Nine studies all with longitudinal design were identified as eligible by presenting data about the impact of intermittent fasting schemes on gut microbiota.

At the phylum level, Firmicutes and Bacteroidetes increase throughout follow-ups, while 16 bacteria genera change their abundance in response to intermittent fasting. Finally, some genera associated with clinical predictors such as weight change, abdominal circumference, and metabolic variables were reported.

Changes induced by fasting schemes positively impact the diversity and abundance of gut microbiota and the biomarkers described here. However, the changes previously reported have been studied in short periods and some return to their basal state after fasting intervention.

Keywords: diversity; intermittent fasting; microbiota; obesity; weight loss. CAF , Pakistan groups PBF vs. PAF , and the total subject TBF vs. A questionnaire was established to acquire personal and other measurement information, such as family background and dietary habits, to further collect individualized data.

As previously reported, a 3 days h food dietary recall was defined for the consumption of total foods and beverages Schröder et al. Selected foods included vegetables, grains, poultry meat, livestock meat, leaf vegetables, eggs, seafood, beans, fruits, dairy, nuts, milk, and sweets.

This questionnaire was also used to assess the dietary record of the last 6 months for each individual. Participant background, age, gender, dietary habits and antibiotic usage were all noted before sampling. A software was developed by Peaking Union Medical college and West China Centre of Medical sciences CDGSS3.

Principal coordinate analysis PCoA was used to measure the beta diversity of food components in the diet of each ethnic group by R software version 3. Fecal samples were collected for all participants on the same day.

Sample collection before fasting was conducted on the morning of May 15, , while samples after fasting were retrieved on the morning of June 15, An ND Nanodrop spectrophotometer Thermo Fisher Scientific, Waltham, MA, United States develop by the United States, was used to determine the DNA content.

A library of the 16S metagenomic sequencing was prepared according to Illumina guidelines. Library construction and amplification of bacterial 16S rRNA gene were performed by metagenomic sequencing. The Thermal Cycler ABI, Thermo Fisher Scientific was utilized for the amplification of HiFi HotStar ReadyMix 2× KAPA , final reaction 25μl includes microbial DNA using 2.

The cycling parameters were as the following: i initial denaturation at 95°C for 3 min, ii 25 cycles of denaturation at 95°C for 30 s, annealing at 55°C for 30 s, and elongation at 72°C for 30 s, and iii final extension at 72°C for 5 min. DNA sequencing was conducted by the use of MiSeq Reagent Kit v3 Illumina, San Diego, CA, United States.

Raw reads were loaded into the European Nucleotide Archive under the succession number PRJEB 1. Sequencing data were submitted to quality control and bioinformatics analysis accuracy. The original off-machine data filtering was improved to obtain high-quality data.

For this, the software TrimGalore of version 0. FLASH2 software was also used to merge sequences from the splicing of paired-end sequences. Moreover, Mothur version 1. Lastly, USEARCH software version Representative sequences were classified according to the Database Project of Ribosome Cole et al.

Mothur software was again used for alpha diversity analysis including Chao1, observed species, ACE, Shannon, Simpson, and coverage among groups. To assess the beta diversity, principal coordinate analysis PCoA based on Bray-Curtis distances was performed by R software version 3.

VENN analyses and rarefaction curves were calculated at the OTU level using the R version 3. Significant species among the different groups were observed by Linear discriminate analysis effect size LEfSe Segata et al.

Statistical analysis was performed on alpha diversity, dietary, and taxonomic data. CAF, PBF vs. PAF, TBF vs. TAF and the Mann-Whitney U test was applied to comparisons between ethnic groups CBF vs.

PBF, CAF vs. The SPSS version PCoA analysis to identify differences in dietary profile revealed divergence among ethnic groups CBF vs. PBF and CAF vs. PAF, Supplementary Figure S1 , but considerable overlap in dietary intake within fasting groups PBF vs.

PAF, CBF vs. CAF, and TBF vs. TAF; Figure 1. The average daily food intake for fasting groups and the respective energy ratios and total energy provided by respective macro-nutrients i.

Within the Chinese fasting groups Table 1 , we observed a significant decrease in the intake of other vegetables and beans, whereas poultry intake increased after fasting CBF vs. Within the Pakistani fasting group, grain intake and consumption of seafood, other vegetables, and vegetable supplements were all significantly increased after fasting PBF vs.

Regardless of ethnicity, the total population after fasting had a significantly higher poultry intake compared with their intake prior to fasting.

The respective energy ratios showed that CHO provides the main source of energy, followed by fats, then proteins comprising the smallest proportion. Figure 1. The nutrients intake profile by principal coordinate analysis PCoA of A Chinese before fasting vs. Chinese after fasting, B Pakistani before fasting vs.

Pakistani after fasting, and C Total before fasting vs. Total after fasting groups. The variance presented by each component is written in brackets using Bray-Curtis.

Table 1. Average daily food intake, total energy, and energy ratios provided by macronutrients across different Ramadan fasting groups.

The average daily food intake and the respective energy ratios for ethnic groups are presented in Supplementary Table S1 , Before fasting, Chinese participants had a significantly higher intake of grains, soy beans, and leaf vegetables with lower intake of livestock meat, fruits, and poultry compared with that of the Pakistani participants.

After fasting, the Chinese group presented significantly higher intake of grains and soybeans but lower intake of milk, other vegetables, fruits, livestock meat, poultry, sweets, and seafood compared with the Pakistani group.

We also found that the proportions of energy sources consumed by each group were significantly different between the Chinese and Pakistani groups, in that Chinese consumed significantly more CHO, while the Pakistani group consumed significantly more fats and proteins.

A total of 6,, raw reads were derived from 68 fecal samples provided by 34 subjects. Low-quality reads accounting for 9. On average, we obtained 91, high-quality reads per sample minimum: 45,, maximum: ,, SD : 27, after processing.

To identify the types and abundance of dominant bacterial taxa among the total cohort, we determined the phylum and genus level taxonomic assignments of OTUs from each sample Supplementary Figure S2. We next compared the prevalence of different taxa among fasting groups at the phylum and genus levels, and found a significant shift in these taxa before and after fasting for both ethnic groups.

Specifically, within the Chinese cohort, the abundance of Bacteroidetes decreased, while Proteobacteria increased after fasting CAF vs. CBF Figure 2A. Conversely, Bacteroidetes increased after fasting in the Pakistani group, and Firmicutes decreased PAF vs. PBF Figure 2B. Comparisons among the full study cohort revealed a strongly significant increase in the abundance of Proteobacteria after fasting TAF vs.

TBF Figure 2C. At the genus level, Dorea , Klebsiella , and Faecalibacterium were all significantly enriched after fasting in comparisons between the CBF with CAF participants Figure 3A.

By contrast, Sutterella , Parabacteroides , and Alistipes were more abundant after fasting in the Pakistani group, while Coprococcus , Blautia , Eubacterium , Streptococcus , Romboutsia , and Dialister were more abundant before fasting PAF vs.

PBF Figure 3B. TBF Figure 3C. Figure 2. Relative abundances of bacterial phyla analyzed by using a metastats test was varied among each group at phylum level.

A Chinese before fasting vs. Pakistani after fasting and C Total before fasting vs. Figure 3. Relative abundances of bacterial taxa analyzed by using a metastats test was varied among each group at genus level.

We next compared differences in the predominant phyla between ethnic groups before and after fasting. The results showed that before fasting, the Pakistani group presented a significantly higher abundance of Firmicutes and Actinobacteria compared to the Chinese group, while the Chinese participants had higher levels Bacteroidetes Supplementary Figure S4A.

Phylum level comparisons after fasting between ethnic groups indicated that Lentisphaerae and Tenericutes were significantly more abundant in the Pakistani samples Supplementary Figure S4B.

At the genus level, Several genera were enriched in Pakistani and Chinese groups, respectively Supplementary Figures S5A,B.

To account for differences in distribution species richness in addition to abundance, we used the Chao1, observed species, ACE, Coverage, Shannon, and Simpson indices to compare alpha diversity of gut microbiota between fasting groups CBF vs.

TAF, Supplementary Figure S6 and between ethnic groups CBF vs. PAF, Supplementary Figure S7. First, comparisons between fasting groups showed that among Chinese participants, the ACE was higher after fasting, while the coverage index was lower after fasting CBF vs.

CAF; Supplementary Figure S6A ; other indices showed no significant differences between fasting groups within either ethnic group CBF vs.

However, comparisons of alpha diversity between ethnic groups revealed significantly higher OTU abundance indices in the Pakistani group i. However, the Shannon and Simpson indices showed no differences between ethnic groups CBF vs. The alpha diversity showed that ethnicity rather than fasting drives differences in alpha diversity as Pakistani group presented significantly higher OTU abundance indices than Chinese group.

To investigate differences in gut microbiota diversity between individual study subjects potentially attributable to ethnicity or fasting practices, we next performed PCoA, PERMANOVA test, Venn, and LEfSe analyses.

To identify structural differences in gut microbiota all fasting group samples we conducted PCoA analysis using the Bray-Curtis model.

This analysis showed that the microbial community composition shifted only slightly in Chinese fasting group after fasting Figure 4A , whereas microbiota composition exhibited substantial divergence, with little overlap, between the before and after fasting groups of Pakistani participants Figure 4B.

This stability within the Chinese subjects before and after fasting was potentially reflected in the relative microbiota stability observed in comparisons between the total fasting groups TAF vs. TBF Figure 4C. PCoA analysis comparing ethnic groups showed that ethnicity apparently drives substantial differences in microbiota structure, indicated by the lack of overlap between communities of different ethnicities both before Supplementary Figure S8A and after Supplementary Figure S8B fasting CBF vs.

Subsequent PERMANOVA tests further supported the significant differences between ethnic groups CBF vs. PBF; CAF vs. Figure 4. Principle coordinate analysis PCoA of the overall composition of the genera communities among the fasting groups. Each sample of respective groups were represented by a different colors symbol circles like CBF, PBF, TBF orange circles , CAF, PAF, and TAF blue circles.

The percent of variation for each axis was explained and reported in square brackets using the Bray-Curtis. TAF comparisons.

Figure 5. LEfSe analysis of signature taxa in the A Chinese before fasting vs. Linear discriminant analysis report represents the Prefixes abbreviations for the taxonomic rank of each taxon: phylum p , class c , order o , family f , genus g , and species s.

Venn analysis showed that among the total 1, OTUs identified in all samples Figure 6 , OTUs were shared between the Chinese before and after fasting groups, with 85 and unique OTUs in the CBF and CAF groups, respectively.

Similarly, OTUs were shared between both Pakistani fasting groups, with OTUs unique to the PBF group, and 80 OTUs unique to the PAF group. Venn comparisons of the total fasting groups showed that OTUs were shared in between samples collected before and after fasting, with OTUs unique to the TBF group and 75 OTUs unique to the TAF group.

Venn analysis of ethnic differences showed that OTUs were shared between the Chinese and Pakistani groups prior to fasting, while were unique to the CBF group and were unique to the PBF group Supplementary Figure S12A.

Similar overlap was observed in comparisons of ethnic groups after fasting, with commonly shared OTUs, unique to CAF, and unique to PAF Supplementary Figure S12B. Figure 6. Venn diagram of unique and shared OTUs operational taxonomic units in different fasting groups.

Total after fasting. The overlaps represent the common taxa between groups, and the non-overlapping portions represent unique taxa in each group. To uncover whether latent relationships exist between the intake of specific nutrients sources and the composition of gut microbiota, we constructed a heatmap to illustrate correlations between bacterial taxa and diet.

Figure 7. In this study, we investigated whether fasting-associated dietary behavior affected shifts in gut microbiota composition among 34 healthy participants originating from China and Pakistan, using high-throughput 16S rRNA gene sequencing.

To avoid any geographic bias, study participants from different ethnic groups were all recruited from the same city of Lanzhou Gansu, China. Previous studies have reported that gut microbiota can be influenced by environment, host genetic background and ethnicity, drug intake, diet, and dietary behavior Lloyd-Price et al.

Zeb et al. However, among the changes in gut microbiota incurred by dietary behavioral patterns, the impact of fasting on gut microbiota has not been well investigated. One previous study of the effects of fasting for Ramadan on gut microbiota revealed that fasting behaviors can lead to shifts in in gut microbial community composition Ozkul et al.

However, this study was unable to capture the influence of dietary composition on these shifts, only the practice of fasting, itself, thus leaving the effects of several, potentially major contributing factors unresolved.

Furthermore, the inclusion of participants from two distinct ethnic groups can provide deeper insight into the drivers of gut microbiota dynamics. Dietary composition and behaviors have been shown to serve as strong influences that can shift gut microbiota structure David et al. Since short-term alterations in dietary behavior, such as fasting, may alter the mealtimes and meal sizes, these behaviors may thus lead to rapid metabolic changes and consequent modifications in the proportions of Firmicutes and Bacteroidetes Jumpertz et al.

At the phylum level, an increased proportion of Bacteroidetes and decreased Firmicutes were observed after fasting in the Pakistani group Figure 2B , which is in agreement with previously described effects of caloric restriction on gut microbiota in a mouse model Wang et al.

Bacteroidetes were also significantly increased in the Chinese participants after fasting. This could be at least partially explained by enrichment for anaerobic fermenting taxa capable of degrading recalcitrant substrates and converting complex polysaccharides to simple sugars for ATP production Dahiya et al.

Shifts in the ratio of Firmicutes to Bacteroidetes has been previously described as part of a response to dietary changes, genetic and age variations in the host, and disease Turnbaugh et al.

Our results indicate that fasting for Ramadan can also affect this ratio, suggesting that fasting can have implications on health. In addition, Proteobacteria were significantly enriched after fasting in the total group comparison TBF vs. TAF , which is noteworthy because enrichment of Proteobacteria has been suggested as a gut microbial signature of dysbiosis Shin et al.

In this study, we found that, at the genus level, Sutterella and Parabacteroides increased in abundance in the Pakistani group after fasting Figure 3B. The prevalence of Sutterella suggested potential metabolic benefits, in light of previous reports indicating positive impacts by this genus on glucose levels, while Parabacteroides has been described as a potential factor associated with inhibition of weight gain Zeng et al.

Within the Chinese group, Faecalibacterium and Butyricicoccus increased after fasting, which aligned with the findings of Ozkul et al. A study by Li et al. In addition, the significant enrichment of Klebsiella in the total cohort after fasting TAF suggests that gut health could also be negatively affected by fasting since the high abundance of Klebsiella has been associated with various diseases, such as neonatal necrotizing enterocolitis, multiple myeloma, and virus infections Qin et al.

However, we found significantly lower levels of genus Coprococcus after fasting in total group comparisons. This finding is also notable since previous studies have reported an association between high abundance of this genus and obesity Kasai et al.

Routy et al. The results of other studies have suggested that Akkermansia can also help inhibit obesity and ameliorate alcohol-associated cirrhosis Grander et al. In our study, we observed that the consumption of sweets was positively correlated with the prevalence of Akkermansia.

However, further study is required to clearly resolve how Akkermansia is affected by dietary intake. Further PCoA analysis of dietary composition indicated that diets differed slightly across fasting groups, but dramatically differed i. This result was highly similar to the results of PCoA analysis for gut microbiota across the respective ethnic groups.

Taken together, these findings highlight the clear contribution of diet on gut microbiota during fasting and across ethnic groups. Moreover, this study confirms the occurrence of shifts in gut microbial community triggered by dietary changes e.

Based on these results, we thus propose that ethnicity and fasting for Ramadan can alter the gut microbiota of humans, strongly mediated by changes in diet.

In agreement with other studies in humans, here we found that the dominant phyla in all groups were Firmicutes, Bacteroidetes, and Proteobacteria Schnorr et al.

We observed that phylum-level structure was distinct among ethnic groups, with a higher abundance of Firmicutes in Pakistani participants than in Chinese before fasting, which instead had a higher prevalence of Bacteroidetes.

Different relative proportions of Firmicutes and Bacteroidetes were previously reported by several studies, suggesting the potential influence of the host Mariat et al. The Faecalibacterium and Roseburia genera belonging to Firmicutes phylum are well-established butyrate producers, which is necessary for maintaining intestinal mucosa Peng et al.

Metabolites such as butyrate, short-chain fatty acids, and acetate have been reported to improve gut barrier function Peng et al. Schnorr et al. Despite the well-established, significant contribution of the ethnic background toward gut microbial alpha diversity but not beta diversity Deschasaux et al.

This observation is possibly dependent on dietary intake and diet-related behavior. In particular, ethnic groups showed significant differences in several alpha diversity indices and clear separation in beta diversity.

Pakistani group presented significantly higher OTU abundance indices i. The alteration of alpha diversity among ethic groups were also reported by Liu et al.

Future and ongoing studies will further clarify how ethnicity, which has many associated genetic, behavioral, and geographic factors, can contribute to driving the structure of microbiota in the context of regional diets and intermittent or stochastic changes in nutrient inputs.

In the light of several other studies that provide evidence of differences in microbiota diversity and composition associated with distinct ethnic groups, and under the influences of nutritional intake and environment, here we endeavor to resolve the impact of dietary behavior i.

Although the results of the study were significant but limited by the number of participants, it was necessary to further examined the influences of dietary behaviors such as fasting in a larger study cohort. Furthermore, future projects using high-throughput metabolomics, in conjunction with sequencing techniques, will provide remarkably higher resolution to our current understanding of the tripartite contributions of diet, microbiota, and their metabolites to human health.

To our knowledge, this study provides the first investigation into the influence of Ramadan fasting on gut microbiota in either Chinese or Pakistani individuals.

Our results demonstrate that, in the absence of geographic separation, significant differences exist in the structure, composition, and alpha- and beta diversities of gut microbiota in Chinese and Pakistani individuals, largely attributable to significant variations in diet.

In addition, intermittent caloric restriction associated with fasting for Ramadan only appeared to affect beta diversity and the prevalence of some signature taxa. This work provides inroads to understanding how modification to dietary behavioral patterns can influence the generally diet-driven microbiota, whose further study can potentially guide behavior- or lifestyle-based treatments for targeted enrichment of specific taxa beneficial to gut health.

The datasets presented in this article are available with reasonable requests. Requests to access the datasets should be directed to XH, School of Public Health, Lanzhou University, Lanzhou China.

The studies involving human participants were reviewed and approved by Medical Ethics Committee approval of the School of Public Health GW , Lanzhou University, China.

XH and RL conceived the study and designed the experiments. IkA and KL performed DNA extraction and drafted the manuscript. IkA, KL, SF, MH, and IzA coordinated in selecting field sampling sites and sample collection. IkA and KL analyzed the data and contributed to data interpretation.

All authors contributed to the critical revision of the manuscript, read, and approved the final manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

We gratefully acknowledge Mr. Qi Wanpeng and Miss. Zheng Xueqin for their technical assistance and Dr. Isaac V. Greenhut, Ph. Aybak, M. Effect of Ramadan fasting on platelet aggregation in healthy male subjects.

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