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Microbiology and Biotechnology Letters

Research Article(보문)

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Molecular and Cellular Microbiology (MCM)  |  Microbiome

Microbiol. Biotechnol. Lett. 2024; 52(4): 448-461

https://doi.org/10.48022/mbl.2401.01015

Received: February 2, 2024; Revised: May 12, 2024; Accepted: June 4, 2024

Analysis of Gut Microbiota Composition in Obese and Normal Weight Algerian Women by 16S rRNA Gene Amplicon Sequencing

Kahina Gribi1,2*, Mohammed Sebaihia2, Mohammed El Amine Bekara2, Abla Djebbar 2, Manel Zeraoulia1, and Nihel Klouche-Khelil1

1Laboratory of Applied Microbiology in Food, Biomedical and Environment, Department of Biology, Faculty of Nature and Life, Earth and Universe Sciences, University Abou Bekr Belkaid of Tlemcen, Tlemcen 13000, Algeria
2Laboratory of Molecular Biology, Genomics and Bioinformatics, Department of Biology, Faculty of Nature and Life Sciences, University Hassiba Benbouali of Chlef, Chlef 02000, Algeria

Correspondence to :
Kahina Gribi,       kahina.gribi@univ-tlemcen.dz

Abstract

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The prevalence of obesity is increasing throughout the world, imposing a heavy burden on individuals, society and the economy. The gut microbiota (GM) is recognized as an important contributing factor on the development of obesity. Several studies around the world have reported differences in GM composition between obese and lean individuals. However, the GM composition of either obese (OB) or normal weight (NW) Algerian individuals are lacking. Therefore, we conducted the first study in Algeria to characterize and compare the GM composition in OB and NW adult women. Fecal microbiota of 10 Algerian women, 5 OB, with an average Body Mass Index (BMI) of 41.22 ± 5.05, and 5 NW (average BMI of 20.69 ± 0.75), from the region of Tlemcen in Algeria, were analyzed by 16S rRNA gene amplicon sequencing on NovaSeq 6000 Illumina platform. Alpha and Beta diversity analysis did not reveal significant differences between the two groups. However, the GM composition of our cohort was significantly different from that of Europeans, Americans and Asians, showing predominance of the phyla Firmicutes and Actinobacteria, whereas the phylum Bacteroidota was underrepresented. Obese individuals had a significant increase in the genera Enterococcus, Blautia, Romboutsia, Catenisphaera and Clostridium sensu stricto 1, and a reduced abundance of the genera Bifidobacterium, Ligilactobacillus, Catenibacterium, Collinsella and Akkermansia. This pilot study revealed a distinctive GM composition in Algerian women, highlighting the need for further larger cohort studies to establish the composition of a typical GM composition in the Algerian population.

Keywords: Obesity, gut microbiota, firmicutes, actinobacteria, women, Algeria

Graphical Abstract


Introduction

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The burden of obesity is a global health concern. In 2016, the World Health Organization (WHO) estimated that more than 1,900 million adults were overweight and over 650 million were obese worldwide [1]. Obesity not only affects both the physical and psychosocial aspects of quality of life of individuals, it is also a major contributor to many chronic diseases like diabetes, cardiovascular disease, metabolic and gastrointestinal diseases, and certain types of cancer [2]. Obesity is a complex multifactorial disorder, involving genetic, environmental and lifestyle factors [3]. In recent years, the gut microbiota (GM) was also identified as a major contributing factor to the development of obesity [4, 5].

The GM refers to complex and dynamic microbial communities, formed of trillion of microbes, inhabiting the gut and play a fundamental role in maintaining human health, by contributing to several vital functions, such as host digestion, nutrient absorption, metabolism, immunity, resistance to pathogens and synthesis of vitamins [6]. With a total genome estimated to have 100 times more genes than the human genome, the GM is seen as an extra organ. On the other hand, alterations in the GM composition, called “dysbiosis”, is linked to a variety of metabolic disorders, including obesity and diabetes [7].

A large number of studies on human GM have been conducted in different parts of the world and revealed that the GM of healthy subjects is mostly composed by two dominant bacterial phyla, Firmicutes and Bacteroidota, that represent more than 90% of the total community, followed by other, but less dominant phyla, such as Actinobacteria, Proteobacteria, Fusobacteria and Verrucomicrobia [8]. Several studies have also reported that the taxonomic composition and abundance of human GM can vary among individuals or populations according to a range of factors, such as host genetics, ethnic origin, age, sex, dietary and lifestyle habits, geographic location and socioeconomic conditions [9].

The potential link between obesity and GM has attracted increasing attention in recent years, with studies revealing distinct differences in the composition of GM of obese individuals compared to those with normal weight [4, 10−14].

The GM of obese individuals is characterized by a reduced microbial diversity and an increase in the relative abundance of Firmicutes, which have a high potential to harvest energy from diet [15, 16].

Thus, understanding the GM composition in obesity is crucial for elucidating the mechanistic underpinnings this multifaceted condition, and has great potential for the development of targeted therapies. Accordingly, more studies are still needed to provide detailed information on variations of GM composition and its impacts on obesity.

To date, the compositions of GM in healthy and obese subjects are mainly reported in Western populations [4, 10, 13, 14, 17]; however, no such studies were performed on the Algerian population, where the prevalence of obesity in 2021 was estimated at 23.3% in adult men and 38.6% in adult women [18]. In order to fill this gap, we report for the first time, an analysis and comparison of the GM from NW and OB Algerian women by 16S rRNA amplicon sequencing.

Materials and Methods

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Ethical statement

This study was approved by the Ethics Committee of clinical trials at the University Hospital Center Tidjani Damerdji in Tlemcen Algeria, under the registration number CE.002.NCT.020, and was conducted following the guidelines of the Declaration of Helsinki. All participants provided a written informed consent before the collection of samples and questionnaires.

Participants characteristics and sample collection

A total of 10 volunteer women, aged between 22−47 years old, from the province of Tlemcen, located in the north west of Algeria, were recruited in this study. Participants were divided into two groups according to the WHO BMI classification, as follows: 5 controls with NW (BMI 18.5−24.9 kg/m2) and 5 OB (BMI ≥ 30 kg/m2). Exclusion criteria for both groups were: intake of antibiotics, pre and probiotics supplements and chronic or acute diarrhea within the previous 3 months, or any other gastrointestinal diseases or surgery. Medical data, dietary habits, physical activities, and family background were collected from each participant using a questionnaire. Anthropometric parameters of each participant were measured: including height, weight, and the BMI. Fecal samples were collected in sterile containers, aliquoted and immediately stored at -80℃ until being processed.

DNA extraction and PCR amplification

Genomic DNA was extracted from fecal samples using CTAB/SDS (cetyltrimethylammonium bromide/sodium dodecyl sulfate) method [19].

Concentration and purity of the DNA was assessed by electrophoresis on 1% agarose gels. DNA was diluted to 1 ng/μl using sterile water. The V3−V4 region of the 16S rRNA gene was amplified using the forward primer 341F: 5′-CCTAYGGGRBGCASCAG-3′ [20] and the reverse primer 806R: 5′-GGACTACNNGGGTATCTAAT- 3′ [21], containing barcode and Illumina Nextera adapter sequence. PCR reactions were carried out with Phusion® High-Fidelity PCR Master Mix (New England Biolabs, USA). PCR products were visualized using SYBR green on a 2% agarose gel. Amplicons with a size of 400−450 base pairs (bp) were purified with Qiagen Gel Extraction Kit (Qiagen, Germany).

Library preparation and sequencing

Sequencing libraries were generated using NEBNext® UltraTM DNA Library Prep Kit (New England Biolabs, USA) for Illumina, following manufacturer’s recommendations and index codes were added. The quality of the library was assessed on the Qubit@ 2.0 Fluorometer (Thermo Fisher Scientific, USA) and Agilent Bioanalyzer 2100 system. DNA sequencing was performed on an Illumina NovaSeq 6000 PE250 system (Illumina, USA) to generate 250 bp paired-end reads.

The raw sequence data have been submitted to the GenBank Sequence Read Archive under the Bioproject accession number PRJNA1045996, Biosamples from SAMN38468362 to SAMN38468371.

Bioinformatics Analysis

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Sequence data analysis

Sequence reads were assigned to samples based on their unique barcodes and truncated by cutting off the barcode and primer sequences. Paired-end reads were merged with the FLASH software (V 1.2.11) [22] to generate raw tags; then the raw tags were quality filtered using the fastp (V 0.23. 1) software [23], which generates high-quality clean Tags. Chimeric sequences were detected by comparing the high-quality clean tags against the SILVA reference database (http://www.arb-silva.de/) [24]; and the chimeric sequences were removed to generate effective tags using the vsearch package (V 2.16.0, https://github.com/torognes/vsearch) [25].

ASVs denoise and species annotation

The effective tags were denoised and clustered into amplicon sequence variants (ASVs) using DADA2 [26] in the Quantitative Insights into Microbial Ecology QIIME2 pipeline (V 202202) [27]. The species annotation was performed using QIIME2 software against the Silva database. Phylogenetic relationship of each ASV and the differences of the dominant species among different groups were performed by multiple sequence alignment in QIIME2. The absolute abundance of ASVs was normalized using a standard of sequence number corresponding to the sample with the least sequences. Subsequent analysis of alpha diversity and beta diversity were all performed based on the output normalized data. Top 10 taxa (at the phylum, genus and species level) of each group were selected to plot the distribution histogram of relative abundance in Perl through SVG function [28]. Venn diagram of the common and unique ASVs in the different groups were to the different groups was generated by the R software (V 2.15.3) [29].

Analysis of alpha diversity

Alpha diversity was measured using 5 indices, including Observed features (ASVs), Shannon, Simpson, Chao1, and Good’s coverage. All these indices were calculated with QIIME2 and displayed with R software (V 2.15.3).

Analysis of beta diversity

Beta diversity analysis was used to evaluate differences in taxa complexity between groups. Beta diversity based on weighted and unweighted Unifrac distances was calculated by QIIME2. The beta diversity was visualized using Principal Coordinate Analysis (PCoA) and Non-metric multidimensional scaling (NMDS) with ade4 and ggplot2 packages in R software (V 2.15.3).

Prediction of the functional metagenome

The prediction of the functional metagenome was performed using PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2) (V 2.3.0) [30], which is a software package in R that predicts and analyzes the metagenomic functions based on marker genes. Function prediction was performed according to 16S sequencing data based on the Cluster of Orthologous Groups (COG), Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO), Enzyme Commission (EC) numbers, and MetaCyc pathways databases.

Statistical analysis

All statistical analysis was performed using R software (V 2.15.3). Quantitative variables were presented as mean ± standard deviation (SD), and were compared between OB and NW groups using the Mann-Whitney test. Differences in alpha diversity among the groups were analyzed using the Mann-Whitney test. The global group effect based on the beta diversity values was tested using the permutational multivariate analysis of variance (Adonis) (Vegan package: Adonis function), with 999 permutations. In addition, linear discriminant analysis (LDA) Effect Size (LEfSe) was performed to detect biomarkers of each group by using the LEfSe software (V 1.1.01) [31]. The difference in the distribution of relative abundance of phyla and genera between OB and NW groups was tested using the Chi-square test. The GM functional differences between the OB and NW group were examined using t-test. The significance level was set at 5%.

Results

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Subjects and sample characteristics

In this study, we analyzed 10 fecal samples collected from volunteer women, including five OB and five NW (control group). The characteristics of the participants are given in Table 1. OB women had an average BMI of 41.22 ± 5.05 kg/m2 and a mean age of 35.80 ± 8.35 years, whereas NW women had an average BMI of 20.69 ± 0.75 kg/m2 and a mean age of 33.40 ± 8.35 years. No significant differences in age and height (p > 0.05) were observed between the OB group and the NW group. Body weight and BMI were significantly different between the two groups (p < 0.05).

Table 1 . Characteristics of the participants.

VariablesOB group (n = 5)NW (n = 5)p-value
Age (years)35.80 ± 8.3533.40 ± 9.070.67
Weight (kg)109.40 ± 12.5654.80 ± 1.300.01
Height (m)1.63 ± 0.041.63 ± 0.040.94
BMI (kg/m2)41.22 ± 5.0520.69 ± 0.75< 0.01

Variables were presented as mean ± SD. BMI: Body Mass Index, NW: normal weight group, OB: obese group, (Mann-Whitney test, p-value < 0.05 considered significant).

Sequencing output, preprocessing and taxonomic assignment

After sequencing, a total of 1,360,051 raw reads were obtained from the 10 fecal samples, with an average of 137,136 and 134,875 raw reads per sample in the OB and NW groups, respectively. After quality filtering, adaptors trimming and removal of chimeric sequences, the number of tag sequences for subsequent analysis was 76,002 nochime reads in the OB group, with an average effective rate of 55.51%; and 79,063 nochime reads in the NW group, with an average effective rate of 58.62%, and an average read length of 413 bp (Supplementary Table S1). The rarefaction curves of observed features (ASVs) for both groups reached a plateau, indicating that the majority of microbial taxa had been detected (Fig. 1A).

Figure 1.Rarefaction curves and Venn diagram for ASVs calculated in OB and NW groups. (A) Rarefaction curves for observed features (ASVs) calculated in OB and NW groups. The horizontal axis indicates the number of extracted sequences, and the vertical axis indicates the number of observed ASVs in each group. (B) Venn diagram showing the shared and unique ASVs between the OB and NW groups. NW: normal weight group, OB: obese group.

A total of 2,306 ASVs was obtained, 474 of which were shared by both groups; whereas 559 and 799 were specific to the NW and OB group, respectively (Fig. 1B).

Gut microbiota diversity

The alpha diversity indices: Observed features (ASVs) and Chao1, were higher in the OB group than in the NW group. Conversely, Shannon index and Simpson index were higher in the NW group than in the OB group; but these differences were not statistically significant (Observed ASVs: p = 0.69, Chao1: p = 0.69, Shannon: p = 0.99, Simpson: p = 0.84, Mann-Whitney test) (Fig. 2). The Good’s coverage was 100% for each group (Supplementary Table S2), indicating a high sequencing coverage in all samples to saturate the bacterial diversity.

Figure 2.Box plots of alpha diversity metrics in OB and NW groups. (A) Observed features (ASVs), (B) Shannon index, (C) Simpson index, (D) Chao1 index. NW: normal weight group, OB: obese group.

The differences in microbial compositions between the OB and NW group were analyzed by the UniFrac beta diversity distance using PCoA ordination method and NMDS (Fig. 3). Weighted (R2 = 0.08, p = 0.61, Adonis analysis) and Unweighted (R2 = 0.10, p = 0.68, Adonis analysis) UniFrac distance measure did not reveal a significant difference between the two groups. In addition, the PCoA and NMDS plots did not completely discriminate between the two groups (Fig. 3A−D).

Figure 3.Analysis of Beta diversity of gut microbiota in OB and NW groups. Principal co-ordinates analysis (PCoA) based on weighted UniFrac distance (A) and unweighted UniFrac distance (B). Non-metric multidimensional scaling (NMDS) plot based on weighted UniFrac distance (C) and unweighted UniFrac distance (D). NW: normal weight group, OB: obese group.

Gut microbiota composition and relative abundance

The relative abundance of the ten most abundant phyla, which accounted for 99% of the total sequences, is presented in Fig. 4A. Firmicutes and Actinobacteriota were the two dominant phyla in both the OB (66.1% and 29.2%) and the NW group (58.3% and 31.2%). These were followed by the Euryarchaeota, Verrucomicrobiota, Cyanobacteria, Bacteroidota, Proteobacteria, Desulfobacterota, Campilobacterota and Chloroflexi.

Figure 4.The relative abundance of the top 10 phyla in OB and NW groups (A), the top 10 genera in OB and NW groups (B) and the top 10 species in OB and NW groups (C). The horizontal axis shows the different groups. The vertical axis indicates the relative abundance of the different bacteria, shown as columns with different colors. NW: normal weight group, OB: obese group.

The difference in the relative abundance of the phyla between the OB and NW group was statistically significant (p < 0.001, Chi-square test). The abundance of Firmicutes was higher in the OB group relative to the NW group, while the abundance of Actinobacteriota was higher in the NW group than in the OB group. In addition, the relative abundance of these two phyla showed moderate variability at the individual level in both the OB and NW groups, between 49.5% and 73.3% for Firmicutes and between 19% and 42.1% for Actinobacteriota.

On the other hand, the relative abundance analysis at the genus and species levels indicated that the GM of both the OB and NW groups were mainly composed of ten genera: Bifidobacterium (17.4%, 20.8%), Enterococcus (16%, 7.8%), Catenibacterium (2.8%, 11%), Romboutsia (8.4%, 4.6%), Ligilactobacillus (3.1%, 5.7%), Clostridium sensu stricto 1 (7.1%, 3.1%), Blautia (8%, 4.9%), Collinsella (6.1%, 8.2%), Catenisphaera (1.6%, 0.3%) and Akkermansia (0.5%, 2.8%) (Fig. 4B) and ten species: B. adolescentis (11.9%, 12.4%), Lactobacillus ruminis (2.5%, 5%), B. longum (2%, 6%), swine fecal bacterium SD-Pec10 (2.6%, 0.7%), Chlamydia trachomatis (1.6%, 0.2%), Methanobrevibacter smithii (0.8%, 1.9%), Anaerococcus vaginalis (0.1%, 0.7%), Blautia obeum (1.4%, 1.3), B. bifidum (0.6%, 0.4%) and Candidatus Melainabacteria bacterium MEL.A1 (0.4%, 0.1%) (Fig. 4C). The relative abundances of these taxa were significantly different between the OB and NW group (p < 0. 001, Chi-square test).

Identification of differentially abundant taxa in the gut microbiota

The LEfSe analysis revealed several taxa that were differentially represented in the GM of the OB and NW group. The class Alphaproteobacteria, the family Rhizobiaceae and the genus Lachnospiraceae_UCG_001 were much more enriched in the OB group (LDA score > 2 and p < 0.05) (Fig. 5A−C); whereas, the NW group was characterized by a preponderance of the species Bacteroides dorei (LDA score > 3 and p < 0.05) (Fig. 5D).

Figure 5.Linear discriminant analysis (LDA) effect size (LEfSe) analysis of GM in OB and NW groups. The results of the LEfSe analysis based on the LDA score to identify the biomarkers at (A) Class level, (B) Family level, (C) Genus level, (D) Species level. Red taxa were more abundant in OB group, green taxa were more abundant in NW group. NW: normal weight group, OB: obese group.

Analysis of the functional potential of the gut microbiota

PICRUSt2 analysis was applied to predict the functional potential of the GM of the OB and NW groups based on the classification schemes of the COG, the EC numbers, the KO and the MetaCyc databases.

Based on the COG database, two pathways related to bacterial cell division (COG0772) and ABC-type Fe3+- siderophore transport system (COG0609) and an uncharacterized conserved protein (COG1302) were increased in the OB group compared to the NW group; while, only one pathway related to glycosyltransferase involved in cell wall biosynthesis (COG0463) was enriched in the NW group (p < 0.05, t-test) (Fig. 6A).

Figure 6.Prediction analysis of the functional metagenome in OB and NW groups using PICRUSt2 based on (A) COG pathways, (B) EC numbers, (C) KO pathways, (D) MetaCyc pathways. The left figure shows the functional abundance differences between groups, and each bar in the figure represents the average abundance of the function in groups; the right figure shows the confidence of inter-groups differences. (t-test, p-value < 0.05 considered significant). NW: normal weight group, OB: obese group.

According to the EC numbers database, three enzymes including 1-acylglycerol-3-phosphate O-acyltransferase (EC:2.3.1.51), N-acylglucosamine-6-phosphate 2-epimerase (EC:5.1.3.9) and Carbamate kinase (EC:2.7.2.2) were significantly more abundant in the OB group. In contrast, three enzymes, Beta-N-acetylhexosaminidase (EC:3.2.1.52), Citrate (Si)-synthase (EC:2.3.3.1) and Methylenetetrahydrofolate reductase (EC:1.5.1.20), were more abundant in the NW group (p < 0.05, t-test) (Fig. 6B).

Based on KO database, a two-component system sensor histidine (K07718) was more enriched in the OB group, while, the enzyme murE; UDP-N-acetylmuramoyl- L-alanyl-D-glutamate--2,6-diaminopimelate ligase (K01928) was more expressed in NW group (p < 0.05, ttest) (Fig. 6C).

Based on MetaCyc pathways database, only one metabolic pathway involved in guanosine nucleotides degradation III (PWY-6608) was significantly more represented in the OB group compared to NW group (p < 0.05, t-test) (Fig. 6D).

Discussion

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In the present study, we characterized for the first time the composition of the GM from OB and NW Algerian women by using 16S rRNA gene sequencing.

The alpha diversity analysis did not reveal significant differences between the two groups. This finding is not consistent with most of the previous studies, which reported that obese had significantly lower diversity than non-obese subjects [10, 16, 32−34]. However, our results are in line with those of certain studies, which did not find significant differences in the alpha diversity between obese and non-obese subjects [13, 14, 35−38]. These conflicting results between studies with regard to the GM diversity in OB and NW individuals may be attributed to differing factors such as genetics, environment, lifestyle and dietary habits of the cohorts [39].

The results of the beta diversity analysis, using weighted and unweighted UniFrac distance measure, showed no significant difference between the OB and NW group. In addition, the NMDS and PCoA plots did not completely discriminate between the two groups. These findings suggest that GM of the OB and the NW group are similar, which is not in agreement with a large number of studies, which showed significant difference in the beta diversity between obese and healthy individuals [13, 14, 33]. However, our result is similar to other studies which found no differences between the GM composition of obese and non-obese subjects [38, 40]. It is worth noting that contradictory results in the diversity of the GM in lean and obese subjects are common between studies [41, 42].

The most pronounced feature of our study was a higher relative abundance of the phylum Actinobacteriota, occupying the second position after the Firmicutes, instead of the Bacteroidota, which were in the sixth position, in both the OB and NW group. This finding is contrary to the majority of the previous studies, which have consistently reported that human GM is primarily composed of Firmicutes and Bacteroidota, representing about 90% of all bacterial species, with a relative abundance of 60−65% and 20−25%, respectively [39, 43, 44]. However, although rare, the dominance of Actinobacteria over the Bacteroidota was also reported in very few studies on the GM of French, Saudi, Polynesian, Indian, Chinese and Russian individuals were also dominated by Firmicutes and Actinobacteria [11, 45−48].

Because the majority of studies on GM composition have focused on Western populations, with comparatively fewer from the developing countries [42, 49], our finding indicates that it is very difficult to make conclusions on the typical taxonomic characteristics of the GM of obese and lean subjects; and adds doubt to the already controversial use of the Firmicutes/Bacteroidetes ratio as a potential marker for GM dysbiosis in obese persons [50]. In fact, conflicting results between studies on the shift of the relative abundance of Firmicutes and Bacteroidetes in healthy and obese individuals were documented [42]. Although the majority of the previous studies reported that Firmicutes increased and Bacteroidetes decreased in obese compared to lean subjects [4, 15]; other studies showed either a shift in the opposite direction (higher abundance of Bacteroidetes compared to Firmicutes in obese subjects [51, 52], or an increase in both phyla in obese subjects [53] or, no difference in the abundance of both phyla between healthy and obese subjects [54−56]. These conflicting results may be explained by complex genotype-lifestyle-environment interactions; and therefore, further investigations are still needed to demonstrate how changes in the composition of the GM contribute to obesity. Accordingly, the relative abundance of the phyla Firmicutes and Actinobacteriota in the Algerian GM, in both NW and OB groups, instead of the taxonomic composition, dominated by Firmicutes and Bacteroidetes, reported in a large number of studies, can be attributed to any of the factors that are known to influence the quantitative and qualitative changes in the GM composition and function, such as genetics, diet, geographical and socio-economic conditions [39].

Having said that, it was not unexpected that the GM composition in the present study significantly differed from other studies. In fact, Algeria is both a North African and a Mediterranean country, with a Mediterranean- type diet, characterized by a high content of plantbased food, and the health benefits of which are well known [57]. Studies have indicated that diets rich in fiber, as is characteristic of the Mediterranean diet, can promote the growth of beneficial bacteria such as Actinobacteria in the gut [58, 59], which may explain in part the increased abundance of this phylum in Algerian subjects. The phylum Actinobacteria includes a diverse group of bacteria that play crucial roles in maintaining gut health [60]. One of the prominent functions of some members of this phylum in the gut is its involvement in the breakdown of dietary fibers and complex carbohydrates to produce short-chain fatty acids (SCFAs) as metabolic byproducts. SCFAs, such as acetate, propionate, and butyrate, which serve as energy sources for the colonic epithelial cells and exert anti-inflammatory effects, contributing to the overall health of the gastrointestinal mucosa [61, 62].

In addition, our analysis revealed that the distribution of the phyla Firmicutes and Actinobacteriota between the OB and NW groups was statistically significant. We found that the GM of OB women contained more Firmicutes and less Actinobacteriota compared to the NW group. The increased abundance of the Firmicutes in the OB group is consistent with previous studies [13, 63, 64]. The potential mechanism behind the association between Firmicutes and obesity lies in their capacity to extract energy from the diet more efficiently. The surplus energy may contribute to increased fat deposition and, consequently, obesity [15].

Concerning the decrease in the relative abundance of Actinobacteriota in the OB group of our study, this finding is not in agreement with many other studies, which found no significant differences in the abundance of this phylum between lean and obese subject [42]. Therefore, the role of Actinobacteria which is usually considered a minor phylum in the human GM, in health and obesity needs to be further clarified.

At the genus level, we found a notable increase in the relative abundance of the genera Enterococcus, Blautia, Romboutsia, Catenisphaera and C. sensu stricto 1 in the OB group and a decrease in the relative abundance of the genera Bifidobacterium, Ligilactobacillus, Catenibacterium, Collinsella and Akkermansia in the OB group.

The higher abundance of the genera belonging to the genera Enterococcus, Blautia, Romboutsia, Catenisphaera and C. sensu stricto 1 (phylum Firmicutes) in the OB group compared to the NW group gives support to the well-established association between members of the Firmicutes phylum and obesity [33, 65−69].

Likewise, the lower abundance of the genus Bifidobacterium in the OB group compared to the NW group is also in accordance with what has already been observed in other studies that species belonging to this genus are traditionally considered beneficial to human health, by preserving gut homeostasis and having anti-obesity effects [33, 52, 70].

The genus Collinsella was significantly reduced in the OB group. This finding is consistent with studies that suggested that the abundance of Collinsella spp. depends on the dietary intake of the host, and that the proliferation of Collinsella spp. is favored by a diet with reduced fiber content [71, 72]. Since the Algerian diet, is of a Mediterranean type, which has a high content of dietary fiber, it is tempting to speculate that this diet prevents the proliferation of Collinsella.

The other bacterial genus showing a reduction in its relative abundance in the OB group was Akkermansia. This result supports previous research showing that obese individuals had reduced Akkermansia compared to individuals with normal weight [73−75]. Members of the genus Akkermansia is known to have potential protective effects against obesity and metabolic disease, and as such, they have been proposed as a promising antiobesity probiotic candidate [76].

The polysaccharide-degrading genus Catenibacterium was also enriched in the NW group relative to the OB group. This result was consistent with a previous study which reported that the GM of Egyptian teenagers were enriched with Catenibacterium, compared to teenagers from the United States [77].

Surprisingly, we observed a lower abundance of the genus Ligilactobacillus in the OB group compared to the NW group. Ligilactobacillus is a previous member of Lactobacillus which was recently assigned to a new genus following the re-classification of the genus Lactobacillus [78]. This result was unexpected because Lactobacillus is well known as an obesity-associated taxon and its abundance was reported to be higher in the GM of patients with obesity and metabolic diseases [11, 79−81].

The LEfSe analysis showed that the genus Lachnospiraceae_ UCG_001 was enriched in the GM of the OB group, which agrees with previous studies showing that Lachnospira genus was significantly more abundant in the OB group [64, 82, 83]. Another study showed that Lachnospiraceae UCG-001 was associated with obesity, and suggested that this genus may be predictive of weight loss in overweight and obesity groups [84].

The LEfSe analysis at species level showed that the species B. dorei was significantly enriched in the NW group. B. dorei is the dominant species of the genus Bacteroides in the human GM that was shown to improve the enteric environment, by providing GM with good living conditions and having a beneficial effect on bacterial lipopolysaccharide production [85]. Our result was in line with several studies from Japan which showed that this species is abundant in lean group [12].

Although, to our knowledge, this is the first study to explore GM composition and to evaluate differences in OB and NW women in Algeria, we must however acknowledge its several limitations. Firstly, the small sample size has reduced the power of the statistical analysis, hampering the detection of statistically significant differences. Secondly, the study population was limited to a cohort of women only and to a particular region in Algeria; therefore, our results may not be generalizable to the whole Algerian population. Because of these limitations, larger cohorts studies, including both men and women and covering a larger geographic region, are warranted in the future. These studies should also investigate the potential effects of specific factors such as diet, lifestyle, clinical characteristics, medical data and medication on the GM composition.

This pilot study described for the first time the unstudied Algerian GM. However, the results did not confirm the expected hypothesis that there will be a difference in the quantitative and qualitative composition of the GM between the NW and OB groups, as indicated by both alpha and beta diversity analyses; but, it revealed a distinctive composition of GM of Algerian subjects, dominated by the phyla Firmicutes and Actinobacteriota instead of Firmicutes and Bacteroidota, both in NW and OB individuals. These results emphasize the importance of further research on the gut microbiome in relation to the North African region.

Author Contributions

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KG and MZ: Performed the experiments; KG, MS, MEB and AD: analyzed and interpreted the data; KG: Wrote the manuscript; MS, MEB, AD and NKK: reviewed and edited the manuscript; MS and NKK: Designed the research, performed the methodology and supervised the study.

Acknowledgments

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This work was supported by a grant from the Algerian Ministry of Higher Education and Scientific Research MESRS/DGRSDT. We would like to thank all the participants in this study. We also thank the nutritionist Dr. Abdelillah Bouhamed for his collaboration in this study.

References

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