단기 NMN 보충이 노화-전 단계의 혈청대사, 대변 미생물군 및 텔로미어 길이에 미치는 영향

 

Nutrients, Gut Microbiome, and Intestinal Inflammation View all 27 Articles

 

Front. Nutr., 29 November 2021 | https://doi.org/10.3389/fnut.2021.756243

 

The Impacts of Short-Term NMN Supplementation on Serum Metabolism, Fecal Microbiota, and Telomere Length in Pre-Aging Phase

 

Kai-Min Niu1,2,3, Tongtong Bao1,2, Lumin Gao2, Meng Ru3, Yumeng Li1, Liang Jiang4, Changming Ye4, Shujin Wang1,5 and Xin Wu1,2,3*

 

1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences (CAS), Tianjin, China

 

2CAS Key Laboratory of Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences (CAS), Changsha, China

 

3Institute of Biological Resources, Jiangxi Academy of Sciences, Nanchang, China

 

4ERA Biotechnology (Shenzhen) Co., Ltd., Shenzhen, China

 

5Institute of Life Sciences, Chongqing Medical University (CAS), Chongqing, China

 

Aging is a natural process with concomitant changes in the gut microbiota and associate metabolomes.

노화는 장내 미생물총 및 관련 대사체 변화를 수반하는 자연적 과정입니다.

 

중요한 NAD+ 중간체인 베타-니코틴아미드 모노뉴클레오타이드는 노화과정을 지연시키는 데 점점 더 많은 관심을 불러일으키고 있습니다.

Beta-nicotinamide mononucleotide, an important NAD+ intermediate, has drawn increasing attention to retard the aging process.

 

We probed the changes in the fecal microbiota and metabolomes of pre-aging male mice (C57BL/6, age: 16 months) following the oral short-term administration of nicotinamide mononucleotide (NMN).

우리는 니코틴아미드 모노뉴클레오티드(NMN)의 경구 단기 투여 후 노화-전 수컷 쥐(C57BL/6, 연령: 16개월)의 대변 미생물총 및 대사체 변화를 조사했습니다.

 

노화에 대한 분자 게이지로서의 텔로미어 길이를 고려하여, 사전 노화 쥐와 인간 지원자(나이 45-60세)의 말초 혈액 단핵세포(PBMC)에서 이를 측정했습니다.

Considering the telomere length as a molecular gauge for aging, we measured this in the peripheral blood mononuclear cells (PBMC) of pre-aging mice and human volunteers (age: 45–60 years old).

 

Notably, the NMN administration did not influence the body weight and feed intake significantly during the 40 days in pre-aging mice.

특히, NMN 투여는 노화-전 쥐에서 40일 동안 체중 및 사료섭취에 유의한 영향을 미치지 않았습니다.

 

Metabolomics는 266개의 상향조절된 혈청 대사체와 58개의 하향조절된 혈청 대사산물을 제시했습니다.

Metabolomics suggested 266 upregulated and 58 downregulated serum metabolites.

 

We identified 34 potential biomarkers linked with the nicotinamide, purine, and proline metabolism pathways.

니코틴아미드, 퓨린 및 프롤린 대사경로와 관련된 34개의 잠재적 바이오마커를 확인했습니다.

 

Nicotinamide mononucleotide는 Helicobacter, Mucispirillum, Faecalibacterium의 증가와 함께, 대변 박테리아 다양성을 유의하게 감소시켰고(p < 0.05), 니코틴아미드 대사와 관련된 Akkermansia의 풍부함을 낮췄습니다.

Nicotinamide mononucleotide significantly reduced the fecal bacterial diversity (p < 0.05) with the increased abundance of Helicobacter, Mucispirillum, and Faecalibacterium, and lowered Akkermansia abundance associated with nicotinamide metabolism.

 

We propose that this reshaped microbiota considerably lowered the predicated functions of aging with improved immune and cofactors/vitamin metabolism.

이 재형성된 미생물군이 개선된 면역 및 보조인자/비타민 대사와 함께 노화의 전제 기능을 상당히 낮췄다고 제시합니다.

 

특히, PBMC의 텔로미어 길이는 NMN 투여 쥐와 인간에서 유의하게 연장되었습니다.

Most notably, the telomere length of PBMC was significantly elongated in the NMN-administered mice and humans.

 

Taken together, these findings suggest that oral NMN supplementation in the pre-aging stage might be an effective strategy to retard aging.

종합하면, 이러한 결과는 노화-전 단계에서 경구 NMN 보충이 노화를 지연시키는 효과적 전략이 될 수 있음을 시사합니다.

 

기본 분자 메커니즘을 풀기 위한 추가 연구와 노화에 대한 NMN의 영향을 검증하기 위한 포괄적 임상시험을 권장합니다.

We recommend further studies to unravel the underlying molecular mechanisms and comprehensive clinical trials to validate the effects of NMN on aging.

 

 

Introduction

 

The aging population is continuously increasing.

고령화 인구가 지속적으로 증가하고 있습니다.

 

2050년에는 세계적으로 60세 이상 인구가 12억 명이 넘을 것으로 예측되었습니다(1).

It has been predicted that the people over 60 years of age will be more than 1.2 billion globally in 2050 (1).

 

Elongated lifespan, however, may come with undesirable health conditions, such as organ damage, metabolic dysfunction, decreased bone density, and untoward inflammatory responses (2).

그러나 수명 연장은 장기 손상, 대사기능 장애, 골밀도 감소, 부적절한 염증 반응과 같은 바람직하지 않은 건강 상태와 함께 올 수 있습니다(2).

 

실제로 노화는 생물학적 시스템(즉, 영양소 감지, 장내 미생물 표적 조절) 개입을 통해 노화관련 기능의 적당한 감소로 느려질 수 있습니다(3).

Indeed, aging can be slowed to a moderate decline of age-related functionality via intervening in the biological systems (viz., nutrient sensing, gut microbiome-targeted modulation) (3).

 

Lifestyle adjustments like caloric restriction, time-restricted feeding, and alternate fasting, are known to improve cerebrovascular health in the elder population (4).

칼로리 제한, 시간 제한 섭식 및 대체 단식 등의 생활습관 조정은 노인의 뇌혈관 건강을 개선하는 것으로 알려져 있습니다(4).

 

연구에 따르면 니코틴아마이드 아데닌 다이뉴클레오타이드(NAD+) 수치는 포유류는 물론 벌레에서도 노화에 따라 감소하는 것으로 나타났습니다(5, 6).

Studies have shown that nicotinamide adenine dinucleotide (NAD+) levels decrease with aging in worms as well as mammals (5, 6).

 

The inhibition of NAD+ consumption and/or replenishment of NAD+ precursors are considered to retard aging and age-predisposed diseases by boosting the NAD+ levels (7, 8).

NAD+ 소비억제 및/또는 NAD+ 전구체 보충은 NAD+ 수준을 높여 노화 및 노화 경향이 있는 질병을 지연시키는 것으로 간주됩니다(7, 8).

 

Nicotinamide mononucleotide is a key NAD+ precursor that has been deemed a potentially effective, affordable, and safe anti-aging agent capable of extending the lifespan and ameliorating age-related complications (8–10).

니코틴아미드 모노뉴클레오타이드는 수명을 연장하고 연령 관련 합병증을 개선할 수 있는 잠재적으로 효과적이고 저렴하며 안전한 노화방지제로 간주되는 핵심 NAD+ 전구체입니다(8–10).

 

노화방지 활동 외에도 니코틴아미드 모노뉴클레오타이드(NMN)는 다양한 건강상 효능을 보여줍니다.

Besides anti-aging activities, nicotinamide mononucleotide (NMN) also shows a variety of health benefits.

 

Nicotinamide mononucleotide has displayed positive roles in angiogenic processes and anti-oxidative activities via the SIRT1-dependent signaling pathways (11, 12).

니코틴아미드 모노뉴클레오타이드는 SIRT1 의존적 신호전달경로를 통해 혈관신생 과정과 항산화 활성에서 긍정적 역할을 보여왔습니다(11, 12).

 

비만 쥐의 대사장애 감소는 NMN 보충에서 보고되었습니다(13, 14).

The reduction of metabolic impairment in obese mice has been reported in NMN supplementation (13, 14).

 

향상된 장 항상성은 장내 미생물총 조절을 통해 NMN 치료에서 현재 보고되었습니다(15).

Enhanced intestinal homeostasis has been currently reported in NMN treatment via regulating the gut microbiota (15).

 

An isotope labeling study has demonstrated that the gut bacteria compete with the host to consume orally delivered NMN (16).

동위원소 표지연구는 장내세균이 숙주와 경쟁하여 경구로 전달된 NMN 을 섭취한다는 것을 보여주었습니다(16).

 

Correlations have been observed between gut microbiota and age (17).

장내 미생물총과 연령 간 상관관계가 관찰되었습니다(17).

 

연령 관련 미생물 불균형은 장 투과성과 전신 염증을 유발하여, 노인 건강에 추가로 영향을 줄 수 있습니다(18).

Age-related microbial dysbiosis can induce intestinal permeability and systemic inflammation, further impacting late-life health (18).

 

In addition, inflammations can perturb the balance of the gut microbiota, which in turn shortens the lifespan (19).

또한 염증은 장내 미생물의 균형을 교란시켜 수명을 단축시킬 수 있습니다(19).

 

노화를 지연시키고 숙주 건강을 개선하기 위해 장내 미생물을 표적으로 한 개입이 수행되었습니다(20).

Gut microbiota-targeted interventions have been conducted to retard aging and improve host health (20).

 

장내 미생물총 및 관련 대사산물 조절을 통한 노화에 대한 천연 기능성식품의 예방 효과도 입증되었습니다(21).

A preventive effect of natural functional food on aging via the regulation of gut microbiota and relevant metabolites has also been demonstrated (21).

 

Gut microbiota transplantation of young donors is evident to reverse age-associated impairments in the peripheral and brain immunity, and cognitive behavior in older recipients (22).

젊은 기증자의 장내 미생물총 이식은 말초 및 뇌 면역의 노화관련 손상과 노인 수용자의 인지 행동을 회복시키는 것이 분명합니다(22).

 

장내 미생물총은 노화에 중요한 영향을 미칠 뿐만 아니라 미생물 대사산물도 수명에 중요한 역할을 합니다.

Not only the gut microbiota has vital effects on aging, but also the microbial metabolites exhibit important roles in the lifespan.

 

In recent years, metabolomics has been used to identify important biomarkers of healthy aging and longevity (23, 24).

최근 몇 년 동안 대사체학은 건강한 노화와 장수의 중요한 바이오마커를 식별하는 데 사용되었습니다(23, 24).

 

또한, 통합 대사체-미생물군 분석법은 숙주대사와 장내 미생물총 간 관계분석에서 진보를 보여주었습니다(25).

Additionally, an integrated metabolome-microbiome method displayed advances in the analysis of the relationship between host metabolism and gut microbiota (25).

 

Huang and his colleagues have revealed that long-term oral NMN administration in drinking water increased the abundance of beneficial microbes and contents of bile acid-related metabolites by combining fecal microbiome and metabolomic analysis (15).

Huang과 그 동료들은, 음용수에 장기간 경구 NMN을 투여하면 분변 미생물군집과 대사체 분석을 결합하여 유익한 미생물의 풍부함과 담즙산 관련 대사물의 함량을 증가시킨다는 것을 밝혔습니다(15).

 

텔로미어 길이는 노화 동안 감소하는 중요한 노화 바이오마커입니다(26).

Telomere length is an important aging biomarker that reduces during aging (26).

 

The administration of NMN has been proved to maintain telomere length in the liver of mice (27).

NMN의 투여는 쥐 간에서 텔로미어 길이를 유지하는 것으로 입증되었습니다(27).

 

In aging studies, murine (Mus musculus) is one of the most widely used experimental models.

노화연구에서 쥐(Mus musculus)는 가장 널리 사용되는 실험 모델 중 하나입니다.

 

Jackson 연구소는 C57BL/6J 쥐의 연령단계를 성숙한 성체(3-6개월), 중년 (10-14 개월), 노년(18-24개월)으로 정의했으며, 이는 인간의 20-30세(성인), 38~47세(중년), 56~69세(고령자)에 해당합니다.

Jackson laboratory has defined the age stages of C57BL/6J mice as mature adults (3–6 months), middle-aged (10–14 months), and old (18–24 months) which have been corresponded to the human age of 20–30 years old (mature adult), 38–47 years old (middle-aged), and 56–69 years old (old), respectively (28).

 

Research in aging is generally performed with mice not <18 months and human volunteers not <60 years old (29).

노화에 대한 연구는 일반적으로 18개월 미만의 쥐와 60세 미만 인간 지원자를 대상으로 수행됩니다(29).

 

여기에서 우리는 중년과 성숙한 성인 사이의 노화-전 단계를 쥐의 경우, 약 15-17개월, 인간 지원자의 경우 45-60세로 지정했습니다.

Herein, we designated a pre-aging stage between the middle-aged and mature adults to about 15–17 months for mice and 45–60 for human volunteers.

 

We investigated whether supplementing the NMN at a pre-aging stage could slow down the aging process.

노화-전 단계에서 NMN을 보충하면 노화 과정을 늦출 수 있는지 조사했습니다.

 

여기에서 노화-전 쥐의 혈청 대사산물과 장내 미생물총에 대한 단기 NMN 보충의 효과와 현재 연구에 등록된 노화-전 쥐와 인간 모두에서 텔로미어 길이를 조사하려고 시도했습니다.

Herein, we attempted to investigate the effects of short-term NMN supplementation on the serum metabolites and gut microbiota in the pre-aging mice, as well as the telomere length in both the pre-aging mice and humans enrolled in the present study.

 

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Materials and Methods

 

Animals and Experimental Design

 

The animal experiment was approved and conducted following the Regulations and Administration of the Committee of the Institute of Subtropical Agriculture at the Chinese Academy of Science (No.ISA-2020-18). A total of twenty 16-month-old male C57BL/6 specific pathogen-free mice (STA Laboratory Animal Co., LTD, Hunan, China) were used in the study. All the mice were housed with two mice per cage and raised under controlled conditions (temperature 25 ± 2°C, light/dark 12 h:12 h, humidity 60 ± 10%). The mice had free access to feeds and water. After 4 days of acclimatization, the mice were randomly assigned as the control group and NMN supplemented group with five replicates in each treatment (a cage/replicate). All the mice were fed a chow diet (D12450J, 17.70 kJ/g), which was purchased from the SLAC Laboratory Animal Central (Changsha, China). The control group mice were fed with water, and the NMN group mice were fed with water containing 500 mg/L (w/v) of NMN. The NMN dosage accepted in the experiment was referred to a previous study (15). The NMN-containing water bottles and cages were changed weekly. The whole experiment lasted for 40 days, the food intake and body weight were measured every 5 days, and the water intake was measured every 7 days.

 

Heat Yield Measurement

 

The heat yield of the mice was measured by an infrared camera (Seek Thermal Compact XR iOS Camera, Seek Thermal, Inc., CA, USA) at end of the experiment. The pixels of the images were measured using Image J v1.8.0, National Institutes of Health, Bethesda, Maryland, USA and presented by a histogram.

 

Sample Preparation

 

At end of the experiment, all the mice were fasted for 6 h. The fresh feces of all the mice were directly collected from the anus of the mice to analyze the fecal microbiota. The mice were induced with anesthesia by the intraperitoneal injection of 2% pentobarbital sodium (45 mg/kg body weight). The blood was taken from the enucleation of the eyeballs and collected into a 1.5 ml sterile Eppendorf tube (Eppdendorf, Hamburg, Germany), and then placed at room temperature for 30 min. The blood samples were centrifuged for 15 min at 3,000 g and 4°C, the serum was collected and stored at −80°C until further analyses.

 

Serum Metabolomics

 

The serum metabolites were determined by a commercial service in the Biotree company (Shanghai, China). Briefly, 50 μl of the serum sample was mixed with 200 μl of extracting solution containing 50% methanol and 50% acetonitrile and the two internal standards (L-leucine-5,5,5-d3, CAS:87828-86-2, trimethylamine-d9-N-oxidein, CAS: 1161070-49-0), followed by 10 min of sonication under iced conditions, and then was centrifuged for 15 min at 11,000 g and 4°C to collect the supernatant. The supernatant was subjected to Vanquish ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) platform (Thermo Fisher Scientific, Massachusetts, United States) with an ACQUITY UPLC BEH Amide (2.1 × 100 mm, 1.7 μm) chromatographic column and Q Exactive HFX mass spectrometer (Orbitrap MS, Thermos) and scanned for the positive model. The injection volume was 3 μl. The mobile phase used in the liquid chromatography (LC) elution includes solvent A (25 mmol/L ammonium acetate and 25 mmol/L ammonia in ultrapure water) and solvent B (acetonitrile) with the elution gradient as follows: 0–.5 min, 95% B;.5–7 min, 95–65% B; 7–8 min, 65–40% B; 8–9 min, 40% B; 9–9.1 min, 40–95% B; 9.1–12.0 min, 95% B. The full scan mass spectrum was obtained based on the information-dependent acquisition (IDA) mode in the control of the acquisition software (Xcalibur, Thermo Fisher Scientific). The electron spray ionization source conditions with 50 Arb sheath gas flow rate, 10 Arb Aux gas flow rate, 320°C capillary temperature, 60,000 full mass spectrometry (MS) resolution, 7,500 MS/MS resolution, 10/30/60 collision energy in normalized collisional energy mode, and 3.5 kV spray Voltage (positive) were used. For the data analysis, ProteoWizard database, Palo Alto, CA, USA was used to convert the raw data to the mzXML format, and then processed with an in-house R software, and (X) of chromatography mass spectrometry was used to detect, extract, align and integrate the peak. The peaks were normalized using an internal standard. The principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed using SIMCA-P (16.0.2, Sartorius Stedim Data Analytics AB, Umea, Sweden) to cluster the sample plots across groups. To screen the significantly different metabolic markers, univariate statistical analysis was used based on the criteria of variable importance in the projection (VIP) >1 and the fold change of metabolites <0.5 or more than 2, coupling with p-value <0.05, which was visualized by a volcano plot and heatmap plot. The relevant significant changed metabolism pathway was determined based on the database of Kyoto Encyclopedia of Genes and Genomes (KEGG).

 

Fecal DNA Extraction and Sequencing

 

Fecal samples were freshly collected and snap-frozen using liquid nitrogen and stored at −80°C. The bacterial genomic DNA was extracted using the CTAB method. The concentration was measured using a NanoDrop 2000, the purity and quality of the genomic DNA were checked by running 1% agarose gel electrophoresis. The V4 hypervariable regions of the 16S ribosomal RNA (rRNA) were amplified using 515F and 806R primers. The PCR conditions were 98°C for 1 min, followed by 30 cycles of denaturation at 98°C for 10 s, annealing at 50°C for 30 s, and elongation at 72°C for 30 s. The PCR products were purified using a Qiagen gel extraction kit (Qiagen, Germany). The amplicons were sequenced using an Illumina NovaSeq 6000 platform by a commercial service of Novogene Bioinformatics Technology Co., Ltd (Beijing, China).

 

Fecal Microbial Analyses

 

For the sequence analysis, UParse software (Uparse v7.0.1001, http://drive5.com/uparse/) was used. The sequences of similarity ≥97% were assigned to the same operational taxonomic units (OTUs) (30). The Silva database (http://www.arb-silva.de/) with the Mothur algorithm was used to annotate the taxonomic information of the representative sequences (31). The alpha diversity including observed_species, Chao1, Simpson, and Shannon was determined in QIIME (version 1.7.0) open source software (http://qiime.org/) and visualized by R software (version 2.15.3). The beta diversity includes PCA based on the OTU level, principal coordinate analysis (PCoA) based on the unweighted unifrac matrix, and non-metric multi-dimensional scaling (NMDS) based on Bray–Curtis distance were calculated in QIIME (Version 1.9.1.). Tax4Fun R package (http://tax4fun.gobics.de/) was used to analyze the predicated functions of bacterial species (32).

 

DNA Isolation and Measurement of Telomere Length

 

A non-blinded clinical trial in eight healthy men was conducted to investigate the supplementary effect of NMN on the telomere length of the peripheral blood mononuclear cell (PBMC). The male subjects enrolled in the study were selected based on the criteria based on an NMN clinical trial NCT04228640 (https://clinicaltrials.gov/ct2/show/study/NCT04228640) and a previous study (33) as follows: (1) 45–60 years old with body mass index (BMI) at a range of 18.5–30 kg/m2; (2) no allergic and metabolic diseases; (3) without any form of niacin supplement for 7 days prior to the study and for the whole test period; (4) kept consistent diet and lifestyle habits during the whole test period; (5) took NMN supplement for 90 days; (6) followed verbal and written study directions. The information of the volunteers is presented in Supplementary Table 1. All the participants were instructed to take NMN (300 mg/day/person) (34) in warm water once a day after 30 min of breakfast for a total of 90 days. The blood of all the participants was taken by a doctor at 0, 30, 60, and 90 days of NMN administration using ethylene diamine tetraacetic acid-containing anticoagulant tubes. The blood was separated into serum and PBMC for the analyses of serum cholesterol, triglyceride, and glucose contents using an automatic biochemical analyzer (Beckman Coulter AU5811) with commercial kits. The genomic DNA was extracted from the PBMC from the whole blood of mice and human samples using a FastPure Blood DNA Isolation Mini Kit V2 (Vazyme, Nanjing Vazyme Biotech Co., Ltd, China) following the manual of the manufacturer. The DNA concentration was determined using a NanoDrop 2000 spectrophotometer ThermoFisher Scientific, Waltham, MA, USA. Real-time quantitative PCR was used to assess the telomere length (TL) following the previously described methods (35, 36). Briefly, the primers of tel1b, F-CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGGTTTGGGTT, and te12b R-GGCTTGCCTTACCCTTACCCTTACCCTTACCCTTACCCT was used to amplify the telomeres (T) of the mouse and human. 36B4 primers (mouse: F-ACTGGTCTAGGACCCGAGAAG and R-TCAATGGTGCCTCTGGAGATT; human: F-CAGCAAGTGGGAAGGTGTAATCC, R-CCCATTCTATCATCAACGG-GTACAA) were used to amplify the single-copy gene (S). The relative TL was measured by comparing the ratio of T repeat copy number and S copy number, expressed as the telomere length (T/S) ratio. The clinical study was reviewed and approved by the Institute of Life Sciences, Chongqing Medical University, Chongqing. Verbal and written informed consents were obtained from each subject before the clinical study.

 

Statistics

 

Statistical analysis was conducted using Prism GraphPad 7 software (GraphPad Software Inc., San Diego, California, United States). The significant difference between the control group and the NMN group were performed based on the student's t-test with non-parametric tests.

 

Results

 

NMN Supplementation Enhanced Heat Yield in Pre-Aging Mice

 

The supplementary effect of NMN on age-associated body weight change was determined. In comparison with the control mice, the NMN-supplemented mice showed little change in body weight and feed intake (Figures 1A,B), but significantly increased the water intake (Figure 1C) on 21 days (p < 0.05). Moreover, the NMN-supplemented mice significantly increased the heat yield after 40 days (p < 0.05) (Figures 1D,E).

 

FIGURE 1

 



Figure 1. Supplementary effects of nicotinamide mononucleotide (NMN) on the body weight (A), feed intake (B), water intake (C), heat yield image (D), and histogram (E) of pre-aging mice. Values indicate mean ± SEM (n = 10). *Indicates significant difference at p < 0.05 level.

 

Effect of NMN Supplementation on Serum Metabolome in Pre-Aging Mice

 

Untargeted metabolomics was performed to analyze the effects of NMN supplementation on serum metabolites in pre-aging mice. The PCA and OPLS-DA results showed that the metabolite profiling datasets were clustered separately between the NMN group and the control group (Figures 2A,B). The permutation test indicated that the OPLS-DA model was reliable without overfitting (Figure 2C). The volcano plot displayed significant changes in the serum metabolite profiles for the NMN group. Overall, 266 metabolites were upregulated and 58 downregulated as compared with those in the control group (Figure 2D). Thirty-four significantly discriminant biomarker metabolites were selected based on the VIP value >1 and p-value <0.05 using the OPLS-DA model (Figure 3A). Specifically, among these metabolites, D-proline, pipecolic acid, and (E)-5-(3,4,5,6-Tetrahydro-3-pyridylidenemethyl)-2-furanmethanol were down-regulated, while hypoxanthine, inosine, guanine, 1-Methylnicotinamide, N1-Methyl-4-pyridone-3-carboxamide, niacinamide, nicotinamide N-oxide, 3-Formyl-6-hydroxyindole, N-acetylhistidine, N-acetyltryptophan, and 6-Hydroxy-1H-indole-3-acetamide were upregulated in the NMN group compared to the control group (Figures 3A,B). Notably, these discriminant metabolites were associated with metabolic pathways encompassing nicotinate/nicotinamide metabolism, purine metabolism, and arginine/purine metabolism (Figure 3C).

 

FIGURE 2

 



Figure 2. Supplementary effect of NMN on serum metabolome in pre-aging mice by multivariate statistical analysis. (A) principal component analysis (PCA) plot, (B) orthogonal partial least squares discriminant analysis (OPLS-DA) score plot, (C) OPLS-DA permutation test plot, and (D) Volcano plot.

 

FIGURE 3

 



Figure 3. Supplementary effect of NMN on the top 34 metabolic biomarkers and main metabolic pathways in pre-aging mice by hierarchical clustering analysis. (A) heatmap of hierarchical clustering analysis, (B) radar chart, and (C) pathway analysis (NMN group vs. control group).

 

Effect of NMN Supplementation on Fecal Microbiota in Pre-Aging Mice

 

The 16S ribosomal DNA (rDNA) gene sequencing was employed to investigate the effect of NMN supplementation on the fecal microbiota diversity and composition in pre-aging mice. The NMN supplementation significantly lowered the alpha diversity of fecal microbes based on the observed species and Chao1 α-diversity indexes (Figure 4A). The β-diversity was analyzed by performing PCA, PCoA, and NMDS plots based on the unweighted unifrac matrix, which displayed distinctly separated fecal microbiota (Figure 4B). The dominant phyla were Firmicutes, Bacteroidetes, Camilobacterota, Proteobacteria, and Desulfobacterota (Figure 5A), and the dominant genera were Dubosiella, Helicobacter, Lachnospiraccae_NK4A136_group, and Psychrobacter (Figure 5B). Of these, NMN supplementation significantly enriched the abundance of Camilobacterota and Desulfobacterota phyla, and Helicobacter, Desulfovibrio, and Turicibacter genera, and reduced the abundance of Proteobacteria phylum and Psychrobacter and Akkermansia genera. In addition to these dominant genera, NMN supplementation also enriched Mucispirillum, Colidextribacter, Candidatus_Saccharimonas, Marvinbryantia, Faecalibacterium, unidentified_Oscillospiraceae, A2, UCG-009, Oscillibacter, and Lachnospiraceae_UCG-001, but reduced the abundance of Staphylococcus, Corynebacterium, and Paenalcaligenes (Supplementary Table 2). Notably, a total of 826 core existent species were identified, while 465 and 156 unique species were observed in the control group and NMN group, respectively (Figure 5C). The predicted functional analysis further showed that NMN supplementation significantly downregulated the metabolism and human disease-related functions (at level 1), which are mainly associated with carbohydrate metabolism, lipid metabolism, glycan biosynthesis/metabolism, aging, cancers, and infectious disease (at level 2). On the other hand, NMN supplementation significantly enhanced the cellular processes and environmental information processing functions (at level 1), which are mainly involved in amino acid metabolism, energy metabolism, cofactors/vitamins metabolisms, environmental adaptation, immune system, and xenobiotics biodegradation/metabolism (at level 2) (Figure 6).

 

FIGURE 4

 



Figure 4. Supplementary effect of NMN on the fecal microbiota in pre-aging mice. (A) Alpha diversity indexes, (B) Beta diversity indexes. **Indicates significant difference at p < 0.01.

 

FIGURE 5

 



Figure 5. Supplementary effect of NMN on dominant fecal bacteria in pre-aging mice. (A) Phylum level, (B) genus level, and (C) venn diagram. *Indicates significant difference at p < 0.05 level.

 

FIGURE 6

 



Figure 6. Supplementary effect of NMN on predicted functions of fecal bacteria in pre-aging mice. (A) level 1, (B) level 2.

 

Correlation Analysis of Serum Metabolome and Fecal Microbiota With NMN Supplementation in Pre-Aging Mice

 

Based on the results of the serum metabolite and 16S rDNA sequencing results, the Spearman correlation analysis was performed to explore the association between the top 18 significantly changed bacteria (Supplementary Table 2) and 34 differentially changed serum metabolites (Figure 7). Among these bacteria, Akkermansia, Faecalibacterium, Mucispirillum, A2, Helicobacter, and Lachnospiraceae were closely correlated to the varied metabolites. The Akkermansia genus was positively correlated with pipecolic acid and (E)-5-(3,4,5,6-Tetrahydro-3-pyridylidenemethyl)-2-furanmethanol, and negatively correlated with the other metabolites. Faecalibacterium, Mucispirillum, A2, Helicobacter, and Lachnospiraceae were positively correlated with niacinamide, nicotinamide N-oxide, mesalazine, and N1-methyl-4-pyridone-3-carboxamide, those of which are linked with nicotinate and nicotinamide metabolism. Moreover, Mucispirillum and A2 were also significantly positively correlated with hypoxanthine and inosine that are involved in purine metabolism. Taken together, the result showed that the changed bacterial structure could impact the composition of serum metabolite constitutes.

 

FIGURE 7

 



Figure 7. Correlation analysis for differentially changed bacteria and metabolites with NMN supplementation in pre-aging mice.

 

NMN Supplementation Elongates Telomere Length in Pre-Aging Mice and Humans

 

The TL of PBMC was measured using a PCR-based method. In the pre-aging mice, the length of telomere was significantly increased with 40 days of NMN supplementation (Figure 8A). A similar result was also observed in pre-aging human volunteers after 30 days of NMN supplementation (Figure 8B).

 

FIGURE 8

 

 

Figure 8. Supplementary effect of NMN on the telomere length of the peripheral blood mononuclear cell (PBMC) in (A)