Eight Weeks of Bifidobacterium lactis BL-99 Supplementation Improves Lipid Metabolism and Sports Performance through Short-Chain Fatty Acids in Cross-Country Skiers: A Preliminary Study

1) Background: Probiotics in the form of nutritional supplements are safe and poten- tially useful for strategic application among endurance athletes.Bi dobacterium animalis lactisBL-99 (BL-99) was isolated from the intestines of healthy Chinese infants. We combined plasma-targeted metabolomics and fecal metagenomics to explore the effect of 8 weeks ofBL-99supplementation on cross-country

Hohhot 010110, China *Correspondence: jiangtao@tea.xaipe.edu.cn (T.J.); qirongw@163.com (Q.W.) Abstract: (1) Background: Probiotics in the form of nutritional supplements are safe and poten- tially useful for strategic application among endurance athletes.Bi dobacterium animalis lactisBL-99 (BL-99) was isolated from the intestines of healthy Chinese infants. We combined plasma-targeted metabolomics and fecal metagenomics to explore the effect of 8 weeks ofBL-99supplementation on cross-country skiers' metabolism and sports performance. (2) Methods: Sixteen national top-level male cross-country skiers were recruited and randomly divided into a placebo group (C) and aBL-99 group (E). The participants took the supplements four times/day (with each of three meals and at 21:00) consistently for 8 weeks. The experiment was conducted in a single-blind randomized fashion. The subject's dietary intake and total daily energy consumption were recorded. Blood and stool samples were collected before and after the 8-week intervention, and body composition, muscle strength, blood biochemical parameters, plasma-targeted metabolomic data, and fecal metagenomic data were then analyzed. (3) Results: The following changes occurred after 8 weeks ofBL-99sup- plementation: (a) There was no signi cant difference in the average total daily energy consumption and body composition between the C and E groups. (b) The VO 2maxand 60 /s and 180 /s knee joint extensor strength signi cantly increased in both the C and E groups. By the eighth week, the VO 2max and 60 s knee-joint extensor strength were signi cantly higher in the E group than in the C group. (c) The triglyceride levels signi cantly decreased in both the C and E groups. In addition, the LDL-C levels signi cantly decreased in the E group. (d) The abundance ofBi dobacterium animalisincreased two-fold in the C group and forty-fold in the E group. (e) Plasma-targeted metabolomic analysis showed that, after eight weeks ofBL-99supplementation, the increases in DHA, adrenic acid, linoleic acid, and acetic acid and decreases in glycocholic acid and glycodeoxycholic acid in the E group were signi cantly higher than those in the C group. (f) Spearman correlation analysis showed that there was a signi cant positive correlation betweenBi dobacterium animalis' abundance and SCFAs, PUFAs, and bile acids. (g) There

weeks ofBL-99supplementation, the increases in DHA, adrenic acid, linoleic acid, and acetic acid and decreases in glycocholic acid and glycodeoxycholic acid in the E group were signi cantly higher than those in the C group. (f) Spearman correlation analysis showed that there was a signi cant positive correlation betweenBi dobacterium animalis' abundance and SCFAs, PUFAs, and bile acids. (g) There was a signi cant correlation between the most signi cantly regulated metabolites and indicators related to sports performance and lipid metabolism. (4) Conclusions: Eight weeks ofBL-99supplementation combined with training may help to improve lipid metabolism and sports performance by increasing the abundance ofBi dobacterium, which can promote the generation of short-chain fatty acids and unsaturated fatty acids, and inhibit the synthesis of bile acids. Nutrients2023,15, 4554.

Nutrients2023,15, 4554 2 of 18 Keywords: Bi dobacterium;BL-99; short chain fatty acid; lipid metabolism; sports performance; cross-country skiers 1. Introduction Probiotics are de ned by the FAO (Food and Agriculture Organization of the United Nations) and the WHO (World Health Organization) as live microorganisms that, when ad- ministered in adequate amounts, confer a health bene t on the host [1]. The main bene cial effects of probiotics relate to gastrointestinal (GI) symptoms, energy metabolism, immu- nity, nutrient absorption, and the regulation of oxidative stress [2–4].Bi dobacteriumare commensal microorganisms of the human gastrointestinal tract that are generally regarded as safe bacteria and widely used in functional foods and medicine [5,6].Bi dobacterium's biochemical roles in the human body include inhibiting the growth of harmful bacteria, synthesizing essential vitamins, promoting the absorption of minerals, generating organic acids (such as acetic acid, propionic acid, butyric acid, and lactic acid), and stimulating the immune system [7]. Their regulation of lipid metabolism is considered valuable for general health. In one study, fty-one metabolic syndrome patients were divided into a control group and probiotic group; the probiotic group consumed fermented milk with Bi dobacterium lactisHN019 for 45 days. Compared with the baseline values and values in the control group, the probiotic group showed signi cant decreases in body mass index (BMI), T-CHO, LDL, tumor necrosis factor- (TNF- ), and interleukin-6 (IL-6) [8]. However, the mechanism by whichBi dobacteriumregulate lipid metabolism remains unclear. Probiotics are considered a safe strategy for optimizing the health, sports performance, and recovery of athletes, especially endurance athletes [9]. Research on the application of Bi dobacteriumin sports has increased in recent years. Eleven weeks of supplementation withLactobacillusandBi dobacteriumcould reduce the frequency and severity of gastroin- testinal symptoms during exercise training and competition, and improve or maintain healthy intestinal barrier function [10]. An intervention that combinedBi dobacterium OLP-01 (isolated from an elite Olympic athlete) with a six-week exercise training program signi cantly improved grip strength and fatigue-associated indices (lactate, ammonia, creatine kinase (CK), lactate dehydrogenase (LDH), and glycogen content) [11]. It was reported that a combination ofStreptococcus thermophilusandBi dobacteriumattenuated the range-of-motion decrements occurring after muscle-damaging

or maintain healthy intestinal barrier function [10]. An intervention that combinedBi dobacterium OLP-01 (isolated from an elite Olympic athlete) with a six-week exercise training program signi cantly improved grip strength and fatigue-associated indices (lactate, ammonia, creatine kinase (CK), lactate dehydrogenase (LDH), and glycogen content) [11]. It was reported that a combination ofStreptococcus thermophilusandBi dobacteriumattenuated the range-of-motion decrements occurring after muscle-damaging exercise [12]. Another study involving six weeks ofBi dobacterium longum35,624 supplementations in female swimmers did not show any effects on exercise performance or immune function, but the regimen did appear to alter cognitive function [13]. The results of probiotic interventions have been varied, possibly due to the use of different probiotic strains or multiple strains, differences in the time and dose of supplementation, or the use of different athletic cohorts [10]. The role ofBi dobacteriumin improving exercise performance needs further research and ex- ploration. It is generally con rmed thatBi dobacteriumplays an important regulatory role in lipid metabolism [14]. During exercise, the energy supply ratio of sugar and fat varies with the duration and intensity of exercise. During exercise, according to the difference of intensity and time, the energy supply ratio of glucose and lipid is different. Long-chain and medium-chain fatty acids can be important fuel for energy expenditure during long-term endurance exercise [15]. With the development of metagenomics and metabolomics, it provides us more possi- bilities to explore the effect ofBi dobacteriumsupplementation on lipid metabolism and exercise performance. Physiological and biochemical demands might be more crucial in intense endurance events due to factors such as the intensity and length of the events and the temperature, and probiotics could be an important tool for improving overall health, performance, and energy availability [16]. We aimed to examine the effects of 8 weeks of Bi dobacteriumsupplementation on cross-country skiers' lipid metabolism and exercise performance and the relationship between them by metabolomics and metagenomics.

Nutrients2023,15, 4554 3 of 18 2. Materials and Methods 2.1. Participants and Group Sixteen national top-level male cross-country skiing athletes were recruited from the Shanxi Provincial Winter Sports Management Center. The average age of all the participants was 19.4 0.9 years old, and the average length of their professional athletic training careers was 7.6 3.7 years. After the initial recruitment process, a baseline examination of the athletes was conducted. The exclusion criteria included a history of cerebrovascular disease, hypertension, diabetes, impaired liver/kidney function, dairy allergy, digestive tract disorders, cardiovascular diseases, and metabolic disorders. All the participants signed informed consent forms before taking part. The study was approved by the Ethics Committee of the National Institute of Sports Medicine (approval no.: 202106); International Clinical Registration Number: ChiCTR2300069187. The 16 participants were randomly divided into a C group (control,n= 8) and E group (experiment,n= 8) using a randomization table generated in Microsoft Excel. One subject was unable to complete the follow-up measures due to injury, and fteen subjects completed the trial. This was a single-blind randomized controlled trial. The baseline information of each group is shown in Table. Table 1.Baseline information of the participants. Index C Group ( n= 8) E Group ( n= 7) Age (years) 19.3 0.7 19.6 1.1 Training years 7.3 0.3 7.5 0.3 Height (cm) 178.6 5.5 176.1 3.7 Body mass (kg) 59.5 8.4 59.9 5.2 Fat mass (kg) 3.4 1.3 3.5 1.1 Muscle mass (kg) 31.8 4.5 32.0 1.2 Body Mass Index (BMI) (kg/m 2 ) 18.6 2.1 19.2 1.1 2.2. Probiotic Supplementation Program The C group only received ordinary yogurt and the E group received the same yogurt with the addition of 1 10 9 CFU ofBi dobacterium animalissubsp.LactisBL-99(BL-99). The supplementary solution was administered four times per day, being taken with each of three meals and at 21:00 before going to sleep. The supplementation period lasted for 8 weeks. The participants in each group were asked not to consume other yogurts or yogurt-containing foods during this study. All participants did not use other nutritional supplements during the intervention. We did not change the daily dietary habits

per day, being taken with each of three meals and at 21:00 before going to sleep. The supplementation period lasted for 8 weeks. The participants in each group were asked not to consume other yogurts or yogurt-containing foods during this study. All participants did not use other nutritional supplements during the intervention. We did not change the daily dietary habits of the participants. 2.3. Energy Intake and Expenditure 2.3.1. Dietary Records All the participants maintained their usual dietary habits throughout the experiment, except for the intake of dairy products being prohibited for one week prior to the ex- periment. The dietary analysis was conducted by the weighted food records based on a 2-day food diary (2 random days per week). Fluid consumption and snack intake were also recorded on the same day. Daily nutritional intake was analyzed using the Dietary Analysis and Management System for Athletes (developed by the National Institute of Sports Medicine, Beijing, China). 2.3.2. Training Load and Energy Expenditure during Training The Firstbeat Sport Sensor and Bodyguard 2 (Firstbeat Technologies Oy, Jyväskylä, Finland) were employed to monitor training load and energy expenditure during training. Training impulse (TRIMP) is an indicator generated by the FirstBeat algorithm, used to quantify the training load accumulated during a session; this was calculated based on

Nutrients2023,15, 4554 4 of 18 the athlete's heart rate reserve and the exercise duration of the session. TRIMP takes into account the intensity of exercise as calculated using the heart rate (HR) reserve method and the duration of exercise. 2.4. Body Composition Body composition was measured using an InBody 570 Bioelectric Impedance Analyzer (InBody Corp., Seoul, Republic of Korea) every Monday morning. 2.5. Maximal Oxygen Consumption (VO2max) During the test, all the participants were equipped with a metabolic system (SCHILLER ERGO AT104, Schiller, Switzerland) and were subjected to an increasing intensity exercise load test on a treadmill. The experimental protocol is mainly referring to Gasparini's [17] and has been modi ed appropriately based on our laboratory protocol. The participants warmed up for three minutes at a speed of 1 km/h with a slope of 0 on the treadmill, and then, the load was increased by 1 km/h in terms of the speed and 1 degree in terms of the slope, with each round of load intensity maintained for one minute. When the running speed reached 14 km/h and the slope reached 12.5%, the participants were required to sprint until exhausted. The test was automatically terminated once two of the following three criteria were met: A. their heart rate was more than 180 beats per minute; B. even with encouragement, the participant was unable to maintain the predetermined intensity; and C. VO2maxhad been reached, and real-time VO2began to decrease. 2.6. Isokinetic Muscle Strength Test The isokinetic muscle strengths of the ankle joint and knee joint were quanti ed using an IsoMed 2000 Dynamometer (D. & R. Ferstl GmbH, Hemau, Germany). Before commencing the test, the participants completed 3 duplicate practice trials. The protocol included an ankle and knee joint exion and extension ability test at angular velocities of 60 /s and 180 /s, with 5 repetitions. 2.7. Hematological–Biochemical Analysis In related to the condition of blood collection, the fasting states blood tests were assigned on the 1st day morning of the meso-cycle, which in this case were on the Mondays of the 1st & 9th week. In addition, training sessions were

extension ability test at angular velocities of 60 /s and 180 /s, with 5 repetitions. 2.7. Hematological–Biochemical Analysis In related to the condition of blood collection, the fasting states blood tests were assigned on the 1st day morning of the meso-cycle, which in this case were on the Mondays of the 1st & 9th week. In addition, training sessions were proceeded on Mondays through Saturdays weekly, and each Sunday was a designated resting day regardless of the weekly training load. Thus, choosing Monday as the blood-collecting day allows us to avoid possible errors due to training-related acute physiological responses. Blood samples were collected into 4.5 mL coagulation-promoting tubes. The blood samples were centrifuged at 3500 R/min for 15 min. Serum samples were analyzed using a Mindray BS420 Biochemical Analyzer (Shenzhen Mindray Scienti c Co., Ltd., Shenzhen, China) to detect albumin (ALB), globulin (GLOB), total cholesterol (T-CHO), triglycerides (TG), high-density lipoprotein (HDL-C), and low-density lipoprotein (LDL-C). 2.8. Fecal Metagenomic Analysis (1)Extraction of microbiome DNA and metagenome library preparation The samples were subjected to quality control according to the sample type and product requirements. Genomic DNA was randomly fragmented. The fragmented ge- nomic DNA was selected according to a certain average size, subjected to end-repair, and then 3 0 adenylated. Adaptors were then ligated to the ends of these 3 0 adenylated fragments. The PCR system and program were con gured and set up to amplify the product. The corresponding library quality control protocol was selected depending on the product requirements. Single-stranded PCR products were produced via denatura- tion. Single-stranded circular DNA molecules were produced and replicated via rolling cycle ampli cation, and a DNA nanoball (DNB), which contains multiple copies of DNA, was generated. DNBs of suf cient quality were then loaded into patterned nanoarrays

Nutrients2023,15, 4554 5 of 18 using the high-intensity DNA nanochip technique and sequenced through combinatorial probe-anchor synthesis (cPAS). (2)Bioinformatic Analysis All of the raw data were trimmed, and the host-originating reads were removed (only for samples of host origin). High-quality reads were de novo assembled, and contigs less than 300 bp in length were discarded. Genes were predicted and redundant genes were removed with an identity and coverage cut-off of 95% and 90%, respectively. Signi cant dif- ferences in alpha diversity between the groups were determined using estimated marginal means analysis applied to a linear mixed model, built with alpha diversity as the response variable, the different groups and time points as the predictor variables, and subject number as a random variable. To generate the annotation information, the protein sequences of the genes were aligned against the functional database KEGG with an E value cutoff of 1 10 5 . Differentially enriched KEGG pathways were identi ed. 2.9. Targeted Metabolomic Analysis of Blood In related to the condition of blood collection, the fasting states blood tests were assigned on the 1st day morning of the meso-cycle, which in this case were on the Mondays of the 1st & 9th week. In addition, training sessions were proceeded on Mondays through Saturdays weekly, and each Sunday was a designated resting day regardless of the weekly training load. Thus, choosing Monday as the blood-collecting day allows us to avoid possible errors due to training-related acute physiological responses. Blood samples were collected into 1 mL centrifuge tubes containing EDTA for plasma. The analytical instrument for this experiment was an LC-MS QTRAP 6500+ (SCIEX). The samples were analyzed in both positive and negative ion modes using a spray voltage of 4.5 kV and a capillary temper- ature of 350 C. The mass scanning range was set at 50–1500m/z. The nitrogen sheath gas and nitrogen auxiliary gas were set at ow rates of 30 L/min and10 L/min, respectively. The HPLC-MS system was run in binary gradient mode. The mobile phase consisted of (A) a 0.1% formic acid aqueous solution and (B) a mixed acetonitrile–isopropanol solution. The

temper- ature of 350 C. The mass scanning range was set at 50–1500m/z. The nitrogen sheath gas and nitrogen auxiliary gas were set at ow rates of 30 L/min and10 L/min, respectively. The HPLC-MS system was run in binary gradient mode. The mobile phase consisted of (A) a 0.1% formic acid aqueous solution and (B) a mixed acetonitrile–isopropanol solution. The gradient was set as follows: 0–1 min (5% B), 1–5 min (5–30% B), 5–9 min (30–50% B), 9–12 min(50–78% B), 12–15 min (78–95% B), 15–16 min (95–100% B), 16–18 min (100% B), 18–18.1 min (100–5% B), and 18.1–20 min (5% B). The ow rate was set to 0.2 mL/min. The pooled QC sample was injected ve times at the beginning to ensure system equilibrium, and then, it was injected every ve samples during plasma sample detection to further monitor system stability. A Waters' BEH C18 column (2.1 mm 10 cm, 1.7 m, Waters) was used for all the analyses. The scaling method used in the PCA analysis is pareto correction, and the transformation method used is the log correction. Two hundred RPT was performed to avoid model over- tting, and the VIP of each metabolite was obtained. Since univariate analysis is the simplest and most commonly used method for analyzing differential metabolites between two groups, the univariate analyses were also performed with fold change (FC) analysis and T-test to obtain FC value andpvalue using the R package metaX [18], respectively. For differential metabolites, metabolic pathway enrich- ment analysis was carried out based on the KEGG database, and metabolic pathways with p< 0.05 were signi cantly enriched by differential metabolites. 2.10. Data Analysis SPSS 23.0 statistical analysis software was used to analyze the conventional indices. The data are shown as the mean standard deviation (mean SD), withp< 0.05 as the signi cance level. The Shapiro–Wilk test was used to test the normality of the data, and the repeated measure analysis of variance was used. Two-way ANOVA (time and supplementation) were used to compare the differences between groups. If there was an interaction effect between the time point and theBL-99supplementation, we continued

mean standard deviation (mean SD), withp< 0.05 as the signi cance level. The Shapiro–Wilk test was used to test the normality of the data, and the repeated measure analysis of variance was used. Two-way ANOVA (time and supplementation) were used to compare the differences between groups. If there was an interaction effect between the time point and theBL-99supplementation, we continued with simple main effect analysis. If there was no interaction effect, we continued with main effect analysis. Signi cance was de ned asp< 0.05. The data are presented as the mean SD. In addition, effect size estimates (Cohen's d) were calculated to assess and categorize

This study investigates the effects of Bifidobacterium lactis BL-99 on lipid metabolism and performance in cross-country skiers.