Introduction

The isolation and identification of all bacteria within a specific microbial ecosystem are challenging as they require extensive culturing conditions and boundless labor and time1. Next-generation sequencing (NGS) has emerged as an effective strategy for determining microbial communities without the need for cultivation work, playing a significant role in advancing human gut microbiome research over the past two decades2,3. Notably, 16S rRNA gene amplicon sequencing offers low-cost and high-throughput advantages, making it a valuable tool for analyzing numerous samples4,5. Additionally, shotgun metagenomic sequencing provides high resolution at the species level and even enables the prediction of unknown bacteria’s taxonomic position and function6,7. However, culture-independent methods have limitations, including the inability to cultivate and directly study bacteria assembling incomplete sequences, binning errors, and the failure to capture mobile genetic elements8,9. Furthermore, it is essential to note that since NGS technology relies on genetic information to predict bacterial characteristics and functions, experimental observation and verification are necessary10. Therefore, the limitations inherent in these genome-based approaches should be considered to achieve a robust analysis of the human gut microbiome.

Bacterial culturomics is a high-throughput-oriented cultivation strategy aiming to isolate, cultivate, and identify large-scale living bacterial strains or species from environments or tissue samples, such as the human intestine11. The resulting comprehensive bacterial culture collection is valuable for analyzing viable microbial composition within an ecosystem. This approach enables experimental verification of bacterial characteristics and interactions at the strain level, along with obtaining complete genomes of individual microorganisms, thus establishing a high-accuracy reference genome database12. Previous culturomics studies have shown its potential to address or complement the limitations of conventional cultivation methods and 16S rRNA gene amplicon/shotgun metagenome sequencing13,14. However, large-scale bacterial cultivation and identification still demand significant resources and workload15. The number of samples and culture conditions are critical factors in determining project scale16, while predicting and optimizing the most efficient culture conditions for specific microbial ecosystems remains a formidable challenge17,18.

In this study, we aimed to establish a streamlined culturomics approach with limited culture conditions. We evaluated three non-selective media based on their ability to maintain microbial diversity for a 30-day incubation period. In addition, we confirmed the efficiency and effectiveness of the simplified culture conditions by isolating bacteria in a large-scale. We presented the relationship between overall bacterial species diversity, the number of isolates and samples, and the isolation efficiency based on the preincubation period. Furthermore, we compared the culturomics results with 16S rRNA gene amplicon sequencing data to demonstrate the complementarity of both approaches and their implications for human gut microbiome research. The findings from our streamlined culturomics approach with minimal culture conditions not only showed the significant diversity of isolated species but also highlighted the practical applications of this approach in understanding the human gut microbiome.

Methods

Study design and ethical approval

This study involved collecting stool samples from healthy individuals. To evaluate the preincubation media, stool samples (n = 6) were obtained from three individuals at two different time points, with approval from the Institutional Review Board of Seoul National University (IRB no. 2104/003-014). For the culturomics study, stool samples (n = 8) were collected from eight healthy individuals under approval from the Institutional Review Board of Soon Chun Hyang University Bucheon Hospital (IRB no. 2021–01-028–002). The protocols were conducted in accordance with the guidelines and regulations approved by each ethics committee. All participants provided informed and signed consent, with no biological samples collected from them other than fecal matter.

Sample collection and processing

The selection criteria for donors in this study included individuals who had resided in South Korea, had no medical history of metabolic or gastrointestinal diseases, and had abstained from fermented milk or probiotics for no less than three weeks prior to sample collection. Following the stool collection protocol of the Human Microbiome Project19, the donors were advised to store their samples immediately after defecation in a vacuum refrigerated container with a GasPak EZ anaerobe container system (Becton Dickinson, MD, USA) at 4 °C. The samples were transported to a laboratory within 24 h. All samples were processed in an anaerobic chamber containing 5% CO2, 10% H2, and 85% N2. The specimens were homogenized with sterilized saline and centrifuged at 15,000×g for 15 min at 4 °C. The supernatants were discarded, and the pellets were resuspended in saline to a 0.25 g/L concentration and immediately used for preincubation. The remaining samples were stored at − 80 °C for DNA extraction later.

Preincubation of gut microbiota in vitro

The fecal suspension was mixed in 1–2 mm polysaccharide gel beads composed of 2.5% gellan gum, 0.25% xanthan gum, and 0.2% sodium citrate (w/v, Sigma-Aldrich, MO, USA) for long-term cultivation20. These fecal gel beads were inoculated at a final concentration of 5 g of feces/L into a preincubation medium that was supplemented with 10% (v/v) of 0.22 μm-filtered rumen fluid and 10% (v/v) of defibrinated sheep blood. Rumen fluid supplementation was used to enhance the growth and diversity of bacteria by mimicking the gut environment21. The preparation process of rumen fluid and its ingredients are described in Supplementary Fig. S1 and Table S1. To evaluate the effectiveness of the preincubation medium, gut microbiota medium (GMM), blood culture tubes (BCT; BACT/ALERT FAN plus culture bottles, BioMérieux, Marcy l’Etoile, France), and modified Gifu Anaerobic Medium (mGAM; Nissui Pharmaceutical, Tokyo, Japan) were used. Supplementary Table S2 describes the detailed constituents of each medium. Preincubation was conducted at 37 °C in an anaerobic atmosphere. The culture solution was collected every five days during a 30-day incubation period to extract DNA for 16S rRNA gene amplicon sequencing. Samples without preincubation were designated as day 0 or ‘initial.’

A streamlined bacterial culturomics approach

Our culturomics workflow is described in Fig. 1. Preincubation under anaerobic conditions was conducted at 37 °C in BCT and mGAM, supplemented with rumen fluid and sheep blood. Additionally, the same process was carried out under aerobic conditions to isolate aerotolerant and obligate aerobes simultaneously. The cultured medium was collected at regular intervals for 30 days, and then spread onto mGAM agar plates without any supplement after serial dilution in saline. We used mGAM as the sole medium for colony isolation and pure culture to enhance culturomics accessibility. To mitigate the number of species that become extinct due to dilution, we implemented a strategy to reduce the dilution factor by expanding the spreading area via a 500 cm2 square dish. The colonies were preferentially picked based on variations in colony morphology, as determined by the experimenter, with the remaining colonies being chosen randomly, which resulted in an average of 74 and 93 colonies for each plate collected from aerobic and anaerobic conditions, respectively. The isolates were identified using MALDI-TOF MS on a Biotyper Sirius system (Bruker Daltonics, Bremen, Germany). The spectra were compared with the MBT 8,468 MSPs library to obtain a score value for identification. Cases with score values below 1.69 were considered bacteria that did not have sufficient spectra or were not included in the library, such as new species. Some isolates with low scores were identified with 16S rRNA gene sequencing. Genomic DNA was extracted using Chelex 100 resin (Bio-Rad Laboratories, CA, USA), and the 16S rRNA gene was amplified by PCR using primers 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′), yielding over 1,350 bp of 16S rRNA gene. Sequencing was conducted using an ABI PRISM 3730XL DNA analyzer (Applied Biosystems, CA, USA) at Solgent (Daejeon, South Korea). Strains with less than 98.65% sequence similarity to the phylogenetically closest type strain in the 16S rRNA gene were classified as potential new species. All identified isolates were cryopreserved in 10% glycerol at − 80 °C for long-term storage.

Fig. 1
figure 1

Streamlined culturomics workflow. Blood culture tubes (BCT; BACT/ALERT FAN plus culture bottles, BioMérieux, Marcy l’Etoile, France) for aerobic and anaerobic cultivation were FA PLUS (Ref. 410,851) and FN PLUS (Ref. 410,852), respectively. mGAM, modified Gifu anaerobic medium. Created with BioRender.com.

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16S rRNA gene amplicon sequence-based analysis

The 16S rRNA gene amplicon was sequenced, targeting the V3–V4 regions using the Illumina MiSeq system (Illumina Inc., CA, USA) by Macrogen (Seoul, South Korea). Genomic DNA from the fecal suspension was extracted using a ZymoBIOMICS™ DNA Miniprep Kit (Zymo Research, CA, USA). Templates were prepared using the Illumina Nextera XT protocol with two amplification cycles and two clean-ups with AMPure XP beads (Beckman Coulter, Inc., CA, USA)22. Sequence data was processed in the Integrated Microbial Next-Generation Sequencing pipeline23, demultiplexing sequences with a minimum read length of 200 bp. Before conducting sequence pairing, we trimmed the five bp-length of each side of the sequences. Clustering zero-radius operational taxonomic units (zOTUs) with a 97% sequence similarity was performed using USEARCH v.11.0. The minimum relative abundance of zOTU cutoff was set to 0.001. Sequence alignment and taxonomic classification were conducted based on SILVA (release 128) using the RDP classifier24. Processed files were imported into R and analyzed using the Rhea script25. Microbial alpha diversity was calculated after filtering based on a cutoff of a relative abundance of 0.25% in each community, which has been suggested as an “effective” portion of the community25,26. The neutral community model (NCM) was predicted within the phyloseq package27,28.

Statistical analysis and visualization

Statistical significance between the groups was calculated using one-way ANOVA and the Kruskal–Wallis test. In beta diversity analysis, permutational multivariate analysis of variance and permutational multivariate analysis of dispersion were used to determine the significance of the group distribution. Graphical visualization was performed in GraphPad Prism v.9.4.1, except for Venn diagrams, which were generated using Venny v.2.129.

Results

Evaluation of base medium for human stool preincubation

The primary purpose of preincubation is to distribute the workload while maintaining bacterial diversity for an extended period. We used 16S rRNA gene amplicon sequencing to evaluate non-selective media, BCT, mGAM, and GMM, as base media candidates for preincubation. As a result, BCT and mGAM exhibited significantly higher effective microbial richness compared to GMM (Fig. 2a). In addition, BCT and mGAM showed significantly higher Shannon effective number of species compared to initial fecal samples and GMM (Fig. 2a). In the BCT and mGAM groups, effective microbial richness maintained a constant level throughout the incubation period. In contrast, the Shannon effective index showed a tendency to increase rapidly until about ten days of incubation (Fig. 2b). At the phylum level, BCT and mGAM showed Bacillota and Bacteroidota relative abundances similar to initial fecal samples, while GMM resulted in significant Bacillota dominance (Fig. 2c). Pseudomonadota populations increased during cultivation in BCT and mGAM. A 30-day preincubation did not induce the expansion of Actinomycetota in any tested media. We divided the incubation period into three sections and analyzed population changes at the phylum level (Fig. 2d). From the early incubation stage (Sect. 1), Bacillota dominance was observed in GMM, while Pseudomonadota population increased in BCT and mGAM. Analysis of zOTU occurrence frequency and their relative abundances using the NCM revealed rapid convergence toward a neutral process in BCT and mGAM in Sect. 1, while GMM exhibited a pattern consistent with a niche-based process and did not achieve the same level of fitness as the NCM observed for BCT and mGAM (Fig. 2e). Upon analyzing the phylogenetic distance in microbial communities between media during preincubation, BCT and mGAM groups clustered similarly to the initial gut microbiota, whereas GMM formed a distinct cluster (Fig. 2f). In addition, microbial compositions in BCT and mGAM were changed from the initial samples as the incubation period increased, with mGAM showing more pronounced shift than BCT (Fig. 2g). Overall, GMM exhibited a selective influence on microbial populations during the 30-day human stool preincubation period, while BCT and mGAM showed a gradual change in microbial composition from the initial fecal microbiota, accompanied by an increase in microbial diversity. Furthermore, to determine whether the combined use of BCT and mGAM could be advantageous for obtaining microbial diversity, we compared bacterial composition detected in each medium for 30 days (Fig. 3). The proportion of common zOTUs was 40.8% in BCT and 37.5% in mGAM during the entire cultivation period (Fig. 3a, b). BCT showed higher coverage of initial fecal zOTUs than mGAM (97.1% vs. 92.8%). Notably, the proportion of unique zOTUs was highest in the early stage (5 and 10 days of cultivation) in both media (4.6% in BCT and 5.7% in mGAM). During a 30-day incubation period, 14.6% and 12.7% of unique zOTUs were detected in BCT and mGAM, respectively (Fig. 3c). These findings suggest that using both media in parallel allows for acquiring a wider variety of bacteria than using each medium alone.

Fig. 2
figure 2

Comparison of bacterial diversity estimated by 16s rRNA gene amplicon sequence-base analysis in three nonselective media. Effective microbial richness and Shannon effective number of species (a) across media and (b) by incubation days. Relative abundances (%) of major phyla (c) across media and (d) according to the period of incubation divided into three sections: Sect. 1 (days 5 and 10), Sect. 2 (days 15 and 20), and Sect. 3 (days 25 and 30). (e) Predicted R-Squared values across the incubation period (initial and three sections), showing fitness to the NCM. Group distribution based on phylogenetical differences between (f) media and (g) by the cultivated period of each medium from initial stool samples. (a, c) Statistical significance between the groups was calculated using one-way ANOVA with the Kruskal–Wallis test. (f, g) The significance of the group distribution was determined by permutational multivariate analysis of variance (PERMANOVA) and permutational multivariate analysis of dispersion (PERMDISP).

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Fig. 3
figure 3

Venn diagrams showing unique and shared OTUs. Venn diagrams for (a) BCT and (b) mGAM showing unique and shared OTUs across three sections of cultivation period. (c) Venn diagram comparing the OTUs of the initial stool sample with those recovered in both BCT and mGAM media.

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A streamlined culturomics approach for investigating human gut microbiota

Using the streamlined culturomics approach, we obtained 11,107 isolates from stool samples of eight healthy individuals. Among these, 8141 isolates were identified, resulting in an average of 66 species per sample, comprising 27 aerotolerant and 39 non-aerotolerant species per sample (Fig. 4a). On average, 19 unique species were isolated from each donor, with an additional average of two potential novel species per sample. Notably, when frequency is defined as the number of donors from which each species was isolated, the number of species with a frequency of one was the highest at 153 (Fig. 4b), suggesting the advantages of more sample numbers for isolating bacterial diversity in this culturomics method. However, the number of identified isolates per individual, which varied from as few as 710 to as many as 1,629 (Fig. 4c), did not significantly correlate with cultured species diversity (Pearson correlation coefficient = 0.36, P = 0.38). The identified species were classified into Actinomycetota, Bacillota, Bacteroidota, and Pseudomonadota, which are known as the major phyla in the human intestine, including Fusobacteriota. Among these, Bacillota were the most predominant species across all identified subjects (Fig. 4d). Among the 263 species in the culture collection, 119 aerotolerant species were identified, including 74 unique species and one novel species candidate (Fig. 4e). The 144 non-aerotolerant species included 69 unique species, along with 11 novel species candidates (Fig. 4f). Detailed information on potential novel species isolated in this study is provided in Table 1. Subject information (age and gender) and detailed isolation numbers in each sample were described in Supplementary Table S3. Cultured bacterial species from healthy individuals were listed in Supplementary Table S4.

Fig. 4
figure 4

Cultured isolates and species information. (a) Number of species classified into aerotolerant, non-aerotolerant, unique species isolated from only one donor, and novel species candidates. (b) Number of species based on frequency, which is the number of donors from which each species was isolated. (c) Relationship between the number of species and the number of isolates in each subject. (d) Number of species in each donor at the phylum level. (e) Classification of cultured aerotolerant species into unique, non-unique, and unique and novel species. (f) Classification of cultured non-aerotolerant species into unique, non-unique, novel, and unique and novel species.

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Table 1 Novel species candidates isolated from the healthy human gut microbiota in a streamlined culturomics approach.
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Stool preincubation conditions using BCT and mGAM provided advantages, which are scattering isolation workload and obtaining a wider range of species compared to direct isolation from stool samples without preincubation (Fig. 5). Notable was the enhancement of isolated species diversity, especially under anaerobic conditions (Fig. 5a). When considering the overall efficiency of our cultivation conditions, cultivation for seven days under aerobic conditions and ten days under anaerobic conditions was the point at which we could obtain approximately 91% (91/100) and 95% (203/213) of the species identified in each condition, respectively (Fig. 5b). Notably, ten days of preincubation under anaerobic condition enabled to obtain twice the number of species (105 vs. 203) compared to the number of species obtained without preincubation. Moreover, more various species could be isolated at that point than when each medium was used alone (168 species in BCT, 163 species in mGAM). Nevertheless, some species were isolated after ten days of preincubation, and detailed isolation profiles of identified bacteria, based on preincubation medium and period, were presented in Supplementary Fig. S2 and S3. Moreover, a synergistic effect of species diversity expansion using BCT and mGAM was confirmed, enhancing species isolation by 36% and 50.7% under aerobic and anaerobic conditions, respectively (Fig. 5c). The cumulative bacterial species diversity showed a significant positive correlation with the cumulative number of samples (Pearson correlation coefficient = 0.98, P < 0.0001) (Fig. 5d).

Fig. 5
figure 5

Impact of streamlined culturomics approach on enhancing cultured bacterial species diversity. (a) Effect of preincubation on bacterial species diversity. The statistical significance between the groups was calculated using one-way ANOVA with the Kruskal–Wallis test. (b) Percentage of total species isolated according to preincubation days. (c) Venn diagrams showing the unique and shared species isolated from initial stool samples directly and after preincubation in BCT and mGAM media, respectively. (d) Relationship between cumulative sample number and cumulative species count.

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In addition, we compared the culturomics data with 16S rRNA gene amplicon sequence-based analysis results. Although the effective microbial richness level estimated in a culture-independent method was consistent across subjects (Fig. 6a), the diversity of cultured species varied among individuals (Fig. 6b). Nonetheless, a comparison of the genera identified in two methods revealed that a substantial proportion of the genera were uniquely identified by each method (Fig. 6c).

Fig. 6
figure 6

Comparison of microbial diversity between streamlined culturomics and 16S rRNA gene amplicon analysis results. (a) Effective microbial richness in 16S rRNA gene amplicon-sequence-based analysis. (b) Cultured species diversity in culturomics. (c) Proportion of genera (%) found in each approach.

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Discussion

Culture-independent techniques have significantly expanded our understanding of the human gut microbiome. However, recent emphasis has highlighted the necessity of complementing genome-based findings with culture-dependent studies and experimental validation10,11,30,31,32. High-throughput microbial identification methods, such as MALDI-TOF MS, have notably improved efficiency in culture-based bacterial ecology research11. However, the culture-dependent approach remains labor-intensive, posing challenges for gut microbiome research15. Hence, efforts are needed to reduce workload and establish streamlined culture conditions tailored to gut-derived samples. Moreover, sharing such efforts among researchers could contribute to lowering the barrier to entry for researchers interested in culture-based studies. In this context, we simplified culture conditions and evaluated the practical outcomes in culturomics.

We applied stool preincubation as an effective strategy for isolating diverse microorganisms by distributing workload11. The main factors considered for the preincubation medium were as follows. First, the medium should be non-selective to support the growth of a wide range of gut bacteria. Second, utilizing existing commercial media was preferable to enhance convenience and reproducibility. Although BCT was initially designed for microbial cultivation in clinical blood samples, it has been used in previous culturomics studies due to its suitability for a broad range of microbial cultures15,21,33. In addition, mGAM is a commercial medium initially developed for cultivating anaerobic bacteria and has demonstrated high efficacy in recovering gut microbiota18,34,35. Despite being a noncommercial medium, we compared GMM to other media as it has been widely used in gut microbiome research18,36,37,38. Consequently, GMM induced a high dominance of Bacillota, while BCT and mGAM maintained microbial diversity during a 30-day incubation period (Fig. 2). Additionally, the combined use of BCT and mGAM demonstrated a synergistic effect, particularly effective in isolating various species under anaerobic conditions (Figs. 3, Fig. 5b,c). These findings demonstrate the potential of BCT and mGAM in culturomics, focusing on gut-derived samples from healthy individuals where anaerobic bacteria predominate39.

In this study, we immobilized gut microbiota within gel beads consisting of gellan and xanthan gums20. This method was developed to sustain bacterial diversity in long-term cultures in bioreactors. The main advantage of immobilization was preserving slow-growing or temperature-sensitive bacteria (e.g., Bifidobacterium spp.), which have limited ability to compete for nutrients. By incorporating this procedure into culturomics, we aimed to maintain bacterial diversity during preincubation. For instance, we observed the recovery of some Bifidobacterium species even after seven days of preincubation (Supplementary Fig. S3). This result could be enhanced by evaluating the effects of immobilization under our conditions in the future.

Moreover, we found that preincubation up to ten days efficiently facilitated bacterial isolation (Fig. 5b). During the early stages of preincubation, we were able to isolate most novel species candidates and low-abundance gut bacteria (Supplementary Figs. S2 and S3)40. Commercial or clinical species of interest, such as next-generation probiotics, were also isolated within ten days of cultivation (Supplementary Figs. S2 and S3). However, the task of colony picking is arbitrary, and there is no standardized method to determine the colonies for picking the specific or various species. Therefore, researchers must rely on their experience, such as visible morphological differences, which is one of the significant limitations of the culture-dependent approach. Our results demonstrated that isolating more colonies does not necessarily result in obtaining more diverse species in individual samples (Fig. 4c). Consistent with previous studies16, we found a significant positive correlation between the number of samples and overall microbial species diversity (Fig. 5d). Therefore, while applying multiple cultivation conditions may be appropriate if the goal is to isolate a large number of microbial species from a single sample, increasing the number of samples is a more favorable strategy for capturing overall microbial species diversity, as demonstrated in our study with minimal conditions. Additionally, sample-specific characteristics can play a significant role in determining culture conditions for human gut-derived samples. There is variation in results due to individual differences in gut microbiota (Supplementary Fig. S4), which directly affects the outcomes of the culturomics approach.

Culture-dependent and culture-independent approaches can provide complementary perspectives on the human gut microbiota. This study compared culturomics results and 16S rRNA gene amplicon analysis results. The 16S rRNA genomic analysis provides information on species diversity based on sequence-based zOTUs, while culturomics reveals the diversity of cultivable bacterial species under the given culture conditions (Fig. 6a,b). Interestingly, a substantial proportion of genera were found only by either approach (Fig. 6c). This highlights each approach’s unique strengths and limitations. The culture-dependent approach offers information that the culture-independent approach cannot provide, such as not-yet-cultured species, bacterial viability, and low-abundance bacteria12. However, the culture-dependent approach is limited to providing information only on culturable bacteria under the applied culture conditions. Bacteria that require specific cultivation conditions or cannot be recovered under cultivation conditions may be missed. Therefore, both approaches are complementary to each other, and their strengths can be leveraged to gain a more comprehensive understanding of the gut microbiome.

One limitation of this study is that we could not quantify the total viable microbial population of the eight stool samples. While our culturomics results were compared with the 16S rRNA gene amplicon sequencing data (Fig. 6c), DNA-based analysis does not guarantee the viability of microorganisms. This led to a significant challenge in quantifying the isolation efficiency of diverse gut bacteria from the proposed simplified cultivation conditions. Using flow cytometry to distinguish live and dead cells could be an alternative approach to address this limitation41.

We introduced a streamlined culturomics approach with preincubation to investigate the human gut microbiome. This model distributed workload and reduced overall culturing labor by applying preincubation and a minimal base media, resulting in a diverse collection of 263 species from a large number of bacterial isolates. To further broaden species diversity, culture conditions can be modified by adding growth factors, incorporating antibiotics with different spectrums, or applying physical interventions. However, a high number of factors and parameters can be involved in culture conditions, and increasing the number of variables directly decreases work efficiency. Sharing culturomics research and cases with details is essential to overcoming this problem. Streamlining and optimizing culturomics protocols, developing automated cultivation technologies, and integrating machine learning can further broaden culturomics accessibility to a broader range of researchers16,17,42. Employing these strategies alongside culture-independent methods can yield novel insights into the human gut microbiome and propel microbiome research advancements.