Effects of Artemisia argyi Aqueous Extract on Rumen Fermentation Parameters and Microbiota in Lambs

Abstract

This study sought to evaluate the effects of Artemisia argyi aqueous extract (AAE) on rumen fermentation parameters and the microbiota within the rumen of lambs. A total of 32 lambs that are 3 months old and 24.06 ± 0.04 kg in body weight were randomly assigned to four treatment groups, with eight replicates per treatment. The diets for the four groups were formulated with the following adding dose of AAE: 0 mg/kg (CON), 500 mg/kg (AAE-L), 1000 mg/kg (AAE-M), and 1500 mg/kg (AAE-H), respectively. The results showed that, compared to the CON group, three AAE add groups significantly decreased the A/P ratio; AAE-M and AAE-H groups significantly increased MCP and propionic acid contents. Supplementation with AAE had no significant effect on the alpha and beta diversity of the rumen microbiota, but significantly increased the relative abundances of beneficial bacteria, such as Actinobacteriota in the rumen. In conclusion, AAE supplementation improved the rumen fermentation and microbiota of lambs. In the overall consideration, under the conditions of this research, the supplementation of 1000 mg/kg AAE was optimal.

1. Introduction

Ruminants contribute significantly to the global food supply by providing high-quality products like meat, milk, wool, and leather [1]. The rumen, an essential digestive organ in these animals, relies on its microbial community to convert plant fibers and less nutritious proteins into volatile fatty acids (VFAs). These VFAs play a crucial role by providing 70% to 80% of the energy required for rumen development and the overall growth of the host animal [2,3]. Additionally, the rumen epithelium plays a critical role in absorbing VFAs produced by the rumen microbiota and serves as a vital barrier separating the rumen environment from the host’s blood circulation [4]. In high-intensity ruminant farming, a diet rich in concentrate was commonly used to promote faster growth rates or increase milk yield in these animals. This practice will highly affect the rumen’s fermentation characteristics and microbiota composition, thereby weakening the barrier function of the rumen epithelium, thereby elevating the likelihood of disease and causing significant economic losses in the ruminant industry [5,6]. Employing dietary adjustments to enhance ruminal microorganisms and their metabolic products, such as supplementation with phytonutrients, thiamine, and probiotics, has demonstrated promising efficacy in improving the health of animals [7].

In the modern livestock production system, natural plant-derived feed additives have become one of the research hotspots in the field of livestock production because they contain a variety of bioactive ingredients and have the characteristics of being free from drug resistance, residue, and toxic side effects, as well as being safe and reliable. Artemisia argyi, commonly referred to as medical grass or Artemisia argyi grass, is a perennial herb from the Compositae family that is found extensively throughout China. This plant thrives in warm, moist environments and typically grows along the edges of wild lands. It is known for its robust resistance to both cold and drought conditions. Artemisia argyi is rich in various bioactive compounds, including volatile oils, flavonoids, eudesmane, and triterpenes [8]. Additionally, it supplies polyunsaturated fatty acids, total phenolics, vitamin C, and essential amino acids [9]. However, there are relatively fewer studies on the application of Artemisia argyi in animal production, especially in ruminant production. Only a small minority of studies had illustrated the positive impacts of Artemisia argyi addition in lambs [10,11,12], but in these studies, Artemisia argyi or its leaves were directly fed to animals, and there was little research on Artemisia argyi extracts. The effects of Artemisia argyi aqueous extract (AAE) on rumen fermentation and microbiota in lambs have not been reported.

Therefore, in the present study, the effects of AAE on rumen fermentation parameters and rumen microbiota in lambs were investigated, in order to provide a reference for the application of Artemisia argyi in lamb production.

2. Materials and Methods

2.1. Preparation of AAE

Fresh aerial parts of Artemisia argyi were harvested in August from Horinger County, located at 40°01′ N and 111°58′ E in Hohhot, Inner Mongolia, China. The raw materials were dried in the shade at room temperature and then the whole plant was chopped into short segments, which were added to water at a ratio of 1:25 and then extracted for 7 h at 80 °C. After completion of the extraction process, a vacuum filtration was conducted, and the resultant filtrate was collected and freeze-dried into powder. Through the anthrone-sulfuric acid method [13] and LC-MS [14] analysis of active ingredients in AAE, we identified 11 main substances; the specific active ingredients are shown in Figure 1.

2.2. Animals and Experiment Design

The Research Station of Inner Mongolia Agricultural University in Hohhot, China, was the site where the experiment took place. A total of 32 Dorper × Han female lambs with similar age (3 months) and body weight (24.06 ± 0.04 kg) were randomly divided into 4 treatments with 8 replicates per group. In this study, a fully randomized trial approach was used, involving the following four distinct treatments according to the previous research results of our research group [15,16]: (1) the control group (CON), where lambs were fed a standard diet; (2) the low-dose AAE group (AAE-L), where lambs received the standard diet with an addition of 500 mg/kg AAE; (3) the middle-dose AAE group (AAE-M), where the diet was supplemented with 1000 mg/kg AAE; and (4) the high-dose AAE group (AAE-H), where lambs were given a basal diet with 1500 mg/kg AAE. According to the Nutrient Requirements of Meat-type Sheep, China (NY/T 816-2021) [17], the main diet was designed to fulfill the nutritional needs of lambs. The contents of dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), calcium (Ca), and phosphorus (P) in the feed were determined based on GB/T 6432-2018 [18], GB/T 20806-2006 [19], NY/T 1459-2007 [20], GB/T 6436-2018 [21], and GB/T 6437-2018 [22], respectively. Details regarding the diet’s composition and nutrient content are provided in

Table 1. Composition and nutrient levels of basal diets.

Items	Proportion (%)
Diet Composition (as-fed basis)
Alfalfa hay	16.25
Corn straw	14.00
Oat hay	24.75
Corn	23.25
Soybean meal	10.95
Wheat bran	4.25
Corn germ meal	1.95
Soybean oil	1.10
Premix 1	0.50
Limestone	1.10
Calcium hydrogen phosphate	0.70
Salt	0.40
Sodium bicarbonate	0.80
Total	100.00
Nutrient levels 2 (as dry matter basis)
Digestible energy (MJ/kg)	12.01
Crude protein	15.80
Neutral detergent fiber	40.80
Acid detergent fiber	26.24
Calcium	1.08
Phosphorus	0.40

¹ Premix provided the following per kilogram of diet: vitamin A 6000 IU, vitamin D3 2500 IU, vitamin E 12.5 IU, vitamin K3 1.8 mg, vitamin B1 0.035 mg, vitamin B2 8.5 mg, vitamin B6 0.9 mg, nicotinic acid 22 mg, D-pantothenic acid 17 mg, vitamin B12 0.03 mg, biotin 0.14 mg, folic acid 1.5 mg, Fe 0.04 g, Cu 0.008 g, Zn 0.05 g, Mn 0.03 g, I 0.3 mg, Se 0.3 mg, Co 0.25 mg. ² Digestible energy was a calculated value, while the others were measured values.

. The research spanned 75 days. In the initial 15 days, the lambs were gradually introduced to their diet and adjusted to their environment. For the remaining 60 days, the lambs were provided with their assigned diets. Each lamb was placed in individual pens and received feed two times a day, at 08:00 and 16:00. Both the experimental diets and water were offered ad libitum. Throughout the experimental period, each lamb was housed separately in pens and kept under uniform management conditions.

The animal use was approved by the Animal Ethics and Welfare Committee at Inner Mongolia Agricultural University (NND2021098) and conducted according to the National Standard Guidelines for Ethical Review of Animal Welfare (GB/T 35892-2018) [23].

2.3. Sample Collection and Preparation

On day 60 of the experiment, the lambs were subjected to a 12 h fasting period and subsequently euthanized (jugular vein exsanguination) for sampling. The rumen was obtained by dissection, and a 100 mL rumen fluid sample was collected. A portable pH meter was employed immediately after collecting the samples to assess the pH of rumen fluid samples. The collected rumen fluid was first filtered through four layers of cheesecloth. For ammonia-N (NH₃-N) analysis, two aliquots, each 0.5 mL of the filtrate, were mixed with 4.5 mL of 0.2 mol/L hydrochloric acid to ensure the stabilization of nitrogen. For volatile fatty acids (VFAs) determination, two aliquots, each 4 mL of filtrate, were combined with 1 mL of a 25% metaphosphoric acid solution. The leftover filtrate was kept for microbial protein (MCP) analysis. All samples were maintained at −20 °C until they were analyzed further. Additionally, three 2 mL aliquots of rumen contents were placed into cryogenic vials and kept at −80 °C for ruminal microbiota composition analysis.

2.4. Rumen Fermentation Index Measurement

The content of NH₃-N in rumen fluid was determined according to the colorimetric analysis of Miguel et al. [24]. The MCP content was analyzed by colorimetric analysis with reference to the Coomassie brilliant blue method of Chanjula et al. [25]. The VFA content was analyzed by gas chromatograph (Agilent 7890A, Palo Alto, CA, USA) according to Seo et al. [26].

2.5. Rumen Microbiota Diversity Analysis

An analysis of ruminal microbial community diversity was performed utilizing 16S rRNA gene sequencing. Genomic DNA from the microbial community in ruminal fluid samples was extracted using a DNA kit provided by Omega Bio-tek, located in Norcross, GA, USA. The extracted DNA was subsequently evaluated using 1.0% agarose gel electrophoresis. Universal primers 338 F (5′-ACTCCGGGAGCAGCA-3′) and 806 R (5′-GGACTACH VGGTWTCTAAT-3′) were used to amplify the V3-V4 region of the 16S rRNA gene from rumen content samples. As part of the process of PCR analysis, the PCR products were extracted from 2% agarose gels, purified using an AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), and quantified using a QuantusTM fluorometer (Promega, Madison, WI, USA). Sequencing was conducted on the Illumina MiSeq PE300 platform/NovaSeq PE250 platform (Illumina, San Diego, GA, USA) with the purified amplification products. After purifying, quantifying, and homogenizing the PCR amplification products, high-throughput sequencing was performed on the NovaSeq6000 platform. Singletons and chimeric sequences were excluded, and the remaining tags were organized into operational taxonomic units (OTUs) with UPARSE at a 97% similarity threshold. Subsequently, the OTU representative sequences were annotated using the SSUrRNA database. To compare alpha diversity indices (including Sobs, ACE, Chao, Shannon, and Simpson) between the four groups, the Wilcoxon rank-sum test was applied. Beta diversity was assessed using Qiime software (version 1.91, http://qiime.org/install/index.html, accessed on 14 July 2023), which analyzed community structure similarities among different samples based on the Bray–Curtis distance metric. To identify bacterial taxa that showed differential representation across various groups and taxonomic levels, linear discriminant analysis combined with effect size (LEfSe) was utilized, applying an LDA effect size threshold more significant than 2. Spearman rank correlation coefficients were applied to analyze the Correlation Heatmap. As part of this study, a matrix of values was calculated to examine the relationship between environmental factors and the selected species. In a two-dimensional matrix, color changes represent information about the data, while the colors indicate the magnitude of the data values, which can be visualized using the defined colors.

2.6. Statistical Analysis

Data collection was initially managed using Microsoft Excel 2019. The rumen fermentation parameters among groups were analyzed one-way ANOVA followed Duncan’s test in SAS 9.2 software (SAS Institute Inc., Cary, NC, USA). Differences in the alpha diversity indices and relative abundances of rumen microbiota were carried out using the Kruskal–Wallis H test method and stats package in R software (version 3.3.1, Vienna, Austria). Spearman’s correlation analysis was used to analyze the relationships between rumen microbiota and fermentation parameters. Results were shown as means with standard error of the mean (SEM). A probability value of p < 0.05 was considered statistically significant.

3. Results

3.1. Rumen Fermentation Characteristics

Compared to the CON group, three AAE add groups significantly decreased A/P ratio (p < 0.01;

Table 2. Effects of AAE on ruminal fermentation parameters of lambs.

Items	CON	AAE-L	AAE-M	AAE-H	SEM	p-Value
pH	6.87	6.82	6.72	6.77	0.04	0.468
NH3-N, mg/100 mL	22.74	20.65	18.54	18.87	0.79	0.213
MCP, mg/100 mL	22.88 b	27.75 b	37.63 a	34.34 a	1.42	<0.001
Acetate, mmol/L	55.28	53.47	49.79	54.81	1.06	0.152
Propionate, mmol/L	12.58 b	14.65 ab	16.18 a	15.92 a	0.61	0.046
Butyrate, mmol/L	12.24	13.50	14.32	14.23	0.35	0.132
Iso-butyrate, mmol/L	0.62	0.66	0.67	0.64	0.02	0.932
Valerate, mmol/L	1.33	1.45	1.50	1.45	0.04	0.404
Iso-valerate, mmol/L	0.72	0.78	0.82	0.80	0.04	0.751
A/P	4.43 a	3.78 b	3.13 b	3.66 b	0.14	0.003
TVFA, mmol/L	82.78	84.50	83.27	87.87	1.46	0.570

NH₃-N, ammonia-N; MCP, microbial protein; AAE, Artemisia argyi aqueous extract; SEM, standard error of the mean. Values are presented as means with SEM (n = 8). Different superscript letters (a, b) in the same row denote significant differences (p < 0.05).

); AAE-M and AAE-H groups significantly increased propionate content (p < 0.05); and rumen MCP content was significantly increased in AAE-M and AAE-H groups compared to the CON and AAE-L groups (p < 0.01).

3.2. Rumen Microbiota Diversity

3.2.1. Sampling Depth

Analysis of rumen microbiome diversity from 32 samples resulted in a total of 2,169,019 optimized sequences, with the number of optimized sequence bases being 907,028,473 bases (bp). The average length of the quality sequences was 418 bp. The high-quality sequences were effectively clustered and analyzed into OTUs defined by 97% similarity, and a total of 3457 OTUs were obtained. These belonged to 18 phyla, 34 classes, 66 orders, 119 families, 252 genera, and 580 species. In subsequent analysis, the number of sequences in each sample was flattened to 45,029 to reduce statistical errors. Further, the OTU Good’s coverage index value of all samples was over 99%, and the change of rarefaction curves was generally slow and close to saturation, indicating that the library constructed in this study could effectively reflect the abundance and diversity of the microbial community of the samples (Figure 2).

3.2.2. Rectal Microbiota Diversity Indices

Ace, Chao, Shannon, and Simpson indices were obtained by analysis of the alpha diversity index, as shown in Figure 3. The results showed that the dietary inclusion of AAE had no significant effect on Ace, Chao, Shannon, and Simpson indices (p > 0.05). In conclusion, AAE had no adverse effects on rumen microbial richness (Ace and Chao indices) and diversity (Shannon diversity index and Simpson diversity index) of lambs.

Principal Coordinate Analysis (PCoA) of the rumen microbiota based on Bray–Curtis distance matrices between each sample is shown in Figure 4A. The contribution values of principal components PC1 and PC2 accounted for 15.47% and 11.96% of the total variation, respectively. Thus, rumen microbiota structure had no aggregation distribution in each group, indicating no significant difference in rumen microbial β diversity among groups (p > 0.05). The Venn diagram is shown in Figure 4B, and the total number of OTUs was 3457 OTUs. In the CON group, the number of OTUs was 2264, with 366 unique OTUs. In the AAE-L group, the number of OTUs was 2288, with 401 unique OTUs. In the AAE-M group, the number of OTUs was 2163, with 325 unique OTUs. In the AAE-H group, the number of OTUs was 2002, with 209 unique OTUs. A total of 1367 OTUs (39.54% of the total) were shared among four level-added groups.

3.2.3. Taxonomic Classification Levels of the Bacterial Communities

In this experiment, 18 microbial phyla were identified at the phylum level, and the relative abundances (Taxa > 0.1%) of the top ten species in terms of ruminal microbial phylum-level abundance were presented. As shown in

Table 3. Effects of AAE dietary supplementation on microbial abundance in rumen at phylum level (Top 10 phyla).

Items	CON	AAE-L	AAE-M	AAE-H	SEM	p-Value
Bacteroidota	52.31	48.15	54.03	54.46	3.53	0.511
Firmicutes	43.16	47.12	40.01	39.42	3.57	0.487
Spirochaetota	1.99	2.23	2.43	2.23	0.36	0.276
Fibrobacterota	0.68	0.80	1.67	1.04	0.39	0.746
Actinobacteriota	0.49 b	0.54 b	0.80 ab	1.09 a	0.14	0.017
Proteobacteria	0.25	0.22	0.23	0.11	0.09	0.759
Patescibacteria	0.47	0.29	0.25	0.26	0.04	0.273
Desulfobacterota	0.23	0.14	0.11	0.11	0.03	0.558
Verrucomicrobiota	0.18	0.14	0.10	0.15	0.02	0.372
Chloroflexi	0.02	0.03	0.04	0.03	0.01	0.246
Others	0.21	0.19	0.21	0.24	0.02	0.840

AAE, Artemisia argyi aqueous extract; SEM, standard error of the mean. Values are presented as means ± SEM (n = 8). Different superscript letters (a, b) in the same row denote significant differences (p < 0.05).

and Figure 5A, Bacteroidota (>48% of total), Firmicutes, Spirochaetota, Fibrobacterota, Actinobacteriota, Proteobacteria, Patescibacteria, Desulfobacterota, Verrucomicrobiota, and Chloroflexi were the predominant phyla (>99% of total). Compared to the CON group, Actinobacteriota abundance was significantly increased in the AAE-H group (p < 0.05). Notably, Bacteroidetes and Firmicutes collectively accounted for 90% of rumen microbial diversity in lambs.

At the genus level, 252 microbial genera were identified, and the relative abundances (Taxa > 0.1%) of the top ten species in terms of ruminal microbial genus-level abundance were presented. As shown in

Table 4. Effects of AAE dietary supplementation on microbial abundance in rumen at genus level (Top 10 genera).

Items	CON	AAE-L	AAE-M	AAE-H	SEM	p-Value
Prevotella	28.59	22.40	31.26	29.71	2.46	0.599
Rikenellaceae	6.53	6.68	6.05	7.09	0.71	0.639
Christensenellaceae	6.05	8.28	4.73	5.04	0.55	0.412
Muribaculaceae	5.58	6.13	6.24	6.53	0.69	0.141
NK4A214	5.01	4.62	4.26	3.90	0.33	0.681
F082	3.63	5.08	4.46	4.42	0.54	0.862
Succiniclasticum	4.17	3.17	4.16	3.92	0.48	0.766
Lachnospiraceae	3.14	2.89	2.57	2.88	0.27	0.901
UCG-001	3.45	2.99	2.84	2.19	0.48	0.829
Treponema	1.95	2.20	2.38	2.20	0.18	0.564
Others	33.39	35.55	35.27	32.12	1.42	0.875

AAE, Artemisia argyi aqueous extract; SEM, standard error of the mean. Values are presented as means ± SEM (n = 8).

and Figure 5B, Prevotella, Rikenellaceae, Christensenellaceae, Muribaculaceae, NK4A214, F082, Succiniclasticum, Lachnospiraceae, UCG-001, and Treponema were the predominant genera (>60% of total), and the abundance of these predominant genera did not change by treatment.

To determine the functional communities in the samples, a LEfSe analysis was performed to identify the specific microorganisms in the rumen fluid of the four treatment groups of lambs (Figure 6). Microorganisms with a linear discriminant analysis (LDA) > 2 were considered specific microorganisms among the four treatment groups. A total of 14 specific microbiota were identified from 32 rumen fluid samples collected from lambs, in which Lachnospira and Peptococcaceae were significantly enriched in the CON group; the Anaeroplasma and UCG-011 were significantly enriched in the AAE-L group; and the Muribaculaceae and Succinivibrionaceae were significantly enriched in the AAE-H group.

3.2.4. Spearman Correlation Analysis

Figure 7 shows Spearman’s correlation analysis between ruminal fermentation parameters and any of the most relatively abundant microbial genera (top 50 genera). Butyric acid content was negatively correlated with RF39 (R = −0.42031, p < 0.05), Butyrivibrio (R = −0.43571, p < 0.05). Isobutyric acid content was positively correlated with Treponema (R = 0.35924, p < 0.05), but negatively correlated with Oscillospiraceae (R = −0.38717, p < 0.05). A/P was positively correlated with Rikenellaceae (R = 0.50770, p < 0.01), Christensenellaceae (R = 0.47177, p < 0.01), NK4A214 (R = 0.41056, p < 0.05), Ruminococcaceae (R = 0.40125, p < 0.05), AD3011 (R = 0.39509, p < 0.05), and Anaerovorax (R = 0.42794, p < 0.05), but negatively correlated with Succiniclasticum (R = −0.51870, p < 0.01), Ruminococcus (R = −0.35594, p < 0.05), UCG-014 (R = −0.49450, p < 0.01), Selenomonas (R = −0.58070, p < 0.001), ruminantium (R = −0.42475, p < 0.05), and Anaerovibrio (R = −0.45051, p < 0.01). The pH was positively correlated with Rikenellaceae (R = 0.46182, p < 0.01), Christensenellaceae (R = 0.36178, p < 0.05), F082 (R = 0.36435, p < 0.05), p-251-o5 (R = 0.35722, p < 0.05), Erysipelotrichaceae (R = 0.43840, p < 0.05), AD3011 (R = 0.49013, p < 0.01), and nodatum (R = 0.38452, p < 0.05), but negatively correlated with Succiniclasticum (R = −0.45576, p < 0.01), UCG-001 (R = −0.36858, p < 0.05), UCG-014 (R = −0.41648, p < 0.05), AC2044 (R = −0.36580, p < 0.05), Selenomonas (R = −0.41450, p < 0.05), ruminantium (R = −0.47953, p < 0.01), and Anaerovibrio (R = −0.43686, p < 0.05). Isovaleric acid content was positively correlated with Treponema (R = 0.39846, p < 0.05), Marvinbryantia (R = 0.38636, p < 0.05), UCG-010 (R = 0.36774, p < 0.05), and Anaerovorax (R = 0.37807, p < 0.05). NH₃-N content was positively correlated with NK4A214 (R = 0.37489, p < 0.05), UCG-010 (R = 0.40667, p < 0.05), AD3011 (R = 0.42413, p < 0.05), UCG-008 (R = 0.56707, p < 0.001), Anaerovorax (R = 0.49129, p < 0.01), and Blautia (R = 0.4064, p < 0.05), but negatively correlated with Ruminococcus (R = −0.36810, p < 0.05), UCG-001 (R = −0.36062, p < 0.05), Selenomonas (R = −0.53149, p < 0.01), ruminantium (R = −0.35964, p < 0.05), and Anaerovibrio (R = −0.47406, p < 0.01). TVFA content was positively correlated with Muribaculaceae (R = 0.35267, p < 0.05), UCG-014 (R = 0.35117, p < 0.05), Lachnoclostridium (R = 0.43652, p < 0.05), and Saccharimonas (R = 0.40601, p < 0.05). Acetic acid content was positively correlated with Muribaculaceae (R = 0.51508, p < 0.01), NK3B31 (R = 0.38562, p < 0.05), Lachnoclostridium (R = 0.41085, p < 0.05), Saccharimonas (R = 0.47328, p < 0.01), UCG-010 (R = 0.38203, p < 0.05), UCG-008 (R = 0.38170, p < 0.05), and Anaerovorax (R = 0.42244, p < 0.05). Propionic acid content was positively correlated with Succiniclasticum (R = 0.51503, p < 0.01), UCG-001 (R = 0.42009, p < 0.05), UCG-014 (R = 0.59567, p < 0.001), Selenomonas (R = 0.45825, p < 0.01), and ruminantium (R = 0.40055, p < 0.05), but negatively correlated with Rikenellaceae (R = −0.50293, p < 0.01), Christensenellaceae (R = −0.43915, p < 0.05), and nodatum (R = −0.37727, p < 0.05).

4. Discussion

With the rising demand for lamb, coupled with the deterioration of grassland ecosystems and limited pasture availability, the confined feeding system for lambs has become a promising avenue for economic development. Nevertheless, as intensive ruminant livestock farming has advanced, issues such as metabolic disorders and reduced rumen functionality have become increasingly prevalent [16]. The fermentation parameters of the rumen indicate the homeostasis of its environment and affect the efficiency of energy and protein utilization. The pH value acts as a direct measure of ruminal health, closely associated with dietary composition and additives. The optimal pH range of ruminal fluid (between 6.2 and 7.2) can modulate VFA-producing pathways and enhance VFA absorption [27,28]. Regarding the effect of AAE feeding on ruminal pH, although animals receiving AAE showed lower pH levels, the differences among groups in the experiment were not statistically significant. The variation in rumen fluid pH is affected by factors such as rumination, lactic acid production, VFA synthesis, and the buffering ability of both feed and rumen contents. As ruminal fermentation rates rise, there is a corresponding increase in VFA and lactic acid production, which results in a decrease in rumen fluid pH [29]. Rumen VFA is mainly produced by microbial fermentation of dietary carbohydrates. It is the main energy source of ruminants and can provide 70–80% of the energy of ruminants. The yield of VFA mainly depends on the level and rate of rumen fermentation. Therefore, the concentration and composition of VFA are important indicators of rumen digestion and metabolism [30,31]. Acetic acid, propionic acid, and butyric acid are the main VFA products of rumen microbial digestion and metabolism, accounting for 95% of TVFA [32]. Among them, acetic acid can enter the liver through the blood circulation, where it is converted into acetyl-CoA, and further enters the tricarboxylic acid cycle to produce energy. Propionic acid is the main precursor of gluconeogenesis, and the glucose produced by propionic acid can meet the energy requirements of sheep by 30–50%. After butyric acid is absorbed by rumen epithelial cells, part of it is converted into β-hydroxybutyric acid, which further provides energy for several body tissues, especially muscle tissues [33]. Previous studies have indicated that elevated VFA production in the rumen correlates with a drop in rumen fluid pH [12]. This phenomenon explains the fluctuation in rumen fluid pH observed in this study. Furthermore, it has been proposed that the bioactive compounds found in certain plants may acidify the rumen environment under normal physiological conditions by decreasing the ciliate protozoa population, which subsequently affects the ruminal digestion of starch [32]. The fact that the total VFA concentration remained unchanged and were all treated with the same feeding management practices in lambs indicates that including dietary AAE has no effect on rumen pH. NH₃-N plays a crucial role in microbial protein synthesis within the rumen of ruminant animals, serving as the primary nitrogen source. MCP was primarily synthesized by the diverse microbial population inhabiting the rumen of ruminants, utilizing ammonia and oligopeptides generated from feed degradation. This MCP can be efficiently digested and absorbed by the small intestine, serving as a major source of high-quality protein for ruminants and fulfilling 40–60% of their protein requirements [34]. Consequently, enhancing the concentration of MCP in the rumen has been a focal point of research for numerous scholars. The alteration of MCP content is usually closely related to the growth and metabolic activity of microorganisms and may also reflect the compositional changes of microbial communities. Chen et al. (2021) reported that rumen NH₃-N concentration decreased and MCP concentration increased significantly in lambs fed a diet containing probiotics and a polysaccharide compound from Chinese medicine [35]. The findings of our study were similar to these results. The ratio of acetic acid to propionic acid serves as a critical indicator reflecting the mode of carbohydrate fermentation in the rumen and can be used to classify the type of fermentation. When the ratio was less than 2.5, it indicated a propionic acid-type fermentation, characterized by higher propionic acid production. This condition suggests that animals can utilize propionic acid for greater glucose synthesis, thereby indirectly conserving more glucogenic amino acids. Conversely, when the ratio exceeds 2.5, it signifies an acetic acid-type fermentation, with a higher value indicating lower feed energy utilization efficiency [36]. The observed increase in propionic acid and the simultaneous decrease in the acetic acid to propionic acid ratio in the groups receiving AAE compared to the CON group, although the ratio remained above 2.5, may be attributed to the effects of secondary metabolites from AAE on ruminal fermentation processes. It has been noted that secondary metabolites from plants can diminish the population of methanogenic archaea, which are responsible for hydrogen production used in propionate synthesis [37]. According to Calsamigilia et al. (2007), incorporating certain plant extracts into the rumen has been shown to inhibit methanogenesis [38]. This inhibition leads to reduced levels of methane and acetic acid while enhancing the concentrations of propionic acid and butyric acid. While there is no existing research directly examining how the secondary metabolites of AAE affect ruminal fermentation in ruminants, research on different artemisia species, including A. montana, under in vitro conditions, revealed a rise in the populations of ruminal bacteria such as Ruminococcus albus and Streptococcus bovis, with no significant changes in pH and TVFA levels [39]. This indicates that AAE can be used as a potential plant-based feed additive to inhibit rumen methane production, which is of great significance for environmental protection and the sustainable development of livestock production. Yu et al. (2021) supplemented the diets of lactating cattle with different doses of Artemisia annua extract (0%, 0.25%, 0.50%, 0.75%) and observed a significant increase in rumen TVFA, propionic acid, and butyric acid concentrations in the Artemisia annua extract group compared to the control group. They also noted a reduction in the acetic acid to propionic acid ratio of dairy cows [40]. Similarly, Faryabi et al. (2023) examined the effects of including 25% Artemisia sieberi leaves in the diet of growing male lambs and found that it significantly increased propionic acid concentrations [10].

The equilibrium of the rumen’s ecosystem and its digestive processes relies on the variety of microorganisms that inhabit the rumen, which can be affected by a range of factors, including diet, age of the animal, environmental conditions, and feed additives [41,42]. Alpha diversity and beta diversity serve as two pivotal metrics for assessing the diversity of microbial communities. Alpha diversity, often referred to as core diversity, quantifies the relative abundance of each species within a single community, thereby reflecting the richness and evenness of different microbial taxa. Beta diversity, conversely, examines the compositional differences between communities, highlighting shifts in population structure and revealing the stability and functional dynamics of microbial communities within ecosystems [43]. In this study, through the analysis of rumen microbial communities in sheep, we observed no significant differences in alpha or beta diversity across various groups. This suggests that these metrics can reliably capture fundamental characteristics of microbial communities under diverse experimental conditions, providing a robust foundation for subsequent experimental design and analysis. However, it is important to note that alpha and beta diversity indices do not fully encapsulate all aspects of microbial community properties. In actual ecological settings, microbial communities are dynamic and influenced by multiple factors. In some cases, functional variations among microorganisms may sometimes outweigh changes in species composition, meaning that significant compositional shifts might not always be reflected in alpha or beta diversity measures [44]. Huan et al. also found similar results in their research on adding probiotics and Chinese medicine polysaccharides to the lamb diet [35]. In the present study, Bacteroidetes and Firmicutes emerged as the predominant phyla within the ruminal microbial community, aligning with earlier research on sheep consuming high-grain diets [4]. Increasing the supplemental AAE dose in diets generally reduced the relative abundance of the Firmicutes phylum, which, in turn, lowered the Firmicutes to Bacteroidetes (F: B) ratio. The change in the F:B ratio could be attributed to the antimicrobial effects of sanguinarine in AAE, which may inhibit the growth of gram-positive Firmicutes. According to Beuria et al. (2005), sanguinarine was found to hinder the growth of gram-positive bacteria by interfering with the assembly process of FtsZ in the Z ring [45]. In the present study, the addition of AAE significantly increased the relative abundance of Actinobacteriota. Actinobacteria’s mechanism of action encompasses two key aspects. Once absorbed in the colon, acetic acid produced by Actinobacteria can cross the blood–brain barrier and activate neurons in the hypothalamus. This activation stimulates parasympathetic nerves and boosts growth hormone secretion, leading to increased feed intake and weight gain in mice [46]. Additionally, acetic acid impacts adipocyte storage through its effects on islet B cells, which in turn promotes insulin release [47]. Research has indicated that Actinobacteria’s presence correlates with lipid content, which supports animal growth and development. However, the increase in these bioactive substances can also elevate inflammation levels in the host [48]. In addition, UCG-001 and UCG-014 belong to the phylum Firmicutes, and UCG-001 contains many cellulose-decomposing bacteria. Succiniclasticum, a gram-negative rod-shaped anaerobe, is capable of fermenting succinate and converting it to propionic acid, an essential precursor of glucose in the rumen [49]. Spearman’s correlation analysis revealed that UCG-014 and Succiniclasticum positively correlated with propionate, and negatively correlated with A/P ratio and pH, as well as UCG-001 negatively correlated with the NH₃-N. Although Fibrobacillus, Ruminococcus, and Vibrio butyrate are present in relatively low numbers among rumen microorganisms, they are crucial for the breakdown of soluble proteins, starches, fiber, and non-fibrous carbohydrates in the diet [50].

5. Conclusions

The present research indicated that supplementation with AAE helps to promote the rumen fermentation of lambs. This phenomenon may be explained by the altered structure of the rumen microbiota. In overall consideration, under the conditions of this research, supplementation of 1000 mg/kg AAE was optimal, which might be used as an effective method in the efficient breeding of lambs. This provides a reference basis for the practical application of AAE as a natural plant feed additive in lamb production and for the development of feeding management strategies.