The characteristics of diarrhea-related bacteria in suckling calves and their dynamic succession with ages

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The gut microbes have great influence on prevention and treatment of calf diarrhea, but their role in diarrhea is still lacking. The objective of this study was to identify the diarrhea-related bacteria in two different days of age, and to investigate whether these bacteria were affected by calf ages. Results Forty-eight new-born female calves were selected for recording the fecal score daily and collecting the rectal content at 15 and 35 days of age, respectively. The diarrhea status and health score of calves in two different ages were evaluated according to the fecal score. The rectal microbial fermentation and microbial community structure were different between high-health-status calves and low-health-status calves. Compared to calves with high health status, the low-health-status calves had decreased butyrate molar proportion in rectal feces at both 15 days of age and 35 days of age ( P < 0.05). The LEfSe analysis showed that the relative abundance of Butyricicoccaceae ( Butyricicoccus ) and Clostridiaceae (such as Clostridium sensu stricto 1 and Clostridium perfringens ) were higher in low-health-status calves at both 15 days of age and 35 days of age. However, the relative abundance of Bifidobacterium , Streptococcus , and Peptostreptococcus were lower in low-health-status calves at 15 days of age. At 35 days of age, we found that some member in Prevotellaceae (such as Prevotellaceae bacterium and Prevotella ) were especially decreased in low-health-status calves. Using random forest regression analysis, most of these genera mentioned above were identified as diarrhea-related bacteria. Furthermore, we have further revealed that some bacteria, like Erysipelotrichaceae_UCG-003 and Mogibacterium , were additional diarrhea-related bacteria at 15 days of age. While other bacteria, including Megasphaera , Prevotella 9 , Romboutsia , and Citrobacter were additional diarrhea-related bacteria at 35 days of age. The microbial co-occurrence network analysis revealed that the interaction patterns of calf microbiome changed with diarrhea status and ages. Particularly, the potential pathogens, like Escherichia Shigella , had increased participation in co-occurrence networks of diarrheic calves. Among these diarrhea-related bacteria, the genera that positively correlated with health score had apparent co-exclusion with the genera that negatively correlated with health score, but they correlated with rectal short chain fatty acids positively. Conclusions Overall, our study revealed that the diarrhea-related bacteria of calves will vary at different ages, which may contribute to the treatment and prevention of diarrhea in the calf industry by targeted microbial intervention. calf diarrhea days of age gut microbiota microbial co-occurrence network random forest regression analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Diarrhea is a common disease on dairy farm, which has an extremely high incidence in suckling calves, seriously threatens the health of calves, and negatively affects their subsequent production performance [ 1 ]. Although diarrhea can be caused by various factors, such as pathogen infections, environmental conditions, nutritional management and immune functions, the disturbance of the gut bacterial community is often tightly associated with diarrhea. It has been reported that compared to healthy calves, the calves with diarrhea experienced a fluctuation in microbial diversity and had a "delayed" gut microbiota in their early life [ 2 ]. Through a random forest algorithm, Ma et al. [ 2 ] found that Trueperella , Streptococcus , Dorea , uncultured Lachnospiraceae , Ruminococcus 2 , and Erysipelatoclostridium could be used to predict calf diarrhea with an accuracy rate of 84.3%. Furthermore, calf diarrhea can be prevented and treated by microbial intervention and modulation. Previous studies have demonstrated that probiotic supplementation can reduce the incidence of diarrhea and improve growth performance [ 3 , 4 ]. Kim et al. [ 5 ] and Islam et al. [ 6 ] recently performed intriguing trials in which they found fecal microbiota transplantation can ameliorate diarrhea in pre-weaning calves. Nonetheless, our knowledge on which specific taxa are the most diarrhea-related bacteria and how these diarrhea-related bacteria contribute to diarrhea status in calves is still limited. Previous studies have proved that the gut microbiota, especially early-life gut microbiota, play important roles on host health by providing nutrients, regulating immune system and promoting tissue maturation [ 7 , 8 ]. The gut microbial communities of calves are highly variable from birth to weaning, and their ecological succession begins with a diverse group of pioneer species [ 9 – 11 ]. Several studies have compared the difference in bacterial microbiota between diarrheic and non-diarrheic dairy calves; however, most have not distinguished the changes in calf diarrhea at different days of age [ 12 – 14 ]. Recently, Chen et al. [ 15 ] had reported that the dynamic successions of calf gut microbiota and the interactions among some bacteria could influence calf diarrhea. Thus, we hypothesize that the diarrhea-related bacteria of calves will vary at different days of age. The targeted prevention and treatment based on different age status may be more helpful for calves to cope with diarrhea challenges. The most critical period of dairy calves rearing is the first month of life, due to the high risk of disease and mortality occurrence [ 16 ]. Similarly, some reports indicated that the diarrhea in calves is mainly occurs within one month of life [ 1 , 17 ]. Therefore, the present study analyzed the bacterial community characteristics of calves in a modern dairy farm. Random forest analysis and microbial co-occurrence network were used to screen the key diarrhea-related bacteria and to deconstruct their ecological relationships in calf diarrhea at 15 days of age and 35 days of age, respectively. Our findings will provide new insight for further understanding of known or other potential bacteria related to calf diarrhea, which may contribute to the treatment and prevention of diarrhea in the calf industry. Material and methods Experiment animals and sampling The experiment was carried out at a local farm in Baoji, Shaanxi (34°41′N,109°09′E). Forty-eight new-born calves with similar body weights (39.5 ± 0.6 Kg, mean ± SE) were selected. Immediately after birth, each calf was separated from the cow and housed in the newborn calf barn for individual feeding, with 4 L of colostrum given within 1 hour and another 2 L of colostrum given within 8–10 h. All colostrum, milk, and milk replacer were pasteurized. The calves were transferred to independent calf hutches on the second day of life and were fed twice daily at 07:30 and 14:00 h, with free access to water and starter. The replacement of milk to milk replacer occurred at 20 days of age, and this transition was completed within three days. The weaning of all calves began at 57 days of age and ended at 63 days of age. The composition and nutritional level of calf starter and milk replacer are shown in Supplementary Table S1 . The daily feeding amount was adjusted according to the age of calves, and the feeding regime is shown in the Supplementary Table S2. Fecal consistency scores were recorded daily from 0 days of age to 72 days of age, using a scoring standard (0 = normal, firm stool; 1 = soft, semi-solid; 2 = runny, spreads easily; 3 = watery, devoid of solid matter), as described in previous method [ 18 ]. The initial and remaining amounts of starters were weighed daily from 0 days of age to 72 days of age. Starter samples were dried in a 105°C for 8 h to obtain dry matter (DM) content. Daily dry matter intake (DMI) per calf was calculated by multiplying daily as-fed intake by DM content of starter. Body weights were recorded before the morning feeding, starting at approximately 06:00 h on 0 days of age, 20 days of age, 57 days of age, and 72 days of age, respectively. Rectal fecal samples were collected twice by rectal stimulation using sterile gloves at 15 days of age and 35 days of age, respectively. All samples were quickly placed at liquid nitrogen for temporary storage and then transferred − 80°C for long-term storage. Calf enrollment criteria The calves were diagnosed with diarrhea when showing the fecal score was ≥ 2. However, two calves were excluded in our study because of pneumonia. Since diarrhea was the only disease in calves in this study and its occurrence was a randomized event, we introduced an indicator to assess the health status of calves, which called calf health score (Y score). As shown in Fig. 1 , point C represented the sampling time, point A represented the day at which the calf had the last fecal score of 2 or 3 before the sampling time, and point B represented the day at which the calf had the first fecal score of 2 or 3 after the sampling time. The distance of point A to point B represented the duration of time that the calf kept healthy. The longer the distance of point A to point B, the less probability the calf suffered from diarrhea. Point D represented the midpoint of point A to point B. The closer the sampling time of the calf was to point A or point B, the more likely its physiological state at the time susceptible to diarrhea. When the sampling time was closer to point D, it indicated that the physiological state of the calf was relatively healthy. Thus, the distance of point C to point D represented the deviation of the current physiological state toward optimal health at the sampling time. In summary, the Y score is: Y = AB - CD. The details of Y score in all calves are shown in Supplementary Table S3. To investigate the difference in microbial community structure of calves with different health status, we grouped calves according to their Y scores. In general, a total of 36 calves were selected at 15 days of age, of which 18 calves with the highest or lowest Y scores were selected form all calves, and were named as HY15 and LY15 (Y score ≤ 12 vs Y score ≥ 18), respectively. Ten calves were not included in the groups (12.5 ≥ Y score ≤ 16.5). A total of 40 calves were selected at 35 days of age, of which 20 calves with the highest or lowest Y scores were selected form all calves, and were named as HY35 and LY35 (Y score ≤ 13.5 vs Y score ≥ 25), respectively. Six calves were not included in the groups (14.5 ≥ Y score ≤ 21.5). The inclusion/exclusion details in this study are shown in Supplementary Table S3. In addition, to investigate whether the frequency of fecal scores above 1 affects growth performance and feeding intake on starters, all calves except two calves with pneumonia were divided into three groups: Low (the frequency of fecal scores above 1 between 0–3, n = 18), Medium (the frequency of fecal scores above 1 between 4–6, n = 15), and High (the frequency of fecal scores above 1 between 7–11, n = 13). Measurement of Short chain fatty acids (SCFA) in rectal content The determination of SCFA in rectal content samples was conducted as previously by Li et al. [ 19 ]. In brief, the fecal samples were thawed at 4°C, diluted with water, and centrifuged at 135,000 rpm/min for 10 min at 4°C. Two mL of supernatant were mixed with 400 µL of 25% metaphosphoric acid solution and let stand at 5°C for 3–4 h. Later, centrifugation at 135000 rpm/min, 4°C for 15 min was performed to precipitate proteins. One mL of supernatant was mixed with 200 µL of 0.01% crotonic acid solution. All liquids were filtered with a 0.45 µm organic filter and stored at -20°C for subsequent testing. The analysis was performed with an Agilent 7820A gas chromatographic detection system under the following conditions: FID detector and AE-FFAP capillary column (30 m × 0.25 mm × 0.33 µm), injector 200°C, detector 250°C, the oven temperature program was increased from 45°C to 150°C at 20°C/min for 5 min. 16S rRNA gene sequencing and bioinformatics analysis The rectal fecal samples were thawed at 4°C, and the microbial genomic DNA was extracted by the CTAB method [ 20 ]. The V3 - V4 region of the bacterial 16S rRNA gene was amplified by PCR using the diluted genomic DNA as a template, using specific primers 338F (5′-ACTCCTRCGGGAGGCAGCAG‐3′) and 806R (5′‐GGACTACCVGGGTATCTAAT‐3′) with Barcodes [ 21 ]. The PCR products were analyzed using 2% agarose gel electrophoresis and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences Inc., Union City, CA, USA). And they were quantified with QuantiFluor™ ‐ST (Promega Inc., Madison, WI, USA) following the manufacturer's instructions. Library construction was prepared using the TruSeq DNA sample preparation Kit (Illumina Inc., San Diego, CA, USA). The purified amplicons were pooled in equimolar concentrations and paired‐end sequenced on Illumina MiSeq platform according to standard protocols [ 22 ]. Quality filtering on raw tags was performed using specific filtering conditions to obtain high-quality clean tags with QIIME software (V1.9.1) [ 23 ]. All effective tag sequences were classified into operational taxonomic units (OTUs) at an identity threshold of 97% similarity using UPARSE software [ 24 ]. Community richness and diversity were estimated using the Observed species, Ace, Chao 1, Shannon, and Simpson indices. The bray curtis method was performed for principal coordinate analysis (PCoA) and ANOMIS analysis. Construction of microbial co-occurrence networks To investigate the bacterial-bacterial interactions of rectal bacterial community in calves, the microbial co-occurrence networks were constructed using pairwise Spearman's rank correlations based on the relative abundance of bacteria at the genus level. To construct the microbial co-occurrence networks in HY15, LY15, HY35, and HY35 groups, the filter conditions are set as follows: (1) remove connections with correlation coefficient < |0.4|, (2) filter out node with a relative abundance < 0.005%. The network structure was visualized using Cytoscape v3.7.1. Identification of diarrhea related-bacteria by random forest regression analysis Random forest regression analysis was performed using the Random Forest Package according to Zhang et al. [ 25 ]. The documented R code used for this analysis is available in the supplementary material. Briefly, the genera with abundance greater than 0.1% and present in more than half of all samples were included in our analysis. We regressed the relative abundance of these genera against Y score, to acquire most diarrhea-related bacteria at 15 days of age and 35 days of age, respectively. The number of marker taxa were identified using 10-fold cross-validation implemented with the rfcv() function in the R package “randomForest” with five repeats. Statistical analysis The diarrhea rate was calculated according to the formula: Diarrhea rate (%) = sum of calves that had fecal scores above 1 per day / (total number of calves × examined days) × 100 [ 26 ]. Body weight, average daily gain and DMI of starters among Low, Medium, and High groups were analyzed using one-way analysis of variance test. Chi-square test was used to analyze whether there is a difference in the number of positive and negative correlations in the microbial co-occurrence networks. All correlation analyses were performed using Spearman's rank correlation, with coefficient > |0.2|, and a P value < 0.05 was considered significant. All data are expressed as the means ± SE. Differences were statistically significant at P < 0.05. Result Occurrence of diarrhea in calves In present study, calf diarrhea mainly occurred between 10 to 45 days of age and 60 to 72 days of age (pre- and post-weaning) (Fig. 2 ). The diarrhea rate of calves from 0 to 20 days of age (before the replacement of milk replacer), from 21 to 45 days of age (between milk replacer replacement and 45 days of age), and during the whole period was 4.79%, 10.68% and 6.22%, respectively (Table 1 ). We further investigated whether the frequency of fecal scores above 1 affects growth performance and feeding intake on starters of calves, but no differences were found among the Low, Medium, and High groups (Table 2 , P > 0.05). Thus, we have grouped calves with different health status according to their Y scores at 15 days of age and 35 days of age, respectively. As shown in Fig. 3 , a significantly higher frequency of diarrhea in the week before and the week after the sampling time was found in low-health-status calves in both 15 days of age and 35 days of age. In the following research, we try to analyze the diarrhea-related bacteria at 15 days of age and 35 days of age, respectively. Table 1 ༎Calf diarrhea rate in different phase (days of age) Phase 0–20 21–45 57–72 0–72 Diarrhea rate (%) 4.79 10.68 5.97 6.22 Table 2 ༎The growth performance and feeding intake on starters of calves among the Low, Medium, and High groups 1 Low Medium High SE P value Body weight, Kg 0 d 39.47 39.70 39.73 0.32 0.94 20 d 55.37 56.59 55.02 0.48 0.39 57 d 85.56 84.31 82.42 0.78 0.27 72 d 93.05 93.67 90.51 0.91 0.37 Average daily gain, Kg/d 0–20 d 0.79 0.84 0.76 0.02 0.41 21–57 d 0.82 0.75 0.74 0.02 0.11 58–72 d 0.50 0.59 0.54 0.04 0.65 DMI of starters, g/d 0–20 d 18.82 19.80 17.67 2.18 0.93 21–57 d 82.20 73.17 80.16 4.90 0.74 58–72 d 692.44 703.94 621.84 33.01 0.59 1 Low: the frequency of fecal scores above 1 between 0–3, n = 18; Medium: the frequency of fecal scores above 1 between 4–6, n = 15; High: the frequency of fecal scores above 1 between 7–11, n = 13. Difference in rectal microbial fermentation of calves with different health status Compared to HY15, the molar proportion of acetate was increased, but the molar proportion of butyrate was decreased in LY15 (Table 3 , P < 0.05). We also found that the concentration of butyrate showed a decreasing trend in LY15 (Table 3 , P = 0.07). Compared to HY35, the molar proportion of butyrate was decreased in LY35 (Table 4 , P < 0.05). Table 3 SCFA in feces of 15-day-old calves Item Group P value HY15 LY15 Concentration (mmol/Kg) Acetate 35.02 ± 4.21 32.53 ± 3.93 0.68 Propionate 12.37 ± 2.18 8.51 ± 1.24 0.16 Isobutyrate 1.42 ± 0.36 0.90 ± 0.23 0.26 Butyrate 22.71 ± 2.89 14.66 ± 2.88 0.07 Isovalerate 1.42 ± 0.49 0.75 ± 0.24 0.26 Valerate 0.76 ± 0.26 0.43 ± 0.19 0.34 Total SCFA 73.70 ± 8.91 57.77 ± 7.62 0.21 Molar proportion (%) Acetate 0.50 ± 0.03 0.58 ± 0.02 0.02 Propionate 0.16 ± 0.02 0.15 ± 0.01 0.67 Isobutyrate 0.02 ± 0.00 0.02 ± 0.01 0.92 Butyrate 0.30 ± 0.02 0.24 ± 0.02 0.02 Isovalerate 0.01 ± 0.00 0.01 ± 0.00 0.38 Valerate 0.01 ± 0.00 0.00 ± 0.00 0.35 A:P 4.32 ± 0.83 4.47 ± 0.49 0.89 SCFA = short chain fatty acids; The data are expressed as the means ± SE. Table 4 SCFA in feces of 35-day-old calves Item Group P value HY35 LY35 Concentration (mmol/Kg) Acetate 38.73 ± 2.65 42.22 ± 3.40 0.48 Propionate 10.90 ± 0.91 11.36 ± 1.18 0.79 Isobutyrate 1.26 ± 0.22 1.73 ± 0.27 0.25 Butyrate 11.84 ± 1.27 9.88 ± 1.01 0.29 Isovalerate 1.60 ± 0.26 1.90 ± 0.29 0.50 Valerate 0.85 ± 0.22 0.72 ± 0.23 0.73 Total SCFA 65.17 ± 3.81 67.81 ± 5.78 0.74 Molar proportion (%) Acetate 0.60 ± 0.02 0.64 ± 0.01 0.14 Propionate 0.17 ± 0.01 0.16 ± 0.01 0.80 Isobutyrate 0.02 ± 0.00 0.02 ± 0.00 0.49 Butyrate 0.18 ± 0.01 0.14 ± 0.00 0.02 Isovalerate 0.03 ± 0.00 0.03 ± 0.00 0.96 Valerate 0.01 ± 0.00 0.01 ± 0.00 0.52 A:P 3.87 ± 0.29 4.16 ± 0.30 0.53 SCFA = short chain fatty acids; The data are expressed as the means ± SE. Difference in microbial community structure of calves with different health status PCoA analysis based on bray curtis distance showed that there were significant differences in microbial community structure between 15-day-old calves and 35-day-old calves (Fig. 4 A, P < 0.01). The differential microbiota composition between 15-day-old calves and 35-day-old calves is shown in Fig. 5 A. Compared to 15-day-old calves, some fiber-degrading bacteria (such as Bacteroidaceae and Prevotellaceae) as well as Bifidobacterium were enriched in 35-day-old calves, while some cumulative anaerobic bacteria (such as Escherichia Shigella and Lactobacillaceae) were decreased in 35-day-old calves. We further found that microbial community structures were different between HY15 and LY15, and between HY35 and LY35 (Fig. 4 B and 4 C, P < 0.01). Compared to HY15, the Butyricicoccaceae ( Butyricicoccus ) as well as Clostridium perfringens were enriched, but Bifidobacterium , Streptococcus , and Peptostreptococcus were decreased in LY15 (Fig. 5 B). Compared to HY35, the Butyricicoccaceae and Clostridiaceae (such as Clostridium sensu stricto 1 and Clostridium perfringens ) were enriched in LY35, which was similar with 15-day-old calves (Fig. 5 C). However, we found that some member in Prevotellaceae (such as Prevotellaceae bacterium and Prevotella ) were especially decreased in LY35 (Fig. 5 C). The results above may imply that the structure of calf gut microbial community is perturbed by the onset of diarrhea, and the diarrhea-associated microbes are different at the two ages due to structural differences in the gut microbes at 15 days of age and 35 days of age. Microbial co-occurrence networks of rectal microbiota of calves at genus level To further explore the potential ecological roles of the keystone genera in calves with different health status, we performed microbial network analysis to depict the interactions among predominant genera (relative abundance > 0.005%, present in more than 50% of samples) in HY15, LY15, HY35, and LY35 groups, respectively. As shown in Fig. 6 , the four microbial networks were dominated by genera of Firmicutes . Compared to calves at the same age, the microbial networks in calves with low health status were found to have more negative correlations and less positive correlations, with negative/positive correlations in HY15, LY15, HY35, and LY35 groups was 36/152, 80/114, 22/93 and 52/89, respectively (Supplementary Table S4, Chi-square test, P < 0.01). Some opportunistic pathogens, primarily Escherichia Shigella , increased their participation in the entire networks of calves with low health status, especially at 35 days of age (Fig. 6 C and 6 D). The degree (the number of associations to other bacteria) of Escherichia Shigella in the HY15, LY15, HY35, and LY35 groups were 11, 14, 2, and 10, respectively (Supplementary Table S5). Some bacterial genera like Clostridium_sensu_stricto_1 , and Butyricicoccus had strong positive correlations with Escherichia Shigella , while others like Phascolarctobacterium , Faecalibacterium , UCG-005 , and Prevotella-9 were negatively correlated with it ( r > 0.6, P < 0.05, Fig. 6 ). Identification of diarrhea-associated bacteria in rectal microbiota of calves using random forest algorithm To further identify potential diarrhea-associated bacteria at different ages, we regressed the relative abundance of rectal bacteria at genus level against Y score using a random forest algorithm model. According to the cross-validation error curves, the TOP 10 and TOP 22 genera in 15-day-old calves and 35-day-old calves were chosen for further study, respectively (Supplementary Figure S1 and S2). The lists of top 10 and 22 bacterial taxa in 15-day-old calves and 35-day-old calves, in order of time-discriminatory importance, were shown in Fig. 7 A and 7 C, respectively. We further constructed the co-occurrence network of these genera with Y score to explore the interactions among them. Among the TOP 10 genera at 15-day old calves, four genera, including Bifidobacterium , Peptostreptococcus , Erysipelotrichaceae_UCG-003 , and Mogibacterium , were positively correlated with calf health scores (Fig. 7 B, P < 0.05). Meanwhile, these genera mentioned above were found to be positively correlated with each other. On the contrary, Lachnospiraceae_UCG-004 was positively correlated with Butyricicoccus , and the former had negative correlations with two genera that were positively correlated with the Y score, including Peptostreptococcus and Mogibacterium (Fig. 7 B, P < 0.05). In 35-day-old calves, five genera, including Prevotella_9 , Megasphaera , Sellimonas , Succinivibrio , and Acidaminococcus , had positive correlations with Y score, and there were seven genera, such as Citrobacter , Butyricicoccus , Roseburia , Subdoligranulum , Clostridium_sensu_stricto_1 , and UCG-005 , were negatively correlated with Y score (Fig. 7 D, P < 0.05). Moreover, the genera that were positively correlated with the Y score had positive correlations with each other, and the genera that were negatively correlated with the Y score were also positively correlated with each other. In contrast, the formers had negative correlations with the latter (Fig. 7 D, P < 0.05). Correlation analysis of diarrhea-associated bacteria with rectal SCFA To further explore the role of these diarrhea-associated microorganisms in rectal fermentation of calves, we performed a correlation analysis. As shown in Fig. 8 A, Erysipelotrichaceae_UCG-003 and Mogibacterium had positive correlations with the molar proportion of acetate, but they had negative correlations with the concentration and molar proportion of butyrate in 15-day-old calves ( P < 0.05). Moreover, Lachnospiraceae_UCG-004 was negatively correlated with the concentration and molar proportion of valerate in 15-day-old calves ( P < 0.05). As shown in Fig. 8 B, Megasphaera and Ligilactobacillus had positive correlations with the concentrations with acetate, butyrate and total SCFA in 35-day-old calves ( P < 0.05). However, Citrobacter had negative correlation with the molar proportion of butyrate in 35-day-old calves ( P < 0.05). Discussion Trillions of microbes colonize in gastrointestinal tract and keep a delicate balance in a symbiotic relationship with the host [ 27 ]. In our study, we found that the gut microbial structure of calves changed greatly with their health status and age. At 15 days of age, Bifidobacterium , Streptococcus and their corresponding families were increased, while Butyricicoccus and Clostridium perfringens were decreased in calves with high health status. Bifidobacterium is an important taxon in early life, being one of the most abundant genera in the infant intestinal microbiota and carrying out important functions for maintaining host-homeostasis [ 28 – 30 ]. Streptococcus is generally regarded as lactic acid bacteria, and some strains such as S. infantarius and S. faecalis exhibited anti- Salmonella activities [ 31 , 32 ]. It's worth noting that Ma et at. [ 2 ] have reported that Streptococcus was key microbial markers that can differentiate “healthy” and “diarrheic” gut microbiota and it was enriched in healthy calves. Although Butyricicoccus is a butyrate producer, some studies reported that it positively correlated with host inflammatory responses and enriched in calf diarrhea caused by Clostridioides difficile [ 33 , 34 ]. At 35 days of age, we found that two Prevotellaceae members were increased, while Butyricicoccaceae and Clostridiaceae were decreased in calves with high health status. Members of Prevotellaceae generally have broad repertoires of polysaccharide utilization loci and carbohydrate active enzymes targeting various plant polysaccharides, which could contribute to high fiber utilization and powerful SCFA production in hindgut [ 35 , 36 ]. The members of Clostridiaceae contain many diarrhea-causing bacteria, such as Clostridioides difficile and Clostridium perfringens . Additionally, we found that a genus, which was called Clostridium_sensu_stricto_1 , was enriched in calves with low health status. Wang et al. [ 37 ] found that Clostridium_sensu_stricto_1 was elevated in the gut of lambs with diarrhea. Sun et al. [ 38 ] also found that Clostridium_sensu_stricto_1 was reduced in the process of relieving diarrhea in weaned piglets treated by coated zinc oxide. Using random forest algorithm, we obtained similar results that mentioned above. Among the TOP 10 and TOP 22 diarrhea-related genera chosen based on health score in 15-day old calves and 35-day old calves, respectively, the Bifidobacterium , Streptococcus , Butyricicoccus , and Clostridium_sensu_stricto_1 , were included. Interestingly, the Butyricicoccus was identified as diarrhea-related genera at both 15 days of age and 35 days of age, which may indicate that it plays a crucial role in calf diarrhea. Besides, some additional genera that have been ignored in our differential analysis seem to be extremely important. For example, Erysipelotrichaceae_UCG-003 , which correlated with health score positively, was far more important than other bacteria in 15 days of age. Some studies suggested that Erysipelotrichaceae was beneficial to improve gut homeostasis, and its genus Erysipelotrichaceae_UCG-003 was enriched in healthy aging cohort than non-healthy aging cohort [ 39 – 41 ]. At 35 days of age, Sellimonas may be a potential biomarker for the restoration of intestinal homeostasis, and its abundance is low in patients with intestinal dysbiosis [ 42 ]. The microbial co-occurrence networks further revealed that there was apparent co-exclusion exists between genera that positively correlated with health score and genera that negatively correlated with it. Although no genera that negatively correlated with health score were detected at 15 days of age, we found that some genera showed exclusions with Butyricicoccus and Lachnospiraceae_UCG_004 . The Citrobacter and Clostridium_sensu_stricto_1 were the two of predominant genera that correlated with health scores negatively at 35 days of age, and both have been reported to be closely related to diarrhea. Citrobacter was commonly defined as pathogens and can induce diarrhea and enteritis [ 43 ]. In addition to the co-occurrence network constructed among diarrhea-associated bacteria, we also delineated the overall interaction pattern of these bacteria with other bacteria in HY15, LY15, HY35, and HY35 group, respectively. The results showed that those “bad” bacteria mentioned above, including Butyricicoccus and Clostridium_sensu_stricto_1 , were likely to cooperate with Escherichia Shigella and negatively correlated with other “good” bacteria. There are various ecological relationships exist in gut microbial communities, ranging from cooperation to competition, while two taxa with similar niches tend to exclude each other for limited food and living space [ 44 ]. Overall, our study highlighted the changed microbial interaction patterns between diarrheic calves and healthy calves, which may shape different microbial function. We also emphasized that although the diarrhea-related bacteria of calves will vary at different ages, the changed genera can fill the gap in the ecological niche, against the same pathogenic bacteria, and ensure the health of calve. Promoting a successful transition of the main members of gut microbiota from cumulative anaerobic bacteria (such as Lactobacillaceae) to fiber-degrading bacteria (such as Prevotellaceae) in early calf rearing may benefit calves to better cope with diarrhea challenges. Nevertheless, future studies to investigate the active microbial functions and taxa using culture-based technologies are required to confirm the function of these diarrhea-related bacteria in deeper mechanistic level. Conclusion In summary, significant difference of gut microbial structure existed between high-health-status calves and low-health-status calves, and some specific bacteria, which we referred as diarrhea-related bacteria, changed in their roles on diarrhea with calf ages. Moreover, the interaction patterns of gut microbiota also show great variation in diarrhea status and calf ages. Our study provides new insights into developing novel prevention and treatment strategies in calf diarrhea by targeted microbial intervention. Declarations Ethics approval The use of the animals and the experimental procedure were approved by the Animal Care Committee and Use Committee of the Northwest A&F University (protocol number: NWAFAC1008). Availability of data and materials The raw sequence data can be found in the NCBI repository in BioProject: PRJNA744001. Author contributions Guangfu Tang: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing. Xi Wang: Formal analysis, Software, Validation, Visualization, Writing – original draft. Minghui Cui: Investigation, Methodology, Resources, Validation. Gehan Ren: Investigation, Methodology, Validation, Visualization. Fang Yan: Writing – review & editing. Shunshan Wang: Software, Validation. Junhu Yao: Methodology, Supervision. Xiurong Xu: Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing. Declaration of interest None. Acknowledgements None. Financial support statement This study was funded by the Key Science and Technology Program of Shaanxi Province (No.2022NY-088). References McGuirk SM. 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Gut microbiota features associated with Clostridioides difficile colonization in dairy calves. PLoS One. 2021;16(12):e0251999. Accetto T, Avguštin G. The diverse and extensive plant polysaccharide degradative apparatuses of the rumen and hindgut Prevotella species: A factor in their ubiquity?. Syst Appl Microbiol. 2019;42(2):107-116. Fehlner-Peach H, Magnabosco C, Raghavan V, Scher JU, Tett A, Cox LM, et al. Distinct Polysaccharide Utilization Profiles of Human Intestinal Prevotella copri Isolates. Cell Host Microbe. 2019;26(5):680-690.e5. Wang Y, Zhang H, Zhu L, Xu Y, Liu N, Sun X, et al. Dynamic Distribution of Gut Microbiota in Goats at Different Ages and Health States. Front Microbiol. 2018;9:2509. Sun Y, Ma N, Qi Z, Han M, Ma X. Coated Zinc Oxide Improves Growth Performance of Weaned Piglets via Gut Microbiota. Front Nutr. 2022;9:819722. Singh H, Torralba MG, Moncera KJ, DiLello L, Petrini J, Nelson KE, et al. Gastro-intestinal and oral microbiome signatures associated with healthy aging. Geroscience. 2019;41(6):907-921. Videvall E, Song SJ, Bensch HM, Strandh M, Engelbrecht A, Serfontein N, et al. Early-life gut dysbiosis linked to juvenile mortality in ostriches. Microbiome. 2020;8(1):147. Wang H, Wang G, Banerjee N, Liang Y, Du X, Boor PJ, et al. Aberrant Gut Microbiome Contributes to Intestinal Oxidative Stress, Barrier Dysfunction, Inflammation and Systemic Autoimmune Responses in MRL/lpr Mice. Front Immunol. 2021;12:651191. Muñoz M, Guerrero-Araya E, Cortés-Tapia C, Plaza-Garrido A, Lawley TD, Paredes-Sabja D. Comprehensive genome analyses of Sellimonas intestinalis, a potential biomarker of homeostasis gut recovery. Microb Genom. 2020;6(12):mgen000476. An J, Zhao X, Wang Y, Noriega J, Gewirtz AT, Zou J. Western-style diet impedes colonization and clearance of Citrobacter rodentium. PLoS Pathog. 2021;17(4):e1009497. Faust K, Raes J. Microbial interactions: from networks to models. Nat Rev Microbiol. 2012;10(8):538-550. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3411867","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":237983298,"identity":"6e82b97b-7daa-452e-a67b-227a04eb78c5","order_by":0,"name":"Guangfu Tang","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Guangfu","middleName":"","lastName":"Tang","suffix":""},{"id":237983299,"identity":"32a1a62f-b943-42ec-9767-be2bc2e0cad8","order_by":1,"name":"Xi Wang","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Wang","suffix":""},{"id":237983300,"identity":"45d92d7a-0be4-4746-a797-0a5578d2e551","order_by":2,"name":"Minghui Cui","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minghui","middleName":"","lastName":"Cui","suffix":""},{"id":237983301,"identity":"71cbb1d8-92c7-4ef9-85ea-7a39a7702528","order_by":3,"name":"Gehan Ren","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gehan","middleName":"","lastName":"Ren","suffix":""},{"id":237983302,"identity":"7898629d-a0c0-45ec-8e55-2903422f8e16","order_by":4,"name":"Fang Yan","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Yan","suffix":""},{"id":237983303,"identity":"6c070ba1-1d05-40df-9e9a-374f0ecdf29f","order_by":5,"name":"Shunshan Wang","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shunshan","middleName":"","lastName":"Wang","suffix":""},{"id":237983304,"identity":"2bc2ae2e-1011-4c48-80dc-26d7ce07e769","order_by":6,"name":"Junhu Yao","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junhu","middleName":"","lastName":"Yao","suffix":""},{"id":237983305,"identity":"06ffa60a-aeaf-45a0-a90e-b92cdf66f60c","order_by":7,"name":"Xiurong Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYJCCA2CSvQFI2IBYCcRq4QFRaURqgQCJBCK1GNzIMTzMu8cmTz7y7TGJHwmHGfjZcwwYfu7ArUVyRlrCYZ5nacWGt/PSJHuAWiR73hgw9p7BrYVfIvnAYZ4DhxM3zs4xu8H74zDIXgNmxjbcWtgkEhsgWmaeMbv5B2iLPSEtcFvmS/CY3eYBajGQIKBFsudZwsE5B9ISN/DkmP+WSUjnkTjzrOBgLx4tBsdzjD+8OWCTOL/9jLHhmwRrOf725I0PfuLRgtB7AELzgIgDRGhgYJBvIErZKBgFo2AUjEQAALoPVIYiYR5gAAAAAElFTkSuQmCC","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiurong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2023-10-05 02:29:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3411867/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3411867/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":44381166,"identity":"b8ebb954-10dd-4b66-8980-78b1cdc6abd3","added_by":"auto","created_at":"2023-10-10 18:26:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":785787,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of calf healthy score\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/44444945b561ac8c69c56787.png"},{"id":44382726,"identity":"99256de5-a359-458f-99f4-0012b9d395ad","added_by":"auto","created_at":"2023-10-10 18:34:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":962104,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of fecal consistency scores from birth to 73 days of age. A fecal consistency score of 0 indicates that the feces are normal (firm but not hard); 1 indicates semi-formed soft feces; 2 indicates that the feces are runny and spread easily; and 3 indicates that the fecal matter was watery (devoid of solid matter).\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/b7f0c6c4b520b0eef3811c21.png"},{"id":44381163,"identity":"5c6a3ba1-bf1a-427d-8e72-46803dd52c8c","added_by":"auto","created_at":"2023-10-10 18:26:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":900968,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing frequency of diarrhea in 15-day-old calves (A) and 35-day-old calves (B) in the week before and after the sampling time. The pink square indicated that the fecal score was ≥ 2.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/4164e28fc18ff61cfd14e7d4.png"},{"id":44381162,"identity":"f84d7579-3678-41dc-b979-c6c6dd59e66d","added_by":"auto","created_at":"2023-10-10 18:26:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":565020,"visible":true,"origin":"","legend":"\u003cp\u003eThe β diversity of calf rectal microbiota between 15-day-old calves and 35-day-old calves (A), and between calves with different health status at 15 days (B) and 35 days (C) of age. PCoA analyses were based on bray curtis distance.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/c5ec402dc852a71301f511f4.png"},{"id":44381167,"identity":"589d794c-bac6-4fba-86b7-2a14b9c5862b","added_by":"auto","created_at":"2023-10-10 18:26:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":707757,"visible":true,"origin":"","legend":"\u003cp\u003eDifference in the bacterial abundance of rectal microbiota between 15-day-old calves and 35-day-old calves (A), and between calves with different health status at 15 days (B) and 35 days (C) of age.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/99ef3c90d44b84eaef178386.png"},{"id":44381172,"identity":"ede38db1-8cd4-4d1d-b25c-a858114183c0","added_by":"auto","created_at":"2023-10-10 18:26:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":18992226,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence network at the genus level of calf fecal microbiota in HY15 (A), LY15 (B), HY35 (C), and LY35 (D) groups. The red lines represent the positive association, and blue lines represent negative associations. The thickness of lines represents strength of relatedness. The size of nodes indicates the relative abundance of genera. The colors of nodes indicate the phyla to which the genera belong. Data were analyzed using Spearman’s correlation, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, |\u003cem\u003er\u003c/em\u003e| \u0026gt; 0.4.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/c02faef5d6d70f366e511b0f.png"},{"id":44382727,"identity":"fe8a9d06-d334-4c58-b7dd-70343cca2c52","added_by":"auto","created_at":"2023-10-10 18:34:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":462444,"visible":true,"origin":"","legend":"\u003cp\u003ePredicting calf diarrhea-associated microbiota using random forest models. A: The TOP 10 genera related to calf diarrhea at 15 days of age. B: The TOP 22 genera related to calf diarrhea at 35 days of age. C: The co-occurrence network of the TOP 10 genera. D: The co-occurrence network of the TOP 22 genera. In co-occurrence networks, the red lines represent the positive association, and blue lines represent negative associations. The thickness of lines represents strength of relatedness. The size of nodes indicates the relative abundance of genera. The colors of nodes indicate the phyla to which the genera belong. Data were analyzed using Spearman's correlation, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, |\u003cem\u003er\u003c/em\u003e| \u0026gt; 0.2.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/732880a5d5177202e5c3afdf.png"},{"id":44383641,"identity":"5440e6d9-8cc3-464b-b95a-9729a9a7e225","added_by":"auto","created_at":"2023-10-10 18:42:34","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":877365,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of rectal microbiota with short chain fatty acid in 15-day-old calves (A) and 35-day-old calves (B). Data were analyzed using Spearman’s correlation, * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Fig.8.png","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/74fb983998624213efdc2255.png"},{"id":44678228,"identity":"06b888df-b8c9-4a72-bd82-a94b61361ccc","added_by":"auto","created_at":"2023-10-16 08:52:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2833625,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/8077b286-c7a6-443a-b7bd-95d688c9495e.pdf"},{"id":44381164,"identity":"40a79675-981d-4661-86d1-0238697c9515","added_by":"auto","created_at":"2023-10-10 18:26:34","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":155714,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3411867/v1/f59ddcdbeb0e4656685fad75.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The characteristics of diarrhea-related bacteria in suckling calves and their dynamic succession with ages","fulltext":[{"header":"Background","content":"\u003cp\u003eDiarrhea is a common disease on dairy farm, which has an extremely high incidence in suckling calves, seriously threatens the health of calves, and negatively affects their subsequent production performance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although diarrhea can be caused by various factors, such as pathogen infections, environmental conditions, nutritional management and immune functions, the disturbance of the gut bacterial community is often tightly associated with diarrhea. It has been reported that compared to healthy calves, the calves with diarrhea experienced a fluctuation in microbial diversity and had a \"delayed\" gut microbiota in their early life [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Through a random forest algorithm, Ma et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] found that \u003cem\u003eTrueperella\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eDorea\u003c/em\u003e, \u003cem\u003euncultured Lachnospiraceae\u003c/em\u003e, \u003cem\u003eRuminococcus 2\u003c/em\u003e, and \u003cem\u003eErysipelatoclostridium\u003c/em\u003e could be used to predict calf diarrhea with an accuracy rate of 84.3%. Furthermore, calf diarrhea can be prevented and treated by microbial intervention and modulation. Previous studies have demonstrated that probiotic supplementation can reduce the incidence of diarrhea and improve growth performance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Kim et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and Islam et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] recently performed intriguing trials in which they found fecal microbiota transplantation can ameliorate diarrhea in pre-weaning calves. Nonetheless, our knowledge on which specific taxa are the most diarrhea-related bacteria and how these diarrhea-related bacteria contribute to diarrhea status in calves is still limited.\u003c/p\u003e \u003cp\u003ePrevious studies have proved that the gut microbiota, especially early-life gut microbiota, play important roles on host health by providing nutrients, regulating immune system and promoting tissue maturation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The gut microbial communities of calves are highly variable from birth to weaning, and their ecological succession begins with a diverse group of pioneer species [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Several studies have compared the difference in bacterial microbiota between diarrheic and non-diarrheic dairy calves; however, most have not distinguished the changes in calf diarrhea at different days of age [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recently, Chen et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] had reported that the dynamic successions of calf gut microbiota and the interactions among some bacteria could influence calf diarrhea. Thus, we hypothesize that the diarrhea-related bacteria of calves will vary at different days of age. The targeted prevention and treatment based on different age status may be more helpful for calves to cope with diarrhea challenges.\u003c/p\u003e \u003cp\u003eThe most critical period of dairy calves rearing is the first month of life, due to the high risk of disease and mortality occurrence [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Similarly, some reports indicated that the diarrhea in calves is mainly occurs within one month of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Therefore, the present study analyzed the bacterial community characteristics of calves in a modern dairy farm. Random forest analysis and microbial co-occurrence network were used to screen the key diarrhea-related bacteria and to deconstruct their ecological relationships in calf diarrhea at 15 days of age and 35 days of age, respectively. Our findings will provide new insight for further understanding of known or other potential bacteria related to calf diarrhea, which may contribute to the treatment and prevention of diarrhea in the calf industry.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperiment animals and sampling\u003c/h2\u003e \u003cp\u003eThe experiment was carried out at a local farm in Baoji, Shaanxi (34\u0026deg;41\u0026prime;N,109\u0026deg;09\u0026prime;E). Forty-eight new-born calves with similar body weights (39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 Kg, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE) were selected. Immediately after birth, each calf was separated from the cow and housed in the newborn calf barn for individual feeding, with 4 L of colostrum given within 1 hour and another 2 L of colostrum given within 8\u0026ndash;10 h. All colostrum, milk, and milk replacer were pasteurized. The calves were transferred to independent calf hutches on the second day of life and were fed twice daily at 07:30 and 14:00 h, with free access to water and starter. The replacement of milk to milk replacer occurred at 20 days of age, and this transition was completed within three days. The weaning of all calves began at 57 days of age and ended at 63 days of age. The composition and nutritional level of calf starter and milk replacer are shown in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The daily feeding amount was adjusted according to the age of calves, and the feeding regime is shown in the Supplementary Table S2.\u003c/p\u003e \u003cp\u003eFecal consistency scores were recorded daily from 0 days of age to 72 days of age, using a scoring standard (0\u0026thinsp;=\u0026thinsp;normal, firm stool; 1\u0026thinsp;=\u0026thinsp;soft, semi-solid; 2\u0026thinsp;=\u0026thinsp;runny, spreads easily; 3\u0026thinsp;=\u0026thinsp;watery, devoid of solid matter), as described in previous method [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The initial and remaining amounts of starters were weighed daily from 0 days of age to 72 days of age. Starter samples were dried in a 105\u0026deg;C for 8 h to obtain dry matter (DM) content. Daily dry matter intake (DMI) per calf was calculated by multiplying daily as-fed intake by DM content of starter. Body weights were recorded before the morning feeding, starting at approximately 06:00 h on 0 days of age, 20 days of age, 57 days of age, and 72 days of age, respectively. Rectal fecal samples were collected twice by rectal stimulation using sterile gloves at 15 days of age and 35 days of age, respectively. All samples were quickly placed at liquid nitrogen for temporary storage and then transferred \u0026minus;\u0026thinsp;80\u0026deg;C for long-term storage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCalf enrollment criteria\u003c/h2\u003e \u003cp\u003eThe calves were diagnosed with diarrhea when showing the fecal score was \u0026ge;\u0026thinsp;2. However, two calves were excluded in our study because of pneumonia. Since diarrhea was the only disease in calves in this study and its occurrence was a randomized event, we introduced an indicator to assess the health status of calves, which called calf health score (Y score). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, point C represented the sampling time, point A represented the day at which the calf had the last fecal score of 2 or 3 before the sampling time, and point B represented the day at which the calf had the first fecal score of 2 or 3 after the sampling time. The distance of point A to point B represented the duration of time that the calf kept healthy. The longer the distance of point A to point B, the less probability the calf suffered from diarrhea. Point D represented the midpoint of point A to point B. The closer the sampling time of the calf was to point A or point B, the more likely its physiological state at the time susceptible to diarrhea. When the sampling time was closer to point D, it indicated that the physiological state of the calf was relatively healthy. Thus, the distance of point C to point D represented the deviation of the current physiological state toward optimal health at the sampling time. In summary, the Y score is: Y\u0026thinsp;=\u0026thinsp;AB - CD. The details of Y score in all calves are shown in Supplementary Table S3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo investigate the difference in microbial community structure of calves with different health status, we grouped calves according to their Y scores. In general, a total of 36 calves were selected at 15 days of age, of which 18 calves with the highest or lowest Y scores were selected form all calves, and were named as \u003cb\u003eHY15\u003c/b\u003e and \u003cb\u003eLY15\u003c/b\u003e (Y score\u0026thinsp;\u0026le;\u0026thinsp;12 vs Y score\u0026thinsp;\u0026ge;\u0026thinsp;18), respectively. Ten calves were not included in the groups (12.5\u0026thinsp;\u0026ge;\u0026thinsp;Y score\u0026thinsp;\u0026le;\u0026thinsp;16.5). A total of 40 calves were selected at 35 days of age, of which 20 calves with the highest or lowest Y scores were selected form all calves, and were named as \u003cb\u003eHY35\u003c/b\u003e and \u003cb\u003eLY35\u003c/b\u003e (Y score\u0026thinsp;\u0026le;\u0026thinsp;13.5 vs Y score\u0026thinsp;\u0026ge;\u0026thinsp;25), respectively. Six calves were not included in the groups (14.5\u0026thinsp;\u0026ge;\u0026thinsp;Y score\u0026thinsp;\u0026le;\u0026thinsp;21.5). The inclusion/exclusion details in this study are shown in Supplementary Table S3.\u003c/p\u003e \u003cp\u003eIn addition, to investigate whether the frequency of fecal scores above 1 affects growth performance and feeding intake on starters, all calves except two calves with pneumonia were divided into three groups: \u003cb\u003eLow\u003c/b\u003e (the frequency of fecal scores above 1 between 0\u0026ndash;3, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18), \u003cb\u003eMedium\u003c/b\u003e (the frequency of fecal scores above 1 between 4\u0026ndash;6, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15), and \u003cb\u003eHigh\u003c/b\u003e (the frequency of fecal scores above 1 between 7\u0026ndash;11, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of Short chain fatty acids (SCFA) in rectal content\u003c/h2\u003e \u003cp\u003eThe determination of SCFA in rectal content samples was conducted as previously by Li et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In brief, the fecal samples were thawed at 4\u0026deg;C, diluted with water, and centrifuged at 135,000 rpm/min for 10 min at 4\u0026deg;C. Two mL of supernatant were mixed with 400 \u0026micro;L of 25% metaphosphoric acid solution and let stand at 5\u0026deg;C for 3\u0026ndash;4 h. Later, centrifugation at 135000 rpm/min, 4\u0026deg;C for 15 min was performed to precipitate proteins. One mL of supernatant was mixed with 200 \u0026micro;L of 0.01% crotonic acid solution. All liquids were filtered with a 0.45 \u0026micro;m organic filter and stored at -20\u0026deg;C for subsequent testing. The analysis was performed with an Agilent 7820A gas chromatographic detection system under the following conditions: FID detector and AE-FFAP capillary column (30 m \u0026times; 0.25 mm \u0026times; 0.33 \u0026micro;m), injector 200\u0026deg;C, detector 250\u0026deg;C, the oven temperature program was increased from 45\u0026deg;C to 150\u0026deg;C at 20\u0026deg;C/min for 5 min.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e16S rRNA gene sequencing and bioinformatics analysis\u003c/h2\u003e \u003cp\u003eThe rectal fecal samples were thawed at 4\u0026deg;C, and the microbial genomic DNA was extracted by the CTAB method [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The V3 - V4 region of the bacterial 16S rRNA gene was amplified by PCR using the diluted genomic DNA as a template, using specific primers 338F (5\u0026prime;-ACTCCTRCGGGAGGCAGCAG‐3\u0026prime;) and 806R (5\u0026prime;‐GGACTACCVGGGTATCTAAT‐3\u0026prime;) with Barcodes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The PCR products were analyzed using 2% agarose gel electrophoresis and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences Inc., Union City, CA, USA). And they were quantified with QuantiFluor\u0026trade; ‐ST (Promega Inc., Madison, WI, USA) following the manufacturer's instructions. Library construction was prepared using the TruSeq DNA sample preparation Kit (Illumina Inc., San Diego, CA, USA). The purified amplicons were pooled in equimolar concentrations and paired‐end sequenced on Illumina MiSeq platform according to standard protocols [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Quality filtering on raw tags was performed using specific filtering conditions to obtain high-quality clean tags with QIIME software (V1.9.1) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. All effective tag sequences were classified into operational taxonomic units (OTUs) at an identity threshold of 97% similarity using UPARSE software [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Community richness and diversity were estimated using the Observed species, Ace, Chao 1, Shannon, and Simpson indices. The bray curtis method was performed for principal coordinate analysis (PCoA) and ANOMIS analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of microbial co-occurrence networks\u003c/h2\u003e \u003cp\u003e To investigate the bacterial-bacterial interactions of rectal bacterial community in calves, the microbial co-occurrence networks were constructed using pairwise Spearman's rank correlations based on the relative abundance of bacteria at the genus level. To construct the microbial co-occurrence networks in HY15, LY15, HY35, and HY35 groups, the filter conditions are set as follows: (1) remove connections with correlation coefficient \u0026lt; |0.4|, (2) filter out node with a relative abundance\u0026thinsp;\u0026lt;\u0026thinsp;0.005%. The network structure was visualized using Cytoscape v3.7.1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of diarrhea related-bacteria by random forest regression analysis\u003c/h2\u003e \u003cp\u003eRandom forest regression analysis was performed using the Random Forest Package according to Zhang et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The documented \u003cem\u003eR\u003c/em\u003e code used for this analysis is available in the supplementary material. Briefly, the genera with abundance greater than 0.1% and present in more than half of all samples were included in our analysis. We regressed the relative abundance of these genera against Y score, to acquire most diarrhea-related bacteria at 15 days of age and 35 days of age, respectively. The number of marker taxa were identified using 10-fold cross-validation implemented with the rfcv() function in the R package \u0026ldquo;randomForest\u0026rdquo; with five repeats.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe diarrhea rate was calculated according to the formula: Diarrhea rate (%)\u0026thinsp;=\u0026thinsp;sum of calves that had fecal scores above 1 per day / (total number of calves \u0026times; examined days) \u0026times; 100 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Body weight, average daily gain and DMI of starters among Low, Medium, and High groups were analyzed using one-way analysis of variance test. Chi-square test was used to analyze whether there is a difference in the number of positive and negative correlations in the microbial co-occurrence networks. All correlation analyses were performed using Spearman's rank correlation, with coefficient \u0026gt; |0.2|, and a \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. All data are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SE. Differences were statistically significant at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOccurrence of diarrhea in calves\u003c/h2\u003e \u003cp\u003eIn present study, calf diarrhea mainly occurred between 10 to 45 days of age and 60 to 72 days of age (pre- and post-weaning) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The diarrhea rate of calves from 0 to 20 days of age (before the replacement of milk replacer), from 21 to 45 days of age (between milk replacer replacement and 45 days of age), and during the whole period was 4.79%, 10.68% and 6.22%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We further investigated whether the frequency of fecal scores above 1 affects growth performance and feeding intake on starters of calves, but no differences were found among the Low, Medium, and High groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Thus, we have grouped calves with different health status according to their Y scores at 15 days of age and 35 days of age, respectively. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, a significantly higher frequency of diarrhea in the week before and the week after the sampling time was found in low-health-status calves in both 15 days of age and 35 days of age. In the following research, we try to analyze the diarrhea-related bacteria at 15 days of age and 35 days of age, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e༎Calf diarrhea rate in different phase (days of age)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhase\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u0026ndash;45\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u0026ndash;72\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026ndash;72\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiarrhea rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e༎The growth performance and feeding intake on starters of calves among the Low, Medium, and High groups\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBody weight, Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e57 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e72 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAverage daily gain, Kg/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;20 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;57 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u0026ndash;72 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDMI of starters, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;20 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;57 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u0026ndash;72 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e692.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e703.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e621.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003eLow: the frequency of fecal scores above 1 between 0\u0026ndash;3, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18; Medium: the frequency of fecal scores above 1 between 4\u0026ndash;6, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15; High: the frequency of fecal scores above 1 between 7\u0026ndash;11, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDifference in rectal microbial fermentation of calves with different health status\u003c/h2\u003e \u003cp\u003eCompared to HY15, the molar proportion of acetate was increased, but the molar proportion of butyrate was decreased in LY15 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). We also found that the concentration of butyrate showed a decreasing trend in LY15 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, P\u0026thinsp;=\u0026thinsp;0.07). Compared to HY35, the molar proportion of butyrate was decreased in LY35 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSCFA in feces of 15-day-old calves\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHY15\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLY15\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eConcentration (mmol/Kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e35.02\u0026thinsp;\u0026plusmn;\u0026thinsp;4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePropionate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.37\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsobutyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.71\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsovalerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal SCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e73.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e57.77\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMolar proportion (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePropionate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsobutyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsovalerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA:P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSCFA\u0026thinsp;=\u0026thinsp;short chain fatty acids; The data are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SE.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSCFA in feces of 35-day-old calves\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHY35\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLY35\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eConcentration (mmol/Kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e38.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e42.22\u0026thinsp;\u0026plusmn;\u0026thinsp;3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePropionate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e10.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsobutyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsovalerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal SCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e65.17\u0026thinsp;\u0026plusmn;\u0026thinsp;3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.81\u0026thinsp;\u0026plusmn;\u0026thinsp;5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMolar proportion (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePropionate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsobutyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsovalerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA:P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSCFA\u0026thinsp;=\u0026thinsp;short chain fatty acids; The data are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SE.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDifference in microbial community structure of calves with different health status\u003c/h2\u003e \u003cp\u003ePCoA analysis based on bray curtis distance showed that there were significant differences in microbial community structure between 15-day-old calves and 35-day-old calves (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The differential microbiota composition between 15-day-old calves and 35-day-old calves is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. Compared to 15-day-old calves, some fiber-degrading bacteria (such as Bacteroidaceae and Prevotellaceae) as well as \u003cem\u003eBifidobacterium\u003c/em\u003e were enriched in 35-day-old calves, while some cumulative anaerobic bacteria (such as \u003cem\u003eEscherichia Shigella\u003c/em\u003e and Lactobacillaceae) were decreased in 35-day-old calves.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe further found that microbial community structures were different between HY15 and LY15, and between HY35 and LY35 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Compared to HY15, the Butyricicoccaceae (\u003cem\u003eButyricicoccus\u003c/em\u003e) as well as \u003cem\u003eClostridium perfringens\u003c/em\u003e were enriched, but \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003ePeptostreptococcus\u003c/em\u003e were decreased in LY15 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Compared to HY35, the Butyricicoccaceae and Clostridiaceae (such as \u003cem\u003eClostridium sensu stricto 1\u003c/em\u003e and \u003cem\u003eClostridium perfringens\u003c/em\u003e) were enriched in LY35, which was similar with 15-day-old calves (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). However, we found that some member in Prevotellaceae (such as \u003cem\u003ePrevotellaceae bacterium\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e) were especially decreased in LY35 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eThe results above may imply that the structure of calf gut microbial community is perturbed by the onset of diarrhea, and the diarrhea-associated microbes are different at the two ages due to structural differences in the gut microbes at 15 days of age and 35 days of age.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMicrobial co-occurrence networks of rectal microbiota of calves at genus level\u003c/h2\u003e \u003cp\u003eTo further explore the potential ecological roles of the keystone genera in calves with different health status, we performed microbial network analysis to depict the interactions among predominant genera (relative abundance\u0026thinsp;\u0026gt;\u0026thinsp;0.005%, present in more than 50% of samples) in HY15, LY15, HY35, and LY35 groups, respectively. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the four microbial networks were dominated by genera of \u003cem\u003eFirmicutes\u003c/em\u003e. Compared to calves at the same age, the microbial networks in calves with low health status were found to have more negative correlations and less positive correlations, with negative/positive correlations in HY15, LY15, HY35, and LY35 groups was 36/152, 80/114, 22/93 and 52/89, respectively (Supplementary Table S4, Chi-square test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Some opportunistic pathogens, primarily \u003cem\u003eEscherichia Shigella\u003c/em\u003e, increased their participation in the entire networks of calves with low health status, especially at 35 days of age (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). The degree (the number of associations to other bacteria) of \u003cem\u003eEscherichia Shigella\u003c/em\u003e in the HY15, LY15, HY35, and LY35 groups were 11, 14, 2, and 10, respectively (Supplementary Table S5). Some bacterial genera like \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, and \u003cem\u003eButyricicoccus\u003c/em\u003e had strong positive correlations with \u003cem\u003eEscherichia Shigella\u003c/em\u003e, while others like \u003cem\u003ePhascolarctobacterium\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eUCG-005\u003c/em\u003e, and \u003cem\u003ePrevotella-9\u003c/em\u003e were negatively correlated with it (\u003cem\u003er\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.6, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of diarrhea-associated bacteria in rectal microbiota of calves using random forest algorithm\u003c/h2\u003e \u003cp\u003eTo further identify potential diarrhea-associated bacteria at different ages, we regressed the relative abundance of rectal bacteria at genus level against Y score using a random forest algorithm model. According to the cross-validation error curves, the TOP 10 and TOP 22 genera in 15-day-old calves and 35-day-old calves were chosen for further study, respectively (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2). The lists of top 10 and 22 bacterial taxa in 15-day-old calves and 35-day-old calves, in order of time-discriminatory importance, were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe further constructed the co-occurrence network of these genera with Y score to explore the interactions among them. Among the TOP 10 genera at 15-day old calves, four genera, including \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003ePeptostreptococcus\u003c/em\u003e, \u003cem\u003eErysipelotrichaceae_UCG-003\u003c/em\u003e, and \u003cem\u003eMogibacterium\u003c/em\u003e, were positively correlated with calf health scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Meanwhile, these genera mentioned above were found to be positively correlated with each other. On the contrary, \u003cem\u003eLachnospiraceae_UCG-004\u003c/em\u003e was positively correlated with \u003cem\u003eButyricicoccus\u003c/em\u003e, and the former had negative correlations with two genera that were positively correlated with the Y score, including \u003cem\u003ePeptostreptococcus\u003c/em\u003e and \u003cem\u003eMogibacterium\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eIn 35-day-old calves, five genera, including \u003cem\u003ePrevotella_9\u003c/em\u003e, \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003eSellimonas\u003c/em\u003e, \u003cem\u003eSuccinivibrio\u003c/em\u003e, and \u003cem\u003eAcidaminococcus\u003c/em\u003e, had positive correlations with Y score, and there were seven genera, such as \u003cem\u003eCitrobacter\u003c/em\u003e, \u003cem\u003eButyricicoccus\u003c/em\u003e, \u003cem\u003eRoseburia\u003c/em\u003e, \u003cem\u003eSubdoligranulum\u003c/em\u003e, \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, and \u003cem\u003eUCG-005\u003c/em\u003e, were negatively correlated with Y score (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, the genera that were positively correlated with the Y score had positive correlations with each other, and the genera that were negatively correlated with the Y score were also positively correlated with each other. In contrast, the formers had negative correlations with the latter (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis of diarrhea-associated bacteria with rectal SCFA\u003c/h2\u003e \u003cp\u003eTo further explore the role of these diarrhea-associated microorganisms in rectal fermentation of calves, we performed a correlation analysis. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA, \u003cem\u003eErysipelotrichaceae_UCG-003\u003c/em\u003e and \u003cem\u003eMogibacterium\u003c/em\u003e had positive correlations with the molar proportion of acetate, but they had negative correlations with the concentration and molar proportion of butyrate in 15-day-old calves (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, \u003cem\u003eLachnospiraceae_UCG-004\u003c/em\u003e was negatively correlated with the concentration and molar proportion of valerate in 15-day-old calves (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB, \u003cem\u003eMegasphaera\u003c/em\u003e and \u003cem\u003eLigilactobacillus\u003c/em\u003e had positive correlations with the concentrations with acetate, butyrate and total SCFA in 35-day-old calves (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, \u003cem\u003eCitrobacter\u003c/em\u003e had negative correlation with the molar proportion of butyrate in 35-day-old calves (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTrillions of microbes colonize in gastrointestinal tract and keep a delicate balance in a symbiotic relationship with the host [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In our study, we found that the gut microbial structure of calves changed greatly with their health status and age. At 15 days of age, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e and their corresponding families were increased, while \u003cem\u003eButyricicoccus\u003c/em\u003e and \u003cem\u003eClostridium perfringens\u003c/em\u003e were decreased in calves with high health status. \u003cem\u003eBifidobacterium\u003c/em\u003e is an important taxon in early life, being one of the most abundant genera in the infant intestinal microbiota and carrying out important functions for maintaining host-homeostasis [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. \u003cem\u003eStreptococcus\u003c/em\u003e is generally regarded as lactic acid bacteria, and some strains such as \u003cem\u003eS. infantarius\u003c/em\u003e and \u003cem\u003eS. faecalis\u003c/em\u003e exhibited anti-\u003cem\u003eSalmonella\u003c/em\u003e activities [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. It's worth noting that Ma et at. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] have reported that \u003cem\u003eStreptococcus\u003c/em\u003e was key microbial markers that can differentiate \u0026ldquo;healthy\u0026rdquo; and \u0026ldquo;diarrheic\u0026rdquo; gut microbiota and it was enriched in healthy calves. Although \u003cem\u003eButyricicoccus\u003c/em\u003e is a butyrate producer, some studies reported that it positively correlated with host inflammatory responses and enriched in calf diarrhea caused by \u003cem\u003eClostridioides difficile\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt 35 days of age, we found that two Prevotellaceae members were increased, while Butyricicoccaceae and Clostridiaceae were decreased in calves with high health status. Members of \u003cem\u003ePrevotellaceae\u003c/em\u003e generally have broad repertoires of polysaccharide utilization loci and carbohydrate active enzymes targeting various plant polysaccharides, which could contribute to high fiber utilization and powerful SCFA production in hindgut [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The members of Clostridiaceae contain many diarrhea-causing bacteria, such as \u003cem\u003eClostridioides difficile\u003c/em\u003e and \u003cem\u003eClostridium perfringens\u003c/em\u003e. Additionally, we found that a genus, which was called \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, was enriched in calves with low health status. Wang et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] found that \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e was elevated in the gut of lambs with diarrhea. Sun et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] also found that \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e was reduced in the process of relieving diarrhea in weaned piglets treated by coated zinc oxide.\u003c/p\u003e \u003cp\u003eUsing random forest algorithm, we obtained similar results that mentioned above. Among the TOP 10 and TOP 22 diarrhea-related genera chosen based on health score in 15-day old calves and 35-day old calves, respectively, the \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eButyricicoccus\u003c/em\u003e, and \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, were included. Interestingly, the \u003cem\u003eButyricicoccus\u003c/em\u003e was identified as diarrhea-related genera at both 15 days of age and 35 days of age, which may indicate that it plays a crucial role in calf diarrhea. Besides, some additional genera that have been ignored in our differential analysis seem to be extremely important. For example, \u003cem\u003eErysipelotrichaceae_UCG-003\u003c/em\u003e, which correlated with health score positively, was far more important than other bacteria in 15 days of age. Some studies suggested that \u003cem\u003eErysipelotrichaceae\u003c/em\u003e was beneficial to improve gut homeostasis, and its genus \u003cem\u003eErysipelotrichaceae_UCG-003\u003c/em\u003e was enriched in healthy aging cohort than non-healthy aging cohort [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. At 35 days of age, \u003cem\u003eSellimonas\u003c/em\u003e may be a potential biomarker for the restoration of intestinal homeostasis, and its abundance is low in patients with intestinal dysbiosis [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe microbial co-occurrence networks further revealed that there was apparent co-exclusion exists between genera that positively correlated with health score and genera that negatively correlated with it. Although no genera that negatively correlated with health score were detected at 15 days of age, we found that some genera showed exclusions with \u003cem\u003eButyricicoccus\u003c/em\u003e and \u003cem\u003eLachnospiraceae_UCG_004\u003c/em\u003e. The \u003cem\u003eCitrobacter\u003c/em\u003e and \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e were the two of predominant genera that correlated with health scores negatively at 35 days of age, and both have been reported to be closely related to diarrhea. \u003cem\u003eCitrobacter\u003c/em\u003e was commonly defined as pathogens and can induce diarrhea and enteritis [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In addition to the co-occurrence network constructed among diarrhea-associated bacteria, we also delineated the overall interaction pattern of these bacteria with other bacteria in HY15, LY15, HY35, and HY35 group, respectively. The results showed that those \u0026ldquo;bad\u0026rdquo; bacteria mentioned above, including \u003cem\u003eButyricicoccus\u003c/em\u003e and \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, were likely to cooperate with \u003cem\u003eEscherichia Shigella\u003c/em\u003e and negatively correlated with other \u0026ldquo;good\u0026rdquo; bacteria.\u003c/p\u003e \u003cp\u003eThere are various ecological relationships exist in gut microbial communities, ranging from cooperation to competition, while two taxa with similar niches tend to exclude each other for limited food and living space [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Overall, our study highlighted the changed microbial interaction patterns between diarrheic calves and healthy calves, which may shape different microbial function. We also emphasized that although the diarrhea-related bacteria of calves will vary at different ages, the changed genera can fill the gap in the ecological niche, against the same pathogenic bacteria, and ensure the health of calve. Promoting a successful transition of the main members of gut microbiota from cumulative anaerobic bacteria (such as Lactobacillaceae) to fiber-degrading bacteria (such as Prevotellaceae) in early calf rearing may benefit calves to better cope with diarrhea challenges. Nevertheless, future studies to investigate the active microbial functions and taxa using culture-based technologies are required to confirm the function of these diarrhea-related bacteria in deeper mechanistic level.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, significant difference of gut microbial structure existed between high-health-status calves and low-health-status calves, and some specific bacteria, which we referred as diarrhea-related bacteria, changed in their roles on diarrhea with calf ages. Moreover, the interaction patterns of gut microbiota also show great variation in diarrhea status and calf ages. Our study provides new insights into developing novel prevention and treatment strategies in calf diarrhea by targeted microbial intervention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe use of the animals and the experimental procedure were approved by the Animal Care Committee and Use Committee of the Northwest A\u0026amp;F University (protocol number: NWAFAC1008).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequence data can be found in the NCBI repository in BioProject: PRJNA744001.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGuangfu Tang: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eXi Wang: Formal analysis, Software, Validation, Visualization, Writing \u0026ndash; original draft.\u003c/p\u003e\n\u003cp\u003eMinghui Cui: Investigation, Methodology, Resources, Validation.\u003c/p\u003e\n\u003cp\u003eGehan Ren: Investigation, Methodology, Validation, Visualization.\u003c/p\u003e\n\u003cp\u003eFang Yan: Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eShunshan Wang: Software, Validation. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJunhu Yao: Methodology, Supervision.\u003c/p\u003e\n\u003cp\u003eXiurong Xu: Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial support statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Key Science and Technology Program of Shaanxi Province (No.2022NY-088).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMcGuirk SM. 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Microbial interactions: from networks to models. \u003cem\u003eNat Rev Microbiol.\u003c/em\u003e 2012;10(8):538-550.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"calf diarrhea, days of age, gut microbiota, microbial co-occurrence network, random forest regression analysis","lastPublishedDoi":"10.21203/rs.3.rs-3411867/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3411867/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCalf diarrhea is one of the major health problems in calf rearing on dairy farms worldwide. The gut microbes have great influence on prevention and treatment of calf diarrhea, but their role in diarrhea is still lacking. The objective of this study was to identify the diarrhea-related bacteria in two different days of age, and to investigate whether these bacteria were affected by calf ages.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eForty-eight new-born female calves were selected for recording the fecal score daily and collecting the rectal content at 15 and 35 days of age, respectively. The diarrhea status and health score of calves in two different ages were evaluated according to the fecal score. The rectal microbial fermentation and microbial community structure were different between high-health-status calves and low-health-status calves. Compared to calves with high health status, the low-health-status calves had decreased butyrate molar proportion in rectal feces at both 15 days of age and 35 days of age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The LEfSe analysis showed that the relative abundance of Butyricicoccaceae (\u003cem\u003eButyricicoccus\u003c/em\u003e) and Clostridiaceae (such as \u003cem\u003eClostridium sensu stricto 1\u003c/em\u003e and \u003cem\u003eClostridium perfringens\u003c/em\u003e) were higher in low-health-status calves at both 15 days of age and 35 days of age. However, the relative abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003ePeptostreptococcus\u003c/em\u003e were lower in low-health-status calves at 15 days of age. At 35 days of age, we found that some member in Prevotellaceae (such as \u003cem\u003ePrevotellaceae bacterium\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e) were especially decreased in low-health-status calves. Using random forest regression analysis, most of these genera mentioned above were identified as diarrhea-related bacteria. Furthermore, we have further revealed that some bacteria, like \u003cem\u003eErysipelotrichaceae_UCG-003\u003c/em\u003e and \u003cem\u003eMogibacterium\u003c/em\u003e, were additional diarrhea-related bacteria at 15 days of age. While other bacteria, including \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003ePrevotella 9\u003c/em\u003e, \u003cem\u003eRomboutsia\u003c/em\u003e, and \u003cem\u003eCitrobacter\u003c/em\u003e were additional diarrhea-related bacteria at 35 days of age. The microbial co-occurrence network analysis revealed that the interaction patterns of calf microbiome changed with diarrhea status and ages. Particularly, the potential pathogens, like \u003cem\u003eEscherichia Shigella\u003c/em\u003e, had increased participation in co-occurrence networks of diarrheic calves. Among these diarrhea-related bacteria, the genera that positively correlated with health score had apparent co-exclusion with the genera that negatively correlated with health score, but they correlated with rectal short chain fatty acids positively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOverall, our study revealed that the diarrhea-related bacteria of calves will vary at different ages, which may contribute to the treatment and prevention of diarrhea in the calf industry by targeted microbial intervention.\u003c/p\u003e","manuscriptTitle":"The characteristics of diarrhea-related bacteria in suckling calves and their dynamic succession with ages","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-10 18:26:29","doi":"10.21203/rs.3.rs-3411867/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c3ebd8fd-e453-4c5c-aed3-380fc6235256","owner":[],"postedDate":"October 10th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T08:44:19+00:00","versionOfRecord":[],"versionCreatedAt":"2023-10-10 18:26:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3411867","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3411867","identity":"rs-3411867","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}