Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Alterations in rumen microbiota via oral fiber administration during early life in dairy cows

Abstract

Bacterial colonization in the rumen of pre-weaned ruminants is important for their growth and post-weaning productivity. This study evaluated the effects of oral fiber administration during the pre-weaning period on the development of rumen microbiota from pre-weaning to the first lactation period. Twenty female calves were assigned to control and treatment groups (n = 10 each). Animals in both groups were reared using a standard feeding program throughout the experiment, except for oral fiber administration (50–100 g/day/animal) from 3 days of age until weaning for the treatment group. Rumen content was collected during the pre-weaning period, growing period, and after parturition. Amplicon sequencing of the 16S rRNA gene revealed that oral fiber administration facilitated the early establishment of mature rumen microbiota, including a relatively higher abundance of Prevotella, Shuttleworthia, Mitsuokella, and Selenomonas. The difference in the rumen microbial composition between the dietary groups was observed even 21 days after parturition, with a significantly higher average milk yield in the first 30 days of lactation. Therefore, oral fiber administration to calves during the pre-weaning period altered rumen microbiota, and its effect might be long-lasting until the first parturition.

Introduction

The gastrointestinal tract of mammals is inhabited by a symbiotic microbial community, which influences the health and growth performance of the host animals1. The rumen represents a typical example of such environments, as feeds ingested by ruminants are degraded and fermented primarily by highly diverse microorganisms including bacteria, archaea, fungi, and protozoa into components such as short-chain fatty acids (SCFAs) and microbial proteins that can be used by the host2. Although the core bacterial members of rumen microbiota are widely distributed regardless of the breed or species of ruminants3, the relative abundance of each bacterial species in the rumen of individual animals varies extensively4. The relatively higher host specificity of the adult rumen microbiota is suggested by the quick reestablishment of the original bacterial community composition following a total exchange of the rumen contents5. Additionally, individual variations in rumen microbiota can influence host productivity6. Although the individuality of rumen microbiota can serve as a target for genetic selection and breeding7, it represents one of the hurdles in manipulating rumen microbiota via feeding management to improve host productivity. Yáñez-Ruiz et al.8 proposed the rumen programming concept, in which the composition of rumen microbiota is manipulated via feeding management during early life, leading to improved lifetime productivity. According to this concept, based on the immaturity of the rumen of pre-weaned calves in terms of function and microbiota9, rumen fermentation may be directed to the desired state by manipulating the establishment of microbiota via feeding intervention in the early life of calves.

The intake of solid feed, such as starter and roughage, increases in calves aged > 3 weeks and stimulates microbial proliferation10 and SCFA production, which facilitates rumen development11. Therefore, under normal feeding conditions, the morphological and functional development of the rumen is accelerated after 4–6 weeks of age12. The calf rumen is rapidly colonized by microbes immediately after birth13. Major fibrolytic bacterial species, such as Fibrobacter succinogenes and Ruminococcus flavefaciens, have been detected in calf rumen within the first 3 days after birth14. These observations suggest the solid feed can be potentially digested in the rumen of calves in their early life. Therefore, an increase in solid feed intake from the first week of life may stimulate microbes that have already colonized the rumen, leading to early rumen development.

Although several studies have indicated that increased roughage feeding to calves facilitates the colonization of rumen bacteria, including major cellulolytic species15,16, these studies have relied on the voluntary feed intake of calves. O’Hara et al.9 suggested that the rumen microbiota should be manipulated via early dietary intervention before 3 weeks of age, when rumen microbiota and voluntary intake of solid feed have not yet been established. Oral administration represents a feasible strategy to achieve an increased supply of solid feed before initiating voluntary intake. However, an appropriate method to achieve oral administration of solid feed to calves has not been developed yet. Therefore, we previously performed a feeding trial via oral fiber administration to newborn calves from 3 days after birth17 and confirmed that oral fiber administration improves body weight gain and gut microbiota in the first 3 weeks after birth. Since data on the effect of oral fiber administration on the health of neonatal calves were limited, the previous study mainly evaluated the presence of adverse effects of oral fiber administration on calf health, such as growth and gut environment. Thus, rumen microbiota in oral fiber-administered calves remained to be investigated.

The aim of the present study was to assess the effect of oral fiber administration from 3 days after birth on rumen bacterial colonization in pre-weaned calves and to evaluate its long-lasting effect on rumen microbiota in adult cows. We hypothesized that oral fiber administration before initiation of voluntary intake of solid diets could facilitate the early development of rumen microbiota via supplementation of growth substrates for bacteria. Based on the rumen programming concept, we presumed that dietary intervention from the early stage of life until weaning could impact the establishment of the rumen microbiota along with long-lasting effects on adult rumen microbiota. To test these hypotheses, we conducted long-term monitoring of rumen microbiota in individual dairy cows from the first week of life to 3 weeks after the first calving.

Results

Effect of oral fiber administration on rumen fermentation and structure of microbiota

A relatively higher butyrate proportion (P = 0.05) and lower ammonia nitrogen (NH3-N) concentration (P < 0.05) were detected in the rumen of the treatment group during the pre-weaning period, while significant differences were not detected in rumen fermentation parameters of adult animals throughout the prepartum and postpartum periods (Supplementary Table S1).

Amplicon sequencing generated a total of 3,701,563 non-chimeric reads, with 20,957 ± 346 reads/sample (mean ± standard error) for the control group and 21,110 ± 422 reads/sample (mean ± standard error) for the treatment group. After data processing for assignment of each read to bacterial taxa at the genus level, 11,216 unique amplicon sequence variants (ASVs) were detected. Principal coordinate analysis (PCoA) of the rumen bacterial community in calves (Fig. 1) showed that Bray–Curtis dissimilarities in the rumen bacterial community were affected by dietary group (P < 0.001), calf age (P < 0.001), and diet × age interaction (P < 0.01). Among the alpha diversity indices of the rumen microbiota in calves higher Shannon index (P < 0.05) was detected in the treatment group at 7 days of age (Supplementary Table S2). Chao1 and abundance-based coverage estimator (ACE) were affected (P < 0.05) by the dietary group in adult animals throughout the prepartum and postpartum periods (Supplementary Table S2).

Figure 1
figure 1

Change in the ruminal bacterial community structure in calves from 7 to 56 days of age. The PCoA plot was generated based on Bray–Curtis dissimilarities of rumen bacterial community determined via 16S rRNA gene amplicon sequencing. Colors indicate the dietary groups; control (yellow) and treatment (blue). Different symbols represent different age points. Individual points represent individual animals. P-values of the effect of dietary group (P < 0.001), calf age (P < 0.001), and diet × age interaction (P < 0.01) was calculated using the PERMANOVA test.

Alterations in the rumen microbiota of pre-weaned calves via oral fiber administration

The bacterial communities clustered by the dietary group at 7–35 days of age (Supplementary Fig. S1). Of the 11,216 unique ASVs, 652 showed mean relative abundances of > 0.1% in either the control or the treatment groups at one of the ages (7, 21, 35, 49, or 56 days) and were used for the comparison (Fig. 2). Pre-weaned calves in the treatment group shared a larger number of bacterial ASVs with weaned calves than did those in the control group at 7 days of age (45 vs. 3 ASVs), and this trend continued throughout the pre-weaning period (38 vs. 13 ASVs at 21 days, 36 vs. 10 ASVs at 35 days, and 27 vs. 20 ASVs at 49 days of age).

Figure 2
figure 2

Bacterial ASVs shared by pre-weaned and weaned calves. Venn diagrams of ASVs shared by pre-weaned calves at (a) 7, (b) 21, (c) 35, and (d) 49 days of age and weaned calves at 56 days of age are shown. Pre-weaned calves were separated based on the dietary groups.

Among the bacterial taxa detected via 16S ribosomal RNA (rRNA) gene amplicon sequencing on the rumen of calves aged 7–56 days (Supplementary Table S3), bacterial genera showing significant differences in their relative abundance by the treatment during at least one sampling point from 7 to 56 days of age were selected and are depicted in Fig. 3. We found remarkable differences in the rumen microbiota structure between the control and treatment groups within the first 21 days after birth (Fig. 3). At 7 days of age, 11 taxa showed a higher abundance in the treatment group, while 5 taxa showed lower abundance than that in the control group. Particularly, the abundance of Prevotella 7 (17.44% vs. 2.64%, P < 0.05), Shuttleworthia (6.41% vs. 0.09%, P < 0.01), Mitsuokella (2.67% vs. 0.02%, P < 0.01), and Selenomonas (1.60% vs. 0.01%, P < 0.01) was higher in the treatment group, while the abundance of Porphyromonas (0.36% vs. 6.41%, P < 0.05) was lower in the treatment group than that in the control group. Although significant difference was not observed, the abundance of Bacteroides was lower in the treatment group than that in the control group at 7 days of age. At 21 days of age, 9 taxa showed a higher abundance in the treatment group, whereas 6 taxa showed a lower abundance than that in the control group. Among them, the treatment group showed a higher abundance of Prevotella 7 (21.74% vs. 2.19%, P < 0.01), Ruminococcaceae UCG-014 (5.62% vs. 1.38%, P < 0.01), and Shuttleworthia (1.40% vs. 0.22%, P < 0.05) than that in the control group, while Ruminococcaceae UCG-005 (0.02% vs. 1.22%, P < 0.01), Lachnospiraceae FCS020 group (0.01% vs. 1.82%, P < 0.01), and Bacteroides (0.03% vs. 0.50%, P < 0.01) had a relatively lower abundance. No remarkable differences in abundance of the selected bacterial taxa were observed in animals aged 35–56 days.

Figure 3
figure 3

Change in the relative abundance of bacterial genera determined via amplicon sequencing. Bacterial genera showing > 0.1% relative abundances and significantly affected by the diet effect were selected from Supplementary Table S3, and the difference between the control and treatment groups at each sampling point were evaluated by a negative binomial model implemented as a Wald test in DESeq2 package in R software. Bacterial genera showing significant differences during at least one age point from 7 to 56 days of age are depicted in the graph. C control group, T treatment group.

Follow-up monitoring of the rumen microbiota in the growing and parturition period

PCoA of the rumen bacterial community from 9 months of age until 21 days after parturition (Supplementary Fig. S2) showed that the beta diversity of the rumen microbiota was affected by diet (P = 0.01) and animal age (P < 0.001). The bacterial community structures differed by the dietary groups until 21 days after parturition (Fig. 4).

Figure 4
figure 4

Change in the ruminal bacterial community structure in adult cows. The PCoA plot was generated based on Bray–Curtis dissimilarities in rumen bacterial communities determined via 16S rRNA gene amplicon sequencing for respective ages; (a) 9 months, (b) 60 days pre-calving, (c) 21 days pre-calving, (d) at calving, and (e) 21 days post-calving. Individual points in each plot represent individual animals. Colors indicate the dietary groups; control (yellow) and treatment (blue). P-values of the diet effect at 9 months (P = 0.02), 60 days pre-calving (P = 0.12), 21 days pre-calving (P = 0.05), at calving (P = 0.58), and 21 days post-calving (P = 0.03) were calculated using PERMANOVA test.

Among the bacterial taxa detected via 16S rRNA gene amplicon sequencing on the rumen microbiota in the growing and parturition period (Supplementary Table S4), bacterial genera that showed significant differences in relative abundance between the control and treatment groups at each sampling point are presented in Table 1. From 9 months of age to 21 days before calving, 4 taxa showed a higher abundance in the treatment group, whereas 5 taxa showed lower abundance than that in the control group. The treatment group had a lower abundance of Prevotella 1 (21.86% vs. 35.60%, P < 0.01) at 21 days before calving than that in the control group. The abundance of Ruminiclostridium 9 (0.45% vs. < 0.01%, P < 0.01) at calving and Shuttleworthia (0.52% vs. 0.11%, P < 0.01) and Unclassified (f) Muribaculaceae (0.10% vs. 0.00%, P < 0.01) at 21 days after calving were higher in the treatment group than that in the control group. Furthermore, these three bacterial taxa were differentially abundant in the treatment compared to control at 21 days after calving detected by the linear discriminatory analysis effect size (LEfSe) analysis (Supplementary Fig. S3).

Table 1 Bacterial taxa showing significant differences between the control and treatment groups at 9 months of age and around calving.

The body weights of the animals in both groups were not significantly different from 7 to 22 months of age (Supplementary Fig. S4). On the other hand, cows in the treatment group showed a higher (P < 0.05) average milk yield during the first 30 days of the first lactation period than that of cows in the control group (Fig. 5). Hierarchical cluster analysis of rumen microbiota at 21 days after calving and average milk yield during the first 30 days of lactation is shown in Fig. 6a. The genera Ruminococcus 2, Uncultured (f) Muribaculaceae, Schwartzia, and Treponema 2 were found to cluster together with the average milk yield of the cows. Furthermore, three of these four bacterial taxa were more abundant in the rumen of the treatment group at 21 days after calving than in the control group (Fig. 6b), and this observation was also confirmed by the LEfSe analysis (Supplementary Fig. S3).

Figure 5
figure 5

Average milk yield during the first 30 days of the lactation period. Milk yield was aggregated weekly or monthly, and P-values were calculated using the Welch’s t-test between the dietary groups at each time point. Asterisk (*) and dagger (†) indicate significance (P < 0.05) and tendency (P < 0.10), respectively.

Figure 6
figure 6

Exploration of the correlation between bacterial taxa and milk yield. (a) Heat map of hierarchical cluster analysis of rumen microbiota and milk yield. Rows represent the bacterial taxa (> 1.0% abundance) determined via 16S rRNA gene amplicon sequencing at 21 days after calving and average milk yield during the first 30 days of the lactation period. Columns represent the individual animals in each dietary group. Heat map color scale (black to green) displays the row Z-score (Z-score = [value of variable of an individual animal − mean of variable]/standard deviation). A dendrogram was generated based on Spearman’s correlation coefficient. (b) Relative abundance of the bacterial taxa clustered with milk yield in panel (a). Each box plot shows data of six animals and their range, median, and quartiles. Asterisk (*) and dagger (†) indicate significance (P < 0.05) and tendency (P < 0.10), respectively. P-values were calculated using a negative binomial model implemented as a Wald test in DESeq2 package in R software.

Discussion

The supplementation of roughage to calves during the pre-weaning period shows beneficial effects, such as improvement in feed intake, growth performance, rumination, and rumen environment18,19. We previously confirmed the beneficial effect of oral fiber administration on calves from 3 days of age to the age of weaning; calves that received oral fiber administration show improved body weight and hindgut microbiota within the first 3 weeks after birth17. The present study revealed that oral fiber administration to calves during the early stage of life altered rumen microbiota, and its effect might be long-lasting until the first parturition.

Diet plays a major role in ruminal microbial colonization in ruminants3. Pre-weaning diets primarily determine the nature of the rumen microbiota in calves20. In the present study, oral administration of a fibrous diet from 3 days of age resulted in the higher fibrous diet intake of calves until 28 days of age without affecting the starter intake (Supplementary Table S5). Therefore, supplementation of calves with a fibrous diet soon after birth leads to development of a distinct bacterial community in the rumen of pre-weaned calves. Pre-weaned calves in the treatment group shared a larger number of bacterial ASVs with weaned calves throughout the pre-weaning period in the present study, suggesting that oral fiber administration facilitates earlier colonization of rumen bacteria.

The distribution of Prevotella spp. within 21 days after birth was the most notable difference in the rumen microbiota of calves; oral fiber administration remarkably increased the abundance of Prevotella spp. This finding was further confirmed via real-time polymerase chain reaction (PCR) (Supplementary Table S6). Prevotella spp. are the most abundant genera in the rumen of mature ruminants3. When calves are fed primarily with milk or milk replacer during the first 14 days after birth, Bacteroides spp. dominate the rumen, and Prevotella spp. become dominant after 14 days of age, along with a gradual increase in solid feed intake21. In fact, the control group in the present study had a relatively higher abundance of Bacteroides spp. at 7 days of age, whereas the treatment group harbored Prevotella spp. at the same age. The present study indicates that early fibrous diet supplementation facilitates early colonization of the predominant rumen bacteria found in adult animals. The increase in abundance of Prevotella spp. via oral fiber administration is reasonable, since this genus represents one of the predominant plant cell wall-polysaccharide degraders found in the rumen22. Prevotella spp. utilize xylan by producing various enzymes for degradation23. The fibrous diet used in the present study contained Timothy hay and psyllium,the latter is mainly composed of heteroxylan. We previously observed that the abundance of Prevotella spp. is enhanced upon psyllium supplementation, but not by Timothy hay, in the feces of calves17. Therefore, psyllium supplementation may enhance the growth of Prevotella spp. in the rumen of calves within the first 21 d after birth.

Oral fiber-administered calves had a relatively higher abundance of Shuttleworthia spp., Mitsuokella spp., and Selenomonas spp., with an increased proportion of butyrate at 7 days of age. Shuttleworthia spp. are known to produce butyrate24 which partly explains the relatively higher butyrate proportion observed at 7 days of age. Mitsuokella spp. produce lactate as the major fermentation product25, and Selenomonas spp. utilize lactate to produce propionate26. Although propionate proportion did not differ between the dietary groups at 7 days of age, the growth of these lactate-producing and lactate-utilizing bacteria may be enhanced in the rumen of calves upon oral fiber administration. Butyrate and propionate have been reported to enhance the development of the rumen epithelium27,28. Therefore, an increase in the abundance of bacterial taxa associated with butyrate and propionate production may be beneficial for calf growth by enhancing the development of the rumen epithelium.

Dietary interventions in early life can effectively manipulate rumen and fecal microbial communities, leading to an improvement in the early adult life productivity of ruminants29,30. In the present study, we observed the compositional difference in rumen microbiota and relatively higher average milk yield in the first 30 days of lactation period in cows that underwent early dietary intervention. Although feed intake record was not available due to total mixed ration feeding on the farm, the animals used in the present study were kept under the same feeding regimen after weaning. Therefore, we could assume that the early dietary intervention was the most significant factor affecting rumen microbiota establishment. Contrary to the present study, Dill-McFarland et al.16 reported that the supplementation of different solid diets during the pre-weaning period influences the early development of rumen microbiota in dairy calves without long-term effects on milk production. Although the discrepancies in findings between studies need to be clarified, the oral administration of a solid diet before initiation of voluntary intake may represent one of the factors leading to long-lasting effects.

In the present study, Prevotella was the predominant bacterial genus found in the rumen of both dietary groups during the prepartum and postpartum periods, which is in agreement with a previous study31. The treatment group had a relatively lower abundance of Prevotella 1 during the prepartum period. Similarly, real-time PCR quantification showed numerically lower abundance of Prevotella spp. in the treatment group during the prepartum period (Supplementary Table S7). The presence of this bacterial genus is negatively correlated with feed efficiency in bulls32,33. Therefore, a low abundance of Prevotella spp. in the treatment group may be beneficial during the prepartum period in terms of energy acquisition, as the nutritional status in the prepartum period influences milk yield and fertility parameters during lactation34.

Cluster analysis based on postpartum rumen microbiota composition and milk yield revealed a positive association of Ruminococcus 2, Uncultured (f) Muribaculaceae, Schwartzia, and Treponema 2 with milk production in the first 30 days of the lactation period. Tong et al.35 reported that Ruminococcus 2 and Muribaculaceae are relatively more abundant in dairy cows with higher milk yields. Another study reported that the abundance of Treponema and Muribaculaceae in the rumen is positively correlated with milk yield, milk fat content, milk protein content, and feed efficiency in dairy cows36. Furthermore, Cunha et al.37 suggested that the presence of Schwartzia, Treponema, and Muribaculaceae is negatively correlated with methane production in Holstein cows. Therefore, presence of these genera may contribute to efficient feed conversion into energy sources for milk production in dairy cows. Collectively, the relatively higher abundance of bacterial genera associated with efficient milk production may explain the relatively higher milk yield in the treatment group.

This study has several limitations that need to be clarified. Although we observed the compositional difference in rumen microbiota and relatively higher average milk yield in cows that underwent oral fiber administration during the early stages of life, the mechanism of action remains unknown. Furthermore, the rumen microbiota and the milk yield could also be affected by the genetic background of the animals. However, the host genetic influence was not controlled in the present study. In addition, the number of animals and experimental period were insufficient to evaluate the long-lasting effect of early dietary intervention on rumen microbiota and host productivity. This study monitored only the first month of lactation in a small number of animals. Further studies should evaluate relatively larger animal numbers and longer monitoring periods while minimizing the other factors (i.e., feed intake, host genetics) affecting rumen microbiota and milk yield. This will verify the possibility of manipulating the rumen microbiota in the early stages of life, which could contribute to improving host productivity.

In summary, we found that oral fiber administration from 3 days of age until weaning facilitated the early establishment of adult rumen microbiota in pre-weaned calves. This may explain the increased growth performance of oral fiber-administered calves in a previous study17. Furthermore, our dietary intervention strategy could exhibit a long-lasting effect on the rumen microbiota structure until 21 days after parturition, which may favorably affect milk production in dairy cows. Overall, our findings suggest that dietary intervention via oral fiber administration before initiation of voluntary intake of a solid diet alters rumen microbiota structure, which might contribute to improving host growth and productivity.

Materials and methods

Animals and diets

The animal experiments were conducted in accordance with the Guidelines for Animal Experiments and Act on Welfare and Management of Animals, Hokkaido University, and all experimental procedures were approved by the Animal Care and Use Committee of Hokkaido University. All animal experiments were carried out in accordance with ARRIVE guidelines. Twenty newborn female Holstein calves with an average birth weight of 37.1 ± 1.0 kg (mean ± standard error) were randomly allocated to either the control or treatment group at birth. All calves were housed individually in separate calf hutches containing sawdust bedding. Feeding and managing of animals until weaning at 50 d of age was performed as described previously17. After supplementing colostrum at birth, calves in both groups were fed 4 L of pasteurized whole milk (44.2% crude protein [CP] and 29.3% fat on a dry matter [DM] basis) as a transition milk during the first week since birth. From 8 days until weaning at 50 days of age, milk replacer (28.0% CP and 18.0% fat on a DM basis) was fed twice daily at 0830 and 1600 h. Water, calf starter (22.9% CP, 11.0% neutral detergent fiber [NDF], 5.6% acid detergent fiber [ADF], 6.2% crude ash, and 3.0% ether extract on a DM basis), and chopped Timothy hay (3.4% CP, 53.1% NDF, 34.2% ADF, 4.3% crude ash, and 1.7% ether extract on a DM basis) were provided for ad libitum intake from 3 days of age. In addition to voluntary intake of solid diets, the calves in the treatment group were orally administered with a mixture of ground Timothy hay and psyllium (4.4% CP, 78.6% NDF, 5.8% ADF, 3.9% crude ash, and 0.3% ether extract on a DM basis) from 3 days until weaning at 50 days of age. Timothy hay was ground for oral administration using a Wiley grinder (WM-3, Irie Shokai) with a 2-mm screen. To improve the handling of the treatment diet for oral administration, we incorporated psyllium, which is a dietary fiber that primarily improves gastrointestinal conditions in humans and can be incorporated in oral electrolyte solution supplemented to neonatal calves38. As a treatment diet, ground Timothy hay (50 g) and psyllium (6 g) were mixed with 200 mL of water. Owing to the adhesiveness of psyllium, the treatment diet formed a “hay ball” and showed slight stickiness, which facilitates swallowing by calves. At 3–7 days of age, one hay ball (50 g of fibrous diet) was orally administered after morning milk feeding. From 8 days of age to weaning, an additional hay ball was fed immediately after evening milk feeding (100 g fibrous diet per day).

After weaning, animals in both dietary groups were merged into the same herd and managed on the same farm under identical conditions. From 9 months of age until calving, heifers were fed a ration containing Timothy hay, alfalfa hay, fescue hay, and concentrate. After calving, the cows were fed a diet for lactating cows, as described in Supplementary Table S8. Diets comprised a total mixed ration and were fed twice daily at 0900 and 1600 h. All animals had ad libitum access to water and mineral blocks throughout the experiment. Daily milk production for each cow was measured for the first 30 days of the lactation period and the average values for each dietary group on a weekly and monthly basis were calculated. Milk yield for four animals in each dietary group were not recorded due to health problems including mastitis and displaced abomasum symptoms after calving.

In this study, all animals (n = 20) were maintained until 9 months of age, without severe problems. Owing to health problems, several animals were excluded from the experiment before parturition as follows: three animals (one in the control group and two in the treatment group) at 60 days before the expected calving date and one animal in the control group at 21 days before the expected calving date. One animal in the control group (15 days after calving) and two animals in the treatment group (calving day) were diagnosed with displaced abomasum symptoms and were excluded from further sampling. Owing to technical problems, samples were not collected from three animals aged 7 days in the treatment group and one animal aged 21 days in the control group. All other samples (n = 176) were obtained at the target sampling points.

Sampling of rumen contents

Rumen contents were collected orally using a stomach tube. The stomach tube and the sample collection flask were thoroughly cleaned using water between sample collections from individual animals; the first fraction of the sample was discarded to avoid contamination from the previous sample and saliva. All samples were collected at 4 h after morning feeding. Rumen contents were collected at 7, 21, 35, 49, and 56 days, and at 9 months of age, 60 and 21 days before the expected calving date, at calving day, and 21 days after calving. The pH was measured using a pH meter (pH meter F-51; Horiba, Kyoto, Japan) immediately after sampling. Samples were collected in a sterile 50 mL tube and immediately placed on ice, followed by storage at − 30 °C until use.

Chemical analysis

Rumen contents (1.0 g) were centrifuged at 16,000×g at 4 °C for 5 min, and the supernatant was collected. The SCFA content was analyzed using a gas chromatograph (GC-14B; Shimadzu, Kyoto, Japan) as described previously39. In brief, the supernatant of the rumen contents was mixed with 25% meta-phosphoric acid at a 5:1 ratio, incubated overnight at 4 °C, and centrifuged at 10,000×g at 4 °C. The supernatant was then mixed with crotonic acid as an internal standard and injected into a gas chromatograph equipped with an ULBON HR-20 M fused silica capillary column (0.53 mm i.d. × 30 m length, 3.0 µm film; Shinwa, Kyoto, Japan) and a flame-ionization detector. d/l-lactic acid levels were measured using a commercial assay kit (Megazyme International Ireland, Wicklow, Ireland) according to the manufacturer’s instructions. NH3-N levels were measured via the phenol-hypochloride reaction method40 using a microplate reader at 660 nm (ARVO MX; Perkin Elmer, Yokohama, Japan).

DNA extraction and rumen microbiota profiling via amplicon sequencing

Total DNA was extracted and purified using the repeated bead-beating plus column method41. Rumen contents (0.25 g) were homogenized using sterile glass beads (0.4 g; 0.3 g of 0.1 mm and 0.1 g of 0.5 mm) and cell lysis buffer (1 mL; 500 mM NaCl, 50 mM Tris–HCl [pH 8.0], 50 mM ethylenediaminetetraacetic acid (EDTA), and 4% sodium dodecyl sulfate). The lysates were then incubated at 70 °C for 15 min, and the supernatant was collected for further processing. Bead-beating and incubation steps were repeated once, and all supernatants were combined. Total DNA was precipitated using 10 M ammonium acetate and isopropanol, followed by purification using the QIAamp Fast DNA Stool Mini Kit (Qiagen, Hilden, Germany). The DNA concentration was quantified using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and adjusted with Tris–EDTA buffer to the appropriate concentration.

For a comprehensive analysis of rumen bacterial communities, the MiSeq sequencing platform (Illumina, San Diego, CA, USA) was used. Total DNA obtained from the rumen contents was diluted to a final concentration of 5 ng/μL and subjected to PCR amplification of the V3-V4 regions of the 16S rRNA gene using the primer sets S-D-Bact-0341-b-S-17 (5′-CCTACGGGNGGCWGCAG-3′) and S-D-Bact-0785-a-A-21 (5′-GACTACHVGGGTATCTAATCC-3′)42. The PCR mixture consisted of 12.5 μL of 2× KAPA HiFi HotStart Ready Mix (Roche Sequencing, Basel, Switzerland), 0.1 μM of each primer, and 2.5 μL of DNA (5 ng/μL). PCR amplification was performed according to the following program described previously9: initial denaturation at 95 °C for 3 min; 25 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s; and a final extension step at 72 °C for 5 min. Amplicons were purified using AMPure XP beads (Beckman-Coulter, Brea, CA, USA) and subjected to sequencing on the Illumina MiSeq platform (Illumina) using the MiSeq Reagent Kit v3 (2 × 300 paired-end).

Data obtained from amplicon sequencing using the MiSeq platform were analyzed using QIIME2 version 2019.443. Paired reads were filtered, dereplicated, merged, and chimera-filtered using the q2-dada2 plugin44 to generate ASVs. Taxonomic classification of the ASVs was performed at the phylum, class, order, family, and genus levels using the SILVA 132 99% operational taxonomic units, full length, seven level taxonomy classifier (silva-132-99-nb-classifier.qza). Sequenced data were processed further and analyzed using R software version 3.6.245. ASV and taxonomy tables generated using QIIME2 were imported into R and merged with the sample metadata using the Phyloseq Bioconductor packages46. ASVs identified as Archaea, chloroplasts, and mitochondria were excluded. All samples were rarefied to a sampling depth of 16,805 reads, which was the smallest number of reads observed per sample in the filtered ASV table. Alpha diversity indices including Chao1, ACE, Shannon, and Simpson indices were calculated using the phyloseq function “estimate_richness”. PCoA was performed to determine differences in the microbial community structure based on the Bray–Curtis dissimilarity matrices at the genus level using the Phyloseq package. Venn diagrams were generated using ASVs showing mean relative sequence abundances of > 0.1% in either the control or the treatment groups at each sampling point. The relative abundance of each bacterial taxon was calculated by dividing the number of reads assigned to each taxon by the total number of reads. Taxa with an average relative abundance > 0.1% in > 50% of samples in either the control or treatment group during at least one sampling point were used for the analysis. Hierarchical cluster analysis of bacterial genera determined via amplicon sequencing at 21 days after calving and the weekly and monthly average milk yield for the first 30 days of lactation period was performed using the distances calculated from Spearman’s correlation and average linkage clustering.

Quantification of target bacterial species/groups using real-time PCR

The relative abundance of known ruminal bacterial species and groups, including the total bacteria, F. succinogenes, R. flavefaciens, Ruminococcus albus, Butyrivibrio spp., Prevotella spp., Selenomonas ruminantium, Megasphaera elsdenii, Treponema spp., Streptococcus bovis, Anaerovibrio lipolytica, and Ruminobacter amylophilus, was quantified using real-time PCR. Amplification was performed using a Light Cycler 480 system (Roche Applied Science, Mannheim, Germany) with a KAPA SYBR Fast qPCR Kit (Roche Sequencing, Basel, Switzerland) and the respective primer sets (Supplementary Table S9). The standards used for the real-time PCR were prepared as described previously47. Briefly, plasmid DNA containing the respective target bacterial 16S rRNA gene sequence was obtained by PCR cloning using the species/genus-specific or bacterial universal primer sets. The concentration of the plasmid was determined with a spectrometer. Copy number of each standard plasmid was calculated using the molecular weight of nucleic acid and the length (base pair) of the cloned standard plasmid. Ten-fold dilution series ranging from 1 to 108 copies were prepared for each target and run along with the samples. The respective genes were quantified using standard curves obtained from the amplification profile of the dilution series of the plasmid DNA standard (Supplementary Table S9). The PCR cycling conditions and reaction mixture were the same as those reported previously48. The relative abundance of each bacterial target was expressed as the proportion (%) of the abundance of the 16S rRNA genes of each bacterial target relative to that of the total bacteria.

Statistical analysis

All data were sorted based on animal age into two sets, from 7 to 56 days of age and from 9 months of age to 21 days after calving, and analyzed separately. Data on fermentation parameters and bacterial abundance quantified via real-time PCR were analyzed using a repeated measures model using GraphPad Prism software version 9.1 (GraphPad Software, San Diego, CA, USA) with the fixed effects of dietary group, age, and diet × age interaction, and the random effect of animals within the groups. The Greenhouse–Geisser correction was used where sphericity was violated. If the P-value for the treatment effect was < 0.1, then Tukey’s method was used for multiple comparisons of the means. The effects of dietary group, age, and diet × age interaction on the bacterial taxon abundance determined via amplicon sequencing were assessed using the Poisson regression model in the lme4 package49 in R software. Dunn’s test was used for multiple comparisons, and P-values were adjusted using the Benjamini and Hochberg method50. Although the treatment effect was found to be significant for several bacterial genera, the post hoc test did not reveal any differences between the control and treatment groups at each sampling point (Supplementary Tables S3, S4). Therefore, the bacterial taxa determined via amplicon sequencing were further compared between the dietary groups at each sampling point using the negative binomial model implemented as the Wald test in the DESeq2 Bioconductor package in the R software51. A false discovery rate threshold of 0.15 was used to determine significance. Bray–Curtis dissimilarity matrices were calculated and visualized as PCoA using Phyloseq Bioconductor packages in R. permutational multivariate analysis of variance (PERMANOVA) tests were performed based on the Bray–Curtis dissimilarity matrices to assess the effect of dietary group, age, and diet × age interaction on microbial composition using the Vegan package version 2.5-752 in R software.

Data availability

The raw sequences generated and analyzed during the study are available under BioProject accession number PRJNA715025 (https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA715025) from the National Center for Biotechnology Information (NCBI) sequence read archive (SRA).

References

  1. Zilber-Rosenberg, I. & Rosenberg, E. Role of microorganisms in the evolution of animals and plants: The hologenome theory of evolution. FEMS Microbiol. Rev. 32, 723–735 (2008).

    CAS  Article  Google Scholar 

  2. Hungate, R. E. The Rumen and Its Microbes (Academic Press, 1996).

    Google Scholar 

  3. Henderson, G. et al. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Sci. Rep. 5, 14567. https://doi.org/10.1038/srep14567 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. Weimer, P. J. Redundancy, resilience, and host specificity of the ruminal microbiota: Implications for engineering improved ruminal fermentations. Front. Microbiol. 6, 296. https://doi.org/10.3389/fmicb.2015.00296 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Weimer, P. J., Stevenson, D. M., Mantovani, H. C. & Man, S. L. C. Host specificity of the ruminal bacterial community in the dairy cow following near-total exchange of ruminal contents1. J. Dairy Sci. 93, 5902–5912 (2010).

    CAS  Article  Google Scholar 

  6. Mizrahi, I. & Jami, E. Review: The compositional variation of the rumen microbiome and its effect on host performance and methane emission. Animal 12, S220–S232 (2018).

    CAS  Article  Google Scholar 

  7. Li, F. et al. Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle. Microbiome 7, 92. https://doi.org/10.1186/s40168-019-0699-1 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Yáñez-Ruiz, D. R., Abecia, L. & Newbold, C. J. Manipulating rumen microbiome and fermentation through interventions during early life: A review. Front. Microbiol. 6, 1133. https://doi.org/10.3389/fmicb.2015.01133 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  9. O’Hara, E. et al. Investigating temporal microbial dynamics in the rumen of beef calves raised on two farms during early life. FEMS Microbiol. Ecol. 96, 203. https://doi.org/10.1093/femsec/fiz203 (2020).

    CAS  Article  Google Scholar 

  10. Suárez, B. J. et al. Effects of supplementing concentrates differing in carbohydrate composition in veal calf diets: I. Animal performance and rumen fermentation characteristics. J. Dairy Sci. 89, 4365–4375 (2006).

    Article  Google Scholar 

  11. Pazoki, A. et al. Growth performance, nutrient digestibility, ruminal fermentation, and rumen development of calves during transition from liquid to solid feed: Effects of physical form of starter feed and forage provision. Anim. Feed Sci. Technol. 234, 173–185 (2017).

    Article  Google Scholar 

  12. Castro, J. J., Gomez, A., White, B., Loften, J. R. & Drackley, J. K. Changes in the intestinal bacterial community, short-chain fatty acid profile, and intestinal development of preweaned Holstein calves. 2. Effects of gastrointestinal site and age. J. Dairy Sci. 99, 9703–9715 (2016).

    CAS  Article  Google Scholar 

  13. Minato, H., Otsuka, M., Itabashi, H. & Mitsumori, M. Colonization of microorganisms in the rumen of young calves. J. Gen. Appl. Microbiol. 38, 447–456 (1992).

    Article  Google Scholar 

  14. Guzman, C. E., Bereza-Malcolm, L. T., De Groef, B. & Franks, A. E. Presence of selected methanogens, fibrolytic bacteria, and proteobacteria in the gastrointestinal tract of neonatal dairy calves from birth to 72 hours. PLoS ONE 10, e0133048. https://doi.org/10.1371/journal.pone.0133048 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. Kim, Y. H. et al. Effects of dietary forage and calf starter diet on ruminal pH and bacteria in Holstein calves during weaning transition. Front. Microbiol. 7, 1575. https://doi.org/10.3389/fmicb.2016.01575 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Dill-McFarland, K. A., Weimer, P. J., Breaker, J. D. & Suen, G. Diet influences early microbiota development in dairy calves without long-term impacts on milk production. Appl. Environ. Microbiol. 85, e02141. https://doi.org/10.1128/AEM.02141-18 (2019).

    CAS  Article  PubMed  PubMed Central  ADS  Google Scholar 

  17. Kodithuwakku, K. A. H. T. et al. Effects of oral administration of timothy hay and psyllium on the growth performance and fecal microbiota of preweaning calves. J. Dairy Sci. 104, 12472–12485 (2021).

    CAS  Article  Google Scholar 

  18. Castells, L., Bach, A., Araujo, G., Montoro, C. & Terré, M. Effect of different forage sources on performance and feeding behavior of Holstein calves. J. Dairy Sci. 95, 286–293 (2012).

    CAS  Article  Google Scholar 

  19. Castells, L., Bach, A., Aris, A. & Terré, M. Effects of forage provision to young calves on rumen fermentation and development of the gastrointestinal tract. J. Dairy Sci. 96, 5226–5236 (2013).

    CAS  Article  Google Scholar 

  20. Dias, J. et al. Effect of pre-weaning diet on the ruminal archaeal, bacterial, and fungal communities of dairy calves. Front. Microbiol. 8, 1553. https://doi.org/10.3389/fmicb.2017.01553 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Rey, M. et al. Establishment of ruminal bacterial community in dairy calves from birth to weaning is sequential. J. Appl. Microbiol. 116, 245–257 (2014).

    CAS  Article  Google Scholar 

  22. Dai, X. et al. Metatranscriptomic analyses of plant cell wall polysaccharide degradation by microorganisms in the cow rumen. Appl. Environ. Microbiol. 81, 1375–1386 (2015).

    Article  ADS  Google Scholar 

  23. Dodd, D., Mackie, R. I. & Cann, I. K. O. Xylan degradation, a metabolic property shared by rumen and human colonic Bacteroidetes. Mol. Microbiol. 79, 292–304 (2011).

    CAS  Article  Google Scholar 

  24. Downes, J., Munson, M. A., Radford, D. R., Spratt, D. A. & Wade, W. G. Shuttleworthia satelles gen. nov., sp. nov., isolated from the human oral cavity. Int. J. Syst. Evol. Microbiol. 52, 1469–1475 (2002).

    PubMed  Google Scholar 

  25. Lan, G. Q., Ho, Y. W. & Abdullah, N. Mitsuokella jalaludinii sp. nov., from the rumens of cattle in Malaysia. Int. J. Syst. Evol. Microbiol. 52, 713–718 (2002).

    CAS  PubMed  Google Scholar 

  26. Stewart, C. S., Flint, H. J. & Bryant, M. P. The rumen bacteria. In The Rumen Microbial Ecosystem (eds Hobson, P. N. & Stewart, C. S.) 10–72 (Springer, 1997).

    Chapter  Google Scholar 

  27. Mentschel, J., Leiser, R., Mülling, C., Pfarrer, C. & Claus, R. Butyric acid stimulates rumen mucosa development in the calf mainly by a reduction of apoptosis. Arch. Anim. Nutr. 55, 85–102 (2001).

    CAS  Google Scholar 

  28. Zhang, X. et al. Calcium propionate supplementation improves development of rumen epithelium in calves via stimulating G protein-coupled receptors. Animal 12, 2284–2291 (2018).

    CAS  Article  Google Scholar 

  29. Yáñez-Ruiz, D. R., MacÍas, B., Pinloche, E. & Newbold, C. J. The persistence of bacterial and methanogenic archaeal communities residing in the rumen of young lambs. FEMS Microbiol. Ecol. 72, 272–278 (2010).

    Article  Google Scholar 

  30. Meale, S. J. et al. Early life dietary intervention in dairy calves results in a long-term reduction in methane emissions. Sci. Rep. 11, 3003. https://doi.org/10.1038/s41598-021-82084-9 (2021).

    CAS  Article  PubMed  PubMed Central  ADS  Google Scholar 

  31. Lima, F. S. et al. Prepartum and postpartum rumen fluid microbiomes: Characterization and correlation with production traits in dairy cows. Appl. Environ. Microbiol. 81, 1327–1337 (2015).

    Article  ADS  Google Scholar 

  32. McCann, J. C., Wiley, L. M., Forbes, T. D., Rouquette, F. M. & Tedeschi, L. O. Relationship between the rumen microbiome and residual feed intake-efficiency of brahman bulls stocked on bermudagrass pastures. PLoS ONE 9, e91864. https://doi.org/10.1371/journal.pone.0091864 (2014).

    CAS  Article  PubMed  PubMed Central  ADS  Google Scholar 

  33. McGovern, E. et al. 16S rRNA sequencing reveals relationship between potent cellulolytic genera and feed efficiency in the rumen of bulls. Front. Microbiol. 9, e1842. https://doi.org/10.3389/fmicb.2018.01842 (2018).

    Article  Google Scholar 

  34. Remppis, S., Steingass, H., Gruber, L. & Schenkel, H. Effects of energy intake on performance, mobilization and retention of body tissue, and metabolic parameters in dairy cows with special regard to effects of pre-partum nutrition on lactation—A review. Asian-Aust. J. Anim. Sci. 24, 540–572 (2011).

    CAS  Article  Google Scholar 

  35. Tong, J., Zhang, H., Yang, D., Xiong, B. & Jiang, L. Illumina sequencing analysis of the ruminal microbiota in high-yield and low-yield lactating dairy cows. PLoS ONE 13, e0198225. https://doi.org/10.1101/325118 (2018).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  36. Jiang, Y. et al. Effect of sequestering agents based on a Saccharomyces cerevisiae fermentation product and clay on the ruminal bacterial community of lactating dairy cows challenged with dietary aflatoxin B1. J. Dairy Sci. 103, 1431–1447 (2020).

    CAS  Article  Google Scholar 

  37. Cunha, C. S. et al. Assessing the impact of rumen microbial communities on methane emissions and production traits in Holstein cows in a tropical climate. Syst. Appl. Microbiol. 40, 492–499 (2017).

    CAS  Article  Google Scholar 

  38. Cebra, M. L. et al. Treatment of neonatal calf diarrhea with an oral electrolyte solution supplemented with psyllium mucilloid. J. Vet. Intern. Med. 12, 449–455 (1998).

    CAS  Article  Google Scholar 

  39. Oh, S., Shintani, R., Koike, S. & Kobayashi, Y. Ginkgo fruit extract as an additive to modify rumen microbiota and fermentation and to mitigate methane production. J. Dairy Sci. 100, 1923–1934 (2017).

    CAS  Article  Google Scholar 

  40. Weatherburn, M. W. Phenol-hypochlorite reaction for determination of ammonia. Anal. Chem. 39, 971–974 (1967).

    CAS  Article  Google Scholar 

  41. Yu, Z. & Morrison, M. Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques 36, 808–812 (2004).

    CAS  Article  Google Scholar 

  42. Herlemann, D. P. R. et al. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 5, 1571–1579 (2011).

    CAS  Article  Google Scholar 

  43. Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).

    CAS  Article  Google Scholar 

  44. Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    CAS  Article  Google Scholar 

  45. R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, Austria, 2014).

  46. McMurdie, P. J. & Holmes, S. Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217. https://doi.org/10.1371/journal.pone.0061217 (2013).

    CAS  Article  PubMed  PubMed Central  ADS  Google Scholar 

  47. Koike, S., Yabuki, H. & Kobayashi, Y. Validation and application of real-time polymerase chain reaction assays for representative rumen bacteria. Anim. Sci. J. 78, 135–141 (2007).

    CAS  Article  Google Scholar 

  48. Watabe, Y., Suzuki, Y., Koike, S., Shimamoto, S. & Kobayashi, Y. Cellulose acetate, a new candidate feed supplement for ruminant animals: In vitro evaluations. J. Dairy Sci. 101, 10929–10938 (2018).

    CAS  Article  Google Scholar 

  49. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  50. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

    MathSciNet  MATH  Google Scholar 

  51. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550. https://doi.org/10.1186/s13059-014-0550-8 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  52. Oksanen, J. et al. Vegan: Community Ecology Package. http://cran.r-project.org/package=vegan (2019). Accessed 15 Dec 2021.

Download references

Acknowledgements

This work was partly supported by JSPS KAKENHI Grant Number 22H02488 and the Kieikai Research Foundation Grant 2019C021 provided to S.K.

Author information

Authors and Affiliations

Authors

Contributions

H.K., S.K. designed the study. H.O., Y.W., K.H. contributed to the sample collection. H.K., D.M. performed the laboratory analysis. H.K. performed the bioinformatic analysis. H.M. facilitated the bioinformatic analysis. H.K. wrote the original draft of the manuscript. S.K. reviewed and edited the original manuscript. S.K., K.H., Y.S., Y.K. supervised the study.

Corresponding author

Correspondence to Satoshi Koike.

Ethics declarations

Competing interests

Owada, Watabe, and Hirano are affiliated with ZEN-NOH and the National Federation of Agricultural Cooperative Associations. The remaining authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kodithuwakku, H., Maruyama, D., Owada, H. et al. Alterations in rumen microbiota via oral fiber administration during early life in dairy cows. Sci Rep 12, 10798 (2022). https://doi.org/10.1038/s41598-022-15155-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-022-15155-0

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing