01) and positive correlations between mucosa-attached Clostridium cluster XIVa with acetate (ρ = 0.52, P < 0.01) and total SCFA (ρ = 0.50, P < 0.01) (Fig. 5). Figure 5. View largeDownload slide Relationship between mucosa-attached bacteria and SCFA concentration. Significant correlations were found between SCFA concentrations and the relative abundance of mucosa-attached Coriobacteriaceae UCG-002, Prevotella 9, Rikenellaceae RC9 gut group, Anaerostipes, Blautia, Coprococcus 1, Lachnospiraceae NC2004 group, Pseudobutyrivibrio, Faecalibacterium, Ruminiclostridium 5, Ruminiclostridium 6, Ruminiclostridium 9, Ruminococcaceae UCG-005 and Erysipelotrichaceae UCG-003 and the density of mucosa-attached Bifidobacterium, Clostridium cluster XIVa and total bacteria by Spearman's rank correlation. Figure 5. View largeDownload slide Relationship between mucosa-attached bacteria and SCFA concentration. Significant correlations were found between SCFA concentrations and the relative abundance of mucosa-attached Coriobacteriaceae UCG-002, Prevotella 9, Rikenellaceae RC9 gut group, Anaerostipes, Blautia, Coprococcus 1, Lachnospiraceae NC2004 group, Pseudobutyrivibrio, Faecalibacterium, Ruminiclostridium 5, Ruminiclostridium 6, Ruminiclostridium 9, Ruminococcaceae UCG-005 and Erysipelotrichaceae UCG-003 and the density of mucosa-attached Bifidobacterium, Clostridium cluster XIVa and total bacteria by Spearman's rank correlation. DISCUSSION During early life of ruminants, milk bypasses the undeveloped rumen, nutrients are digested and absorbed in the lower GIT, and the non-digestible dietary substrates are fermented in the hindgut. Therefore, the microbial colonization in the hindgut of dairy calves during the pre-weaned period plays an important role in nutrient and energy harvest. The profiling of the microbiota revealed the colonization of a diverse and dense microbial population at both mucosal surface and in the lumen of hindgut starting from the calves was born. This study is the first to report the presence of highly diverse microbiota in the hindgut of NB calves within 30 min after birth without any feeding (colostrum consumption). This suggests that the hindgut microbiota begin to colonize possibly during the birth process. The transmission process of maternal microbiota to NB calves may be similar to the findings reported for human NB infant gut microbiota, which could originate from amniotic fluid (DiGiulio 2012), meconium (Moles et al.2013) and fetal membranes (van den Berg 2006). The significant individual variation among the NB calves (Fig. S2, Supporting Information) may be due to the variations in the transmission process from the cow and birth environment (uterus, vaginal canal and fetal membranes). The predominant identified families including Bacteroidaceae, Lanchnospiraceae, Lactobacillaceae and Enterobacteriaceae in the hindgut of NB calves resembled the dominant families in 1-day-old piglets (Frese et al.2015). In addition, the presence of Lactobacillus as a predominant genus and higher relative abundance of facultative anaerobic Enterobacteriaceae family at birth and D7 is similar to fecal microbiota of vaginally delivered babies (Matamoros et al.2013) and in the human infants’ gut during early life (Arrieta et al.2014). The roles of facultative anaerobes, such as Enterobacteriaceae spp., are to create the anaerobic environment by utilizing available oxygen during the immediate neonatal period for the establishment of obligate anaerobes (Favier et al.2002). In addition, family Enterobacteriaceae also contains many potential pathogenic bacteria belong to genera Escherichia (Moxley and Francsis 1986) and Salmonella (Zhang et al.2003). The observed high abundance of mucosa-attached Escherichia-Shigella and Salmonella during the first week suggests that the calves are more susceptible to infections due to the greater abundance of opportunistic pathogens during this period. On the other hand, the higher abundance of the mucosa-attached Ruminococcus at D21 compared with D7 was observed. A recent study has reported that Ruminococcus gnavus E1 can modulate the expression of mucins-related gene and increase mucin production (Graziani et al.2016), suggesting that species belong to Ruminococcus may play a role in increasing host resistance to pathogenic bacterial invasion through reinforced barrier functions at D21. Moreover, the observed high relative abundance of obligate anaerobic Bacteroides in the hindgut of NB calf could be due to the availability of substrates after birth, such as mucus glycans. It has been reported that Bacteroides spp. including Bacteroides thetaiotaomicron and Bacteroides fragilis could utilize host mucus glycans (Marcobal et al.2011). Based on these findings, it suggests that the hindgut mucosa-associated microbiota of pre-weaned claves has similar microbial composition to that of the monogastric animals, with the capability to adapt to the anaerobic environment and potentially utilize the available substrates to define their colonization niches. Similar to adult cattle, the Firmicutes, Bacteroidetes and Proteobacteria dominated the digesta-associated hindgut microbiota of pre-weaned calves. The relative abundance of these three dominant phyla is in agreement with the reported main phyla in the fecal microbiota within the first 7 weeks of life in dairy calves (Oikonomou et al.2013). This suggests that the microbial composition in the fecal sample is representative of the digesta-associated microbiota in the hindgut. However, Bacteroidetes was dominated in the mucosa-attached community of 3-week-old calves (Malmuthuge et al.2014), whereas Firmicutes was found to be the predominant and Bacteroidetes was the second most abundant phylum in the hindgut of D21 calves in our study. Such discrepancy may be due to the use of different animals, different farm and management environments, diets and the different primers used to amplify 16S rRNA gene. The segregation of mucosa- and digesta-associated bacterial profiles confirmed the previous findings in mouse (Swidsinski et al.2005), pre-weaned dairy calves (Malmuthuge et al.2012; Malmuthuge et al.2014) and dairy cows (Mao et al.2015; Liu et al.2016). Previous findings have revealed that mucosa-attached microbiota is more diverse but has a lower microbial density (Malmuthuge et al.2015; Mao et al.2015) when compared to digesta-associated microbiota in ruminants, suggesting that the compositional difference in these two microbial communities is a common biological phenomenon. We also observed a high individual variation (higher UniFrac dissimilarity) within the mucosa-attached microbiota than that of the digesta-associated community, suggesting such segregation of these communities occurs soon after birth and their ecological niches could be an essential factor that drives the divergence. Therefore, it is vital to study both communities to generate the full understanding of the gut microbiome and their roles in the hindgut during early life. In addition to different microbial communities between two sample types (mucosa and digesta), we also observed compositional changes among age groups. The mucosa-attached bacterial community was significantly affected by the age, which might be influenced by host physiological changes (e.g. development of host immune system, epithelial integrity and growth) as well as diet during the pre-weaned period. It is noticeable that the effect of age in this study is confounded with the dietary changes. The decrease of digesta-associated Bacteroides at D21 and D42 compared to D7, similar to the reported trend in the rumen of pre-weaned calves (Li et al.2012; Rey et al.2014), could be due to the increase of age and the increased consumption of calf starter. Similarly, higher relative abundance of digesta-associated carbohydrate-utilizing bacterial genera (Blautia, Ruminococcus, Coprococcus 1, Lachnospiraceae NK4A136 group, Pseudobutyrivibrio, Ruminiclostridium 5 and Ruminiclostridium 6) at D21 compared with D7 are also due to increased intake of starter from D14, which provides available carbohydrates to stimulate the colonization of those bacterial groups. It is known that genus Bifidobacterium is highly abundant in the infants’ gut (Turroni et al.2009; Fanaro et al.2003) and our previous study revealed that the proportion of Bifidobacterium was high in the small intestine during the first 12 h of life, especially when colostrum was fed within the first 12 h of life (Malmuthuge et al.2015). In this study, the abundance of mucosa-attached Bifidobacterium (detected by qPCR) was higher at D7 than the older calves (D21 and D42), indicating the consumption of milk that is rich in oligosaccharides (Sela et al.2008; Lozupone et al.2013) could lead to higher population of this genus. In addition, the Bifidobacterium has been reported to form biofilm, which plays an important role in the prevention of pathogen invasion and stimulate the host immune functions (Hidalgo-Cantabrana et al.2013). Moreover, the abundance of Bifidobacterium has been reported to be highly correlated with the expression of genes and microRNAs that regulate host immune function in the small intestine of the same calves (Liang et al.2014). Therefore, it is important to know how the diversity of mucosa-attached Bifidobacterium could be impact by the age and how this could influence the host functions. It is noticeable that although high copy numbers of Bifidobacterium 16S rRNA genes were detected in both mucosa and digesta-associated communities, the amplicon sequencing only detected the digesta-associated Bifidobacterium. The universal bacterial primers (such as 27F and 1492R used in this study) are usually fail to amplify this genus (Malmuthuge et al.2014) because the forward primer (27F) has a few mismatches with 16S rRNA gene sequence of Bifidobacterial genus (Frank et al.2008), which leads to a lower amplification of Bifidobacterial sequences, resulting in a lower relative abundance. Therefore, future studies are needed to characterize the Bifidobacterium in the hindgut of dairy calves using Bifidobacterium-specific primers. It has been demonstrated that mucosa-attached bacteria could affect host immune system development, metabolism and health (Moxley and Francis 1986; Ivanov et al.2009). A recent study also reported that SCFA can affect the intestinal cells turnover (Park et al.2016). We speculate that the shifts in SCFA could also impact on the mucosal-attached bacteria population in addition to their impact on host tissues since the measured SCFA concentration in the lumen is the result of microbial production and host tissue absorption. The observed significant correlation between SCFA concentration and the relative abundance of mucosa-attached bacteria suggests a potential cross-talk between lumen microbial metabolites and mucosa-attached microbiota. For example, the observed negative correlation between the mucosa-attached Escherichia-Shigella abundance and acetate concentration (ρ = –0.57, P < 0.01) in the study may support our above speculation. The decreased mucosa-attached Escherichia from D7 to D21 vs D42 may be caused by the increased acetate concentration in the gut after D7, as acetate has been reported to inhibit the growth of E. coli (Fukuda et al.2011). It was surprising that no significant correlation was found between the relative abundance of digesta-associated bacteria and SCFA concentration in this study, suggesting that future analysis using the quantitative approach is needed to verify the relationship between lumen microbes and SCFA and to verify whether the lumen SCFA is important in the potential cross-talk between microbes. The higher SCFA concentrations at D21 compared with D42 and D7 (including acetate, butyrate and total SCFA) in the hindgut indicate the stronger fermentation ability of hindgut microbiota at D21 compared with D7 and D42. This could be explained by the increased development of rumen from D21 to D42 with increased solid feed intake (Malmuthuge 2016), leading to less substance available to the hindgut microbiota fermentation. The lower SCFA concentration at D7 compared with D21 and D42 also indicates the less developed and/or functional gut at this stage. However, the limitation of this study is that the daily starter intake was not recorded and it is strongly recommended to include intake measure for the future studies to link the gut microbiota and their fermentation profiles. Butyrate plays important roles in gut physiology, immune system and inflammatory response (Wang et al.2012; Arpaia et al.2013; Nastasi et al.2015). It can enhance intestinal barrier function by increasing the expression of tight junction protein related genes (claudion-1, Zonula, Occludens-1) (Wang et al.2012). Moreover, butyrate and propionate have been reported to regulate T cells production and function (Arpaia et al.2013), as well as inhibiting lipopolysaccharide-induced expression of proinflammatory cytokines IL-6 and IL-12p40 (Nastasi et al.2015). Therefore, the lower concentration of SCFA in the hindgut at D7 suggests potential lower immune function, and the importance to enhance gut health at this stage. Microbial amino acid metabolism, carbohydrate metabolism and energy metabolism are crucial functions in the hindgut, which provide energy to the host (McNeil 1984). The higher predicted microbial energy metabolism at D7 indicates that microbiota during early life tends to harvest more energy from the lumen substance for their own growth and proliferation. In addition, the significant increase in predicted amino acid metabolism of mucosa-attached bacteria at D21 and D42 suggests that bacteria tended to derive more energy from amino acid fermentation with the increase of age of calves. The observed temporal variations in the predicted microbial functions of the hindgut bacteria suggest potential temporal variations in the energy harvesting mechanisms with the changes associated with host diet. It is noticeable that the functional prediction based on 16s rRNA gene is biased and future metagenomics and metatranscriptomics are needed to assess the function of hindgut microbiome. However, the predicted function could provide preliminary information of the hindgut microbial functions of pre-weaned calves. CONCLUSION This is the first study to explore the mucosa-attached and digesta-associated microbial composition along the cecum, colon and rectum using amplicon sequencing during the pre-weaning period of dairy calves. The results showed the effect of age on both communities, while no regional effect was detected. It is important to note that calf age is confounded by the changes in dietary regimes (e.g. colostrum, whole milk and calf starter feeding), the management (e.g. housing). The potential rumen development can also influence the microbial composition in the hindgut of dairy calves during pre-weaned period. The changing pattern of the relative abundance of SCFA-producing bacterial genera including Christensenellaceae R-7 group, Blautia, Coprococcus 1, Lachnospiraceae NK4A136 group, Lachnospiraceae UCG-008, Pseudobutyrivibrio, Ruminiclostridium 5, Ruminiclostridium 6 and Ruminococcus 1 with the increase of age was accompanied by the variation of SCFA concentration in the gut, indicating the importance of hindgut microbiota on energy harvest. The higher relative abundance of potential pathogenic bacteria Escherichia-Shigella and Salmonella during the first week indicate that calves may be more susceptible to intestinal infections. However, further studies are needed to explore the functional roles of hindgut microbiota through metagenomics or metatranstriptomics-based approaches. Such knowledge may provide a comprehensive understanding of the importance of hindgut microbiota and microbial manipulation strategies for dairy industry. Overall, this preliminary study has provided fundamental knowledge on hindgut microbial profile of pre-weaned calves under the regular management practice, which is a stepping stone for future nutritional intervention and disease challenge studies to define the role of hindgut microbiota in animal production and health. SUPPLEMENTARY DATA Supplementary data are available at FEMSEC online. Acknowledgements The authors would like to thank Y. Chen, B. Yang, F. Li, O. Wang, X. Xie, A. L. Neves, and B. Ghoshal for assistance in sequencing preparation and data analysis, and acknowledge G. Liang, M. 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FEMS Microbiology EcologyOxford University Press

Published: Mar 1, 2018

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