Filling metataxonomic gaps

The term “microbial dark matter” refers to uncultured microbes that can only be detected through sequencing. However, 16S rRNA gene sequencing may miss low-abundance microorganisms due to limited sequencing depth. Although metagenomic sequencing has improved with short-read methods, excelling in sequencing depth and diversity, and long-read methods, enhancing accuracy and 16S amplicon recovery, detecting low-abundance species remains challenging. Additionally, factors such as sampling, DNA extraction, and quality control can obscure certain taxa (Bharti and Grimm Reference Bharti and Grimm2021; Liu et al. Reference Liu, Qin and Chen2021; Orellana et al. Reference Orellana, Krueger and Sidhu2023). An increasing number of studies have indicated that some bacterial taxa, especially low-abundance bacteria, are overlooked in culture-independent sequencing. For instance, Zehavi et al. (Reference Zehavi, Probst and Mizrahi2018) reported that 60% (1,012 out of 1,698) of cultured operational taxonomic units (OTUs) were absent in 16S rRNA gene sequencing results, representing rare taxa within the rumen. Whelan et al. (Reference Whelan, Waddell and Syed2020) merged culture-dependent and culture-independent sequencing technologies to investigate cystic fibrosis lung bacteria, revealing that 63.34% of OTUs were exclusively detected with culture-dependent sequencing technology, with only 5.65% detected by culture-independent methods. Goldman et al. (Reference Goldman, Sanders and Yan2022) enriched four types of vertebrate fecal samples with various culture media before 16S rRNA gene amplicon sequencing, finding 340 bacterial genera across culture-independent and culture-dependent samples, with 115 genera exclusively identified via culture-dependent sequencing, including 12 uncultured candidate genera. Li et al. (Li et al. Reference Li, Lian and Han2023b) reported similar results in their study on desert soil microbiota using cultured-based sequencing, revealing that 2,799 amplicon sequencing variants (ASVs; 74.1%) were exclusively detected through culture-dependent sequencing, and only 83 ASVs (2.2%) overlapped between culture-dependent and culture-independent sequencing. Feehily et al. (Reference Feehily, O’Neill and Walsh2023) confirmed the vertical transmission of Bifidobacteria using dual culture-based and metagenomic approaches, identifying 16 low-abundance strains solely through culture-dependent sequencing. Through five consecutive cultures of drinking water samples followed by Oxford Nanopore Technology sequencing, Fu et al. (Reference Fu, Zhang and Wang2023) demonstrated that culturing significantly improved the quality of metagenome-assembled genomes (MAGs). This approach yielded 86 high-quality MAGs, including 70 target pathogenic bacteria, whereas culture-independent methods produced only 12 MAGs.

With culturomics, the repertoire of isolated human bacterial species, particularly from the gastrointestinal tract, has rapidly expanded. Didier Raoult’s team at King Abdulaziz University systematically tracked cultured human prokaryotic species, establishing and regularly updating the repertoire through comprehensive searches of culture databases and scientific literature. Their findings revealed that in 2015, only 2,172 prokaryotic species isolates were reported from humans (Hugon et al. Reference Hugon, Dufour and Colson2015). This number increased to 2,776 in 2018 and further to 3,253 by 2020. Notably, 63% of the additional 477 species from 2018 to 2020 were isolated via culturomics (Bilen et al. Reference Bilen, Dufour and Lagier2018; Diakite et al. Reference Diakite, Dubourg and Raoult2021). Another research group led by Liang Xiao at BGI-Shenzhen focused on human gut bacteria using culturomics. In 2019, they identified 338 species from 155 fecal samples using culture-dependent whole-genome sequencing and established the culturable genome reference (CGR), the largest collection of human gastrointestinal bacterial genomes, which included 149 candidate new species (Zou et al. Reference Zou, Xue and Luo2019). By 2023, they expanded the database to CGR2, comprising 527 species, including 179 unidentified ones, of which 126 were cultured for the first time (Lin et al. Reference Lin, Hu and Chen2023). Furthermore, they cultured 195 species from human oral samples, identifying 95 potential novel ones, and established the cultured oral bacteria genome reference (Li et al. Reference Li, Liang and Lin2023c). Despite these advances, the full spectrum of human bacteriota remains to be explored through culturomics.

Initial reports of culturomics primarily focused on human subjects and have progressively expanded to include various domestic animals (i.e., chicken in Ferrario et al. Reference Ferrario, Alessandri and Mancabelli2017; cow in Zehavi et al. Reference Zehavi, Probst and Mizrahi2018; swine in Wang et al. Reference Wang, Howe and Wei2021; [Ferrario et al. Reference Ferrario, Alessandri and Mancabelli2017; Wang et al. Reference Wang, Howe and Wei2021; Zehavi et al. Reference Zehavi, Probst and Mizrahi2018]) and wildlife species (i.e., Egyptian mongoose in Pereira et al. Reference Pereira, Bandeira and Fonseca2020; (Reference Pereira, Bandeira and Fonseca2020)). Ferrario et al. (Reference Ferrario, Alessandri and Mancabelli2017) curated a collection of 420 unique bacterial strains, including isolates uncommon in the chicken gut. With systematic culturomics, Crhanova et al. (Reference Crhanova, Karasova and Juricova2019) increased the bacterial culturability in vitro to over half of the chicken cecal bacteriota. Zehavi et al. (Reference Zehavi, Probst and Mizrahi2018) reported that 23% of rumen prokaryotic microorganisms were culturable. Wang et al. (Reference Wang, Howe and Wei2021) comprehensively cultured swine gut bacteria and found that approximately 50% of total bacterial ASVs and 75% of genera and families, including several novel species, were culturable. Using 25 types of culture media in conjunction with metagenomics, Dong et al. (Reference Dong, Lin and Jing2022) expanded the gut bacteriota repertoire of weanling piglets by identifying 333 new species.

In conclusion, the key benefit of culturomics is its ability to recover bacterial taxa that are overlooked in culture-independent sequencing, thereby enhancing the resolution of bacterial community profiles and improving our understanding of the composition of complex bacterial communities. In the context of bacterial research, the integration of high-throughput methods and culture is the most efficient approach to expanding the repertoire of gut bacterial isolates. Culturomics, in particular, can facilitate the identification of numerous candidate strains for prospective experiments.

Paving the way toward bacteriotherapy

Culturomics plays an important role in clinical microbiology with its ability to improve bacterial identification, facilitate mechanistic studies of host–microbial interactions, and increase the isolation of potential pathogenic or therapeutic organisms. Using culturomics, Dubourg et al. (Reference Dubourg, Baron and Cadoret2018) identified pathogenic bacteria such as Clostridioides saudii, Clostridioides jeddahtimonense, Clostridioides culturomicsense, Butyricimonas phocaeensis, and Anaerosalibacter massiliensis, which were among the first cultured from human fecal samples. Using a non-strictly defined culturomics approach, Khanna et al. (Reference Khanna, Pardi and Kelly2016) developed SER-109, an oral microbiome therapeutic comprised of 50 spore-forming bacterial species isolated from healthy fecal microbiota transplantation donors. SER-109 successfully prevented Clostridium difficile infection and demonstrated greater safety than fecal microbiota transplantation. This finding further supports the potential of designing and developing personalized formulations that include spore formers for the transfer of obligate anaerobes. Additionally, Ghimire et al. (Reference Ghimire, Roy and Wongkuna2020) discovered that 66 out of 102 bacterial species cultured from healthy human donors inhibited C. difficile. They observed the importance of species composition and interactions in achieving effective inhibition.

Based on culturomics and metagenomics investigations of gut bacteria in individuals with kwashiorkor and healthy children, Alou et al. (Reference Alou, Million and Traore2017) identified the 12 species detected only in healthy individuals as potential probiotics. Through investigations of intestinal bacteria in two patients and two healthy individuals using culturomics, Fellag et al. (Reference Fellag, Gouba and Bedotto2020) found that four Enterococcus mundtii and Enterococcus casseliflavus strains could inhibit the growth of Mycobacterium tuberculosis, the causative agent of pulmonary tuberculosis. Future research integrating culturomics, metagenomics, and machine learning technologies will improve the identification of probiotics and their contributions to bacteriotherapy.

Creating a new method for drug screening

Li et al. (Reference Li, Kwok and Wang2023a) integrated culturomics, bionics, and metabolomics to study probiotic-driven drug metabolism. They discovered that Lacticaseibacillus casei Zhang could metabolize racecadotril into its active ingredients in a system mimicking the human intestine in vitro, capturing individual responses to the drug. However, the drug metabolism pattern may differ between a single strain and bacterial communities, with the latter being more suitable for drug screening before clinical application, as it more closely resembles the bacterial status in vivo (Shetty et al. Reference Shetty, Smidt and de Vos2019).

The non-targeted strategy of culturomics has the potential to maximally reflect the genuine status of the bacteriota from specific ecological niches, making it invaluable for drug screening and precision medicine (Li et al. Reference Li, He and Jia2016; Weersma et al. Reference Weersma, Zhernakova and Fu2020). Javdan et al. (Reference Javdan, Lopez and Chankhamjon2020) developed a BG medium by mixing modified Gifu anaerobic medium (mGAM) and Bryant and Burkey medium (BB) at a ratio of 3:7. Using this medium to screen 23 drugs in fecal sample cultures from 20 donors, they quantified the interpersonal differences in microbiome-derived metabolism. Building on the study by Javdan et al. (Reference Javdan, Lopez and Chankhamjon2020), Tao et al. (Reference Tao, Huang and Pan2023) optimized a new medium, termed GB, by mixing mGAM and BB at a ratio of 5:5 through multi-dimensional evaluation (Fig. 2), which more accurately mimics the status of the human gut bacteriota than BG. Tao et al. (Reference Tao, Huang and Pan2023) tested three representative drugs using bacteriota from 10 donors and found that individual responses to different drugs, influenced by personalized gut bacteriota, could be captured by GB. This medium can effectively capture the human fecal bacteriota in a personalized manner, providing researchers with a valuable tool that can significantly advance personalized medicine.

Figure 2.

Multi-dimensional evaluation of medium (Tao et al. Reference Tao, Huang and Pan2023).

Sample conditioning

Goldman et al. (Reference Goldman, Sanders and Yan2022) found that only 109 ASVs (5% of all detected ASVs) could be assigned to the species level and overlapped between culture-independent sequencing and culturomics. Most bacteria detected exclusively by culture-independent methods belonged to Lachnospiraceae, Ruminococcaceae, and Erysipelotrichaceae, consistent with results reported by Pfleiderer et al. (Reference Pfleiderer, Lagier and Armougom2013) (Fig. 3). These families predominantly comprise strictly anaerobic species, indicating that conditions of sample collection play a critical role in culturomics. Pfleiderer et al. (Reference Pfleiderer, Lagier and Armougom2013) recommended collecting fecal samples into containers with continuous gas generation and immediate transfer to an anaerobic chamber at 4°C.

Figure 3.

Comparison of the culture-independent sequencing and culture results. (A) The difference in 16S rRNA gene sequences was detected between fecal samples and plate contents (Goldman et al. Reference Goldman, Sanders and Yan2022). (B) The difference between pyrosequencing and culture results (Pfleiderer et al. Reference Pfleiderer, Lagier and Armougom2013).

Bellali et al. (Reference Bellali, Lagier and Raoult2019) investigated human fecal samples using flow cytometry and the plating technique, revealing that culturability was 50% when the samples were exposed to oxygen for 120 min without antioxidants, but increased to 67% when protected by a protectant medium (patented N°1H53316 CAS 25 FR; Table 1). Furthermore, maintaining samples under anaerobic conditions during processing and limiting oxygen exposure to less than 2 min resulted in an 87% culturability rate, showing no significant differences between these two techniques. Given the anaerobic nature of the gastrointestinal tract and the difficulty in culturing strictly anaerobic species, it is essential to protect gastrointestinal samples from oxygen by shortening the exposure time to oxygen and using a protectant medium.

Table 1.

Composition (g/L) of the protectant medium patented under the following number (N°1H53316 CAS 25 FR) by Bellali et al. (Reference Bellali, Lagier and Raoult2019)

Sample processing

Sample dilution exhibits a strong effect on the richness of isolated bacteria. Zehavi et al. (Reference Zehavi, Probst and Mizrahi2018) diluted cows’ rumen fluid from 10⁻¹ to 10⁻⁶ and plated samples on medium 10 (M10) and M10 supplemented with rumen fluid, revealing that sample dilution had a significant impact on increasing the richness of isolated bacteria. Notably, dilution explained a higher variance (30%) in bacterial isolation compared to the type of medium used; illustrating that serial dilution can efficiently reduce the dependence of culturability on initial abundance (Fig. 4). Increasing dilution led to changes in bacterial composition: at the phylum level, the relative abundance of Bacteroidetes decreased, while Firmicutes increased. At the order level, there was a progressive increase in Lactobacilli, Bacilli, and Enterobacteria. Yadav et al. (Reference Yadav, Nimonkar and Poddar2022) established the “two-dimensional cell separation” by combining serial dilution with gradient centrifugation, successfully isolating species at a rate more than three-fold higher compared to using dilution alone.

Figure 4.

Experimental factors affecting cultivability (Zehavi et al. Reference Zehavi, Probst and Mizrahi2018). (A) The proportion of the cultivable prokaryotic microorganisms in each rumen dilution. (B) The impact of abundance on cultivability.

Passive filtration is another useful process for isolating motile and small-sized Treponema species. Belkacemi et al. (Reference Belkacemi, Khalil and Ominami2019) demonstrated the effectiveness of a device consisting of two chambers separated by a 0.2 µm filtration membrane, which enabled Treponema movement through the membrane from the upper compartment to the lower compartment, facilitating isolation. After serial dilution and secondary isolation on agar medium, Belkacemi et al. (Reference Belkacemi, Khalil and Ominami2019) successfully obtained pure cultures of 10 strains of T. pectinovorum and five strains of T. denticola.

Harsh treatment methods are effective for isolating bacterial spores due to their higher resistance compared to growing cells. Pre-treatment with heat, chemicals, or radiation has been shown to efficiently isolate spores (Nicholson et al. Reference Nicholson, Munakata and Horneck2000). For instance, Hong et al. (Reference Hong, Khaneja and Tam2009) heated human fecal samples at 65°C for 1 h, resulting in the isolation of 88 heat-resistant bacteria when combined with serial dilution. Golnari et al. (Reference Golnari, Bahrami and Milanian2024) heat-shocked various samples, including fecal, soil, and dairy products, at 80°C for 15 min and successfully isolated 36 strains of spore-producing bacteria. Browne et al. (Reference Browne, Forster and Anonye2016) treated human fecal samples with 70% ethanol at an equal volume for 4 h, revealing that ethanol treatment profoundly changes the composition of culturable bacteria with an increase in the abundance of ethanol-resistant taxa. Afouda et al. (Reference Afouda, Hocquart and Pham2020) pretreated human stool samples with 50% ethanol (final concentration) for 1 h, demonstrating that ethanol treatment enhances the proportion of spores and complements direct culturing (Fig. 5). Sample dilution, passive filtration, and harsh treatments effectively modify bacterial community compositions within the niches, increasing the relative abundance of specific taxa and enriching the diversity of cultured bacterial species.

Figure 5.

The impact of ethanol treatment (Afouda et al. Reference Afouda, Hocquart and Pham2020).

Media customizing

Reducing the workload is essential to applying culturomics. In 2012, Lagier et al. explored 212 culture conditions with three stool samples, finding that only 70 were necessary to capture all isolated species (Lagier et al. Reference Lagier, Armougom and Million2012a). Diakite et al. (Reference Diakite, Dubourg and Dione2020) further refined these conditions in 2020 to 16 highly efficient formulations (Table 2), achieving a 98% isolation rate of cultured human gut bacteriota. The effectiveness of yeast extract-casitone-fatty acids agar (YCFA) was previously reported by Browne et al. (Reference Browne, Forster and Anonye2016). Lagier et al. (Reference Lagier, Khelaifia and Alou2016) suggested three key procedures for maximizing bacterial isolation from the human gastrointestinal tract: (i) pre-incubation in a blood culture bottle (yielding 56% of the newly isolated species); (ii) the supplementation of filter-sterilized rumen fluid during pre-incubation (resulting in 40% of the newly isolated species); and (iii) the addition of 5% sheep blood (contributing to 25% of the newly isolated species).

Table 2.

List of the 16 best culture conditions recommended for culturomics of human gut bacteriota by Diakite et al. (Reference Diakite, Dubourg and Dione2020)

The culture media used for the cultivation of gastrointestinal bacteria in pigs or chickens differ slightly from those used for humans (Table 3). The mGAM, Bifidus selective medium (BSM), Wilkins-Chalgren anaerobe broth (WCA), fastidious anaerobe agar (FAA), phenylethyl alcohol agar (PEA), modified peptone-yeast extract-glucose medium (MPYG; with or without sheep blood), and sheep blood-spore medium have been found suitable for the cultivation of gastrointestinal bacteria from pigs (Dong et al. Reference Dong, Lin and Jing2022; Lagier et al. Reference Lagier, Khelaifia and Alou2016; Mun et al. Reference Mun, Kim and Shin2021; Wylensek et al. Reference Wylensek, Hitch and Riedel2020). Wang et al. (Reference Wang, Howe and Wei2021) cultured the fecal samples from pigs at four growth stages using 53 different culture conditions, generating a heatmap to guide the isolation of specific bacterial taxa (Fig. 6). Crhanova et al. (Reference Crhanova, Karasova and Juricova2019) suggested that for the chicken cecal bacteria, nutrient broths with mono- or di-saccharides were suitable for selective culture of Lactobacillaceae. Supplementing with bile salts efficiently enriched Veillonellaceae, while YCFA was beneficial for increasing the abundance of Desulfovibrionaceae. Additionally, the addition of trimethoprim, colistin, nalidixic acid, and streptomycin selectively enriched Erysipelotrichaceae.

Figure 6.

The enriched specific ASVs of interest in pigs with the 53 culture conditions (Wang et al. Reference Wang, Howe and Wei2021).

Table 3.

The media are suitable for bacterial samples from diverse hosts

For the Treponema species, a T-Raoult medium (Belkacemi et al. Reference Belkacemi, Khalil and Ominami2019), derived from oral treponeme enrichment broth (OTEB), OMIZ-Pat medium, new oral spirochaetae medium (NOS), and spirochaetae medium, has proven effective for culturing various Treponema species. Given the diverse niches and bacterial compositions within the gastrointestinal tracts of different hosts, culturomics can achieve greater efficiency by employing host-specific media. Future research integrating metagenomics and metabolomics will provide valuable insights into capturing specialized bacteria within their respective hosts.

Vector updating

Conventional tools for bacterial culturing include plates, tubes, and bottles. Given the demanding nature of culturomics, there is a strong demand for new vectors with higher throughput. Cheng et al. (Reference Cheng, Ho and Aranda-Diaz2022) successfully used 96-well plates to culture 104 bacterial isolates and construct a synthetic community. These plates are capable of harvesting numerous bacterial isolates from a complex microbial community. Zhang et al. (Reference Zhang, Liu and Guo2021) established a protocol for bacterial isolation using 96-well plates with limited dilution and bacterial identification through the “Culturome” bioinformatic pipeline (https://github.com/YongxinLiu/Culturome), achieving high-throughput cultivation and identification of root-associated bacteria within 8–9 weeks. This approach using 96-well plates could be adapted for isolating gastrointestinal bacteria, significantly reducing labor and costs. In another study, Liu et al. (Reference Liu, Yu and Zhong2023) used 96-well plates as incubation vectors in the isolation of ureolytic bacteria from cattle rumen, yielding a total of 976 single-strain colonies, comprising 404 unique strains and 52 clusters with <98% 16S rRNA gene identity. One strain from each cluster underwent whole-genome sequencing, revealing 28 strains carrying urease genes classified into 12 species. This increased the number of phenotypically confirmed ureolytic species by 45.83%. Due to its convenience, cost-effectiveness, and high throughput, the 96-well cell culture plates prove to be a promising tool for advancing culturomics research.

Gelling agents diversifying

Agar is the most commonly used gelling agent in bacterial culture media due to its advantageous material qualities (Das et al. Reference Das, Tripathi and Basu2015). However, the traditional preparation process of agar medium has a significant drawback: autoclaving agar together with phosphate produces hydrogen peroxide, which can inhibit the growth of some taxa. To mitigate this issue, it has been suggested that phosphate and agar should be autoclaved separately and mixed just before solidification (Tanaka et al. Reference Tanaka, Kawasaki and Daimon2014). Further, Tanaka et al. (Reference Tanaka and Benno2015) reported that using a soft agar medium with 0.4% agar, which supported faster molecule diffusion, is more effective in isolating single colonies compared to the conventional 1.5% agar concentration. Nyonyo et al. (Reference Nyonyo, Shinkai and Tajima2013) found that modified basal liquid medium (MBM) supplemented with 1.8% agar captures a greater diversity of isolates from cow rumen content compared to MBM adding gellan gum (0.8% Phytagel or 1% Gelrite). However, isolates from certain genera could only be cultured using gellan gum. Building on this, Nyonyo et al. (Reference Nyonyo, Shinkai and Mitsumori2014) added azo-carboxymethylcellulose to MBM containing either agar or gellan gum to facilitate the isolation of ruminal cellulolytic bacteria, revealing that gellan gum performed better in supporting the growth of these bacteria. Nishioka et al. (Reference Nishioka and Tamaki2022) achieved a similar result, where several recalcitrant bacteria from Dendrobium plants were only isolated using a medium containing gellan gum. These findings illustrate the complementarity between agar and gellan gum and emphasize the importance of diversifying gelling agents. Other gelling agents that could be explored in culturomics include gelatin, xanthan gum, guar gum, isubgol, and carrageenan (Das et al. Reference Das, Tripathi and Basu2015). Diversifying gelling agents and their concentrations may enhance the success rate of gastrointestinal bacterial isolation.

Pre-incubation prolonging and oligotrophic culturing

Given the variable growth rates of bacteria in laboratory culture environments, it is important to account for slow-growing taxa in culturomics research. Microorganisms are generally classified as eutrophic and oligotrophic based on their nutritional requirements (Kuznetsov et al. Reference Kuznetsov, Dubinina and Lapteva1979). However, this classification is often applied to bacteria from extreme environments, such as deserts and oceans (Giraud et al. Reference Giraud, Garçon and de la Broise2019; Norris et al. Reference Norris, Levine and Fernández2021; Tapia-Torres et al. Reference Tapia-Torres, Elser and Souza2015), indicating that a large proportion of oligotrophic bacteria in the gastrointestinal tract may be overlooked. Traditional culture media are typically nutrient-rich, which can overshadow the presence of oligotrophic bacteria, rendering some bacteria “unculturable.” Pulschen et al. (Pulschen et al. Reference Pulschen, Bendia and Fricker2017) successfully cultured several previously uncultured bacteria from Antarctic soils using oligotrophic conditions and prolonged incubation periods. Gray et al. (Reference Gray, Dugar and Gamba2019) studied a non-sporulating Bacillus subtilis strain from the soil that could be cultured in extremely diluted media, growing very slowly under deep starvation conditions while remaining metabolically active. They termed this slow growth the “oligotrophic growth state.” These findings highlight the different growth patterns of bacteria in varying media and underscore the importance of oligotrophic culture. Considering the accumulation of metabolism waste, Chang et al. (Reference Chang, Hou and Pan2019) examined the effect of regularly supplementing the culture with fresh media in a 30-day continuous enrichment period, isolating a total of 106 bacterial species from human fecal samples, including three novel species and six not previously isolated from the human intestine, thereby increasing the isolation rate by 22%. Huang et al. (Reference Huang, Han and Chang2023b) subsequently conducted a trial of oligotrophic culture, demonstrating that 10-fold diluted media yielded a higher number of bacterial species than undiluted media, and 24 species account for 34.7% of the total isolated species which are unique to the oligotrophic media. This highlights the importance of employing oligotrophic media to suppress the dominance of eutrophic bacteria in laboratory cultures. Future studies should aim to isolate more gastrointestinal bacteria using oligotrophic media and a prolonged culture period. Comprehensive genomic analyses of these oligotrophic bacteria have the potential to further enhance our understanding and discovery of “microbial dark matter” in the gastrointestinal tract.

Colony picking

The morphological characteristics of colonies, including size, color, smoothness, and so on, should be considered when picking colonies from a solid plate. There is no standardized method; instead, researchers rely on subjective judgment based on their experience. This inevitably results in some bacteria being lost due to researchers’ biases. To mitigate this, colonies are sometimes picked in large numbers, leading to an increased workload in culturomics. Chang et al. (Reference Chang, Hou and Pan2019) compared “experienced” selective colony picking with picking all the colonies from the plate and found that the former decreased the rate of bacterial acquisition by only 8.5%, significantly reducing labor. Huang et al. (Reference Huang, Sheth and Zhao2023a) developed Culturomics by Automated Microbiome Imaging and Isolation (CAMII), a platform for automated microbiome imaging and isolation. This platform can analyze the size, density, color, circularity, convexity, and inertia of the colonies on the agar plate using a dual-illumination imaging system. To select valuable colonies, it employs a robotic colony picker for high-throughput microbial isolation and can learn from colony morphology data, guiding more standardized colony picking. This method can be combined with sequencing results to correlate taxonomic and morphological data. Additionally, potential interactions between bacteria can be observed by monitoring the growth status of adjacent colonies on agar plates. With the assistance of computers and robots, colonies can be comprehensively picked, reducing human labor.

Efforts to optimize sample handling and culture procedures in culturomics are summarized in Fig. 7. Key steps include handling samples quickly and using antioxidants to protect them from oxygen, employing sample dilution or combining it with centrifugation for better isolation, implementing passive filtration for Treponema, and adopting harsh treatments for spore-forming bacteria before the culture procedure to ensure efficient culturing. During the culture process, several methods can enhance the efficiency of culturomics while reducing time, labor, and cost. These include customizing media for samples from diverse hosts or specific bacteria, updating vectors by using 96-well plates to improve throughput, diversifying gelling agents by varying types and concentrations, prolonging pre-incubation, employing oligotrophic culturing, and optimizing colony picking.

Figure 7.

Improving the culturomics workflows (created with BioRender.com).

Pre-culture screening

Traditional culturing methods typically employ a “culture-first” strategy, which significantly increases the workload and often results in the loss of target bacteria during non-in situ culture processes. In contrast, the “screen-first” strategy requires the identification of target bacteria from complex communities, followed by cell sorting to isolate them precisely. Metagenomics offers comprehensive genomic data about bacteriota, enabling the design of specific probes and primers, predicting bacterial extracellular membrane structures, and reconstructing metabolic pathways. The integrated data facilitates the rapid identification of target bacteria and enables the efficient implementation of the “screen-first” strategy, thus substantially reducing the overall workload.

Metagenomic data can be utilized to reconstruct the metabolic pathways of target bacteria, while single-cell Raman spectroscopy (SCRS) combined with stable isotope probes allows for distinguishing metabolic phenotypes of cells based on Raman spectral shifts caused by substrate uptake. For instance, heavy water is often used to incubate target bacteria and subsequent metabolic activity is detected through Raman spectral shifts in the carbon-–deuterium vibration band at 2000–2300 cm⁻¹ (Berry et al. Reference Berry, Mader and Lee2015). Following identification using SCRS, the next challenge shifts to isolating single cells from samples. Raman-activated cell sorting (RACS) integrates SCRS technology with single-cell sorting to achieve targeted bacterial with specific metabolic functions. Previously, RACS was combined with Raman-activated cell ejection to obtain single cells. However, the small size and light weight of bacteria resulted in low ejection success rates and limited high-throughput cell sorting capability. To address these limitations, Wang et al. (Reference Wang, Ren and Su2017) introduced the integrated Raman-activated droplet sorting microfluidic system, which is capable of high-throughput sorting at rates up to 260 cells/min. Xu et al. (Reference Xu, Gong and Su2020) developed the Raman-activated gravity-driven single-cell encapsulation (RAGE) system, which performs SCRS in the liquid phase within a biologically active environment before packaging the target bacteria into picoliter droplets, obtaining “one-cell-one-tube” samples of target bacteria. This system significantly improves genome coverage from less than 10% to over 92% of the sorted single-cell genome. Subsequently, Jing et al. (Reference Jing, Gong and Pan2022) developed single-cell Raman-activated sorting equipped with a RAGE chip to pre-screen phosphate-solubilizing microbes (PSM) in wastewater, followed by culturing the bacteria. This led to the isolation of four strains of strong organic-PSM and one low abundance organic-PSM strain, Cutibacterium spp., which had not been previously reported for phosphate-solubilizing activity. Notably, the phosphate-solubilizing activity of these strains in pure culture was significantly lower than in situ, underscoring the importance of pre-screening in the natural environment.

Cross et al. (Reference Cross, Campbell and Balachandran2019) used the SAG data from the human oral bacterium Saccharibacterium TM7a to identify and retrograde its extramembrane proteins. These proteins were then screened as candidate antigens for antibody development. After incubation with fluorescent-labeled antibodies, the target bacteria were sorted using flow cytometry, and living cells were enriched and cultured. A modified high-speed flow cytometry system has proven valuable in gut bacteriota research as it enables the maintenance of anaerobic conditions during cell sorting (Thompson et al. Reference Thompson, Crow and Wadey2015).

Batani et al. (Reference Batani, Bayer and Boege2019) modified the standard fluorescence in situ hybridization (FISH) technique to enhance bacterial survival during the process a method they termed “live FISH.” This modified approach involved designing FISH probes based on bacterial 16S rRNA gene sequences. These probes were used in conjunction with fluorescence-activated cell sorting to obtain target live bacteria for subsequent enrichment cultures.

Bacteriophages are highly host-specific viruses, making their native or derived molecules excellent candidates for specific bacterial binding probes. Advances in metagenomics have enabled the deduction of phage sequences and their host interactions from genomic data. Hosokawa et al. (Reference Hosokawa, Iwai and Arikawa2023) developed a probe for the specific detection of Streptococcus using SAGs from oral uncultured bacteria. They identified a cell-wall binding domain phage endolysin as the basis for the probe and combined it with magnetic separation flow cytometry to specifically enrich Streptococcus populations. In conclusion, pre-culture screening can be divided into two key steps: screening and sorting. Screening identifies target bacteria from complex microbial samples while sorting techniques isolate these target bacteria for subsequent enrichment cultures. Prioritizing pre-culture screening is essential for more efficient isolation of gastrointestinal bacteria. Furthermore, many techniques from environmental microbiology, when used in conjunction with anaerobic environments, can facilitate the effective isolation of gastrointestinal bacteria.

Media composition optimizing

The analysis of MAG or SAG sequences can provide important insights for successfully culturing target bacteria, guiding the optimization of medium composition, and significantly enhancing isolation success rates. Over the past 20 years, advancements in metagenomics have led to numerous successful applications of using metagenomics data for optimizing selective media (Renesto et al. Reference Renesto, Crapoulet and Ogata2003; Rettedal et al. Reference Rettedal, Gumpert and Sommer2014; Tyson et al. Reference Tyson, Lo and Baker2005; Viacava et al. Reference Viacava, Qiao and Janowczyk2022). In these cases, target bacterial genomes were analyzed to (i) identify functional or resistance genes; (ii) reconstruct metabolic pathways by screening for complete gene clusters; and (iii) detect genetic defects, such as the absence of essential functional genes.

Using MAG or SAG data, functional genes of target bacteria can be inferred to aid in configuring selective media that screens out non-target bacteria lacking these genes. For instance, Tyson et al. (Reference Tyson, Lo and Baker2005) analyzed sequencing data from a low-diversity subsurface acid mine drainage biofilm and identified a single nif operon in a previously uncultured Leptospirillum Group III genomic fragment. This operon was presumed to be unique to nitrogen-fixing bacteria in this bacteriota. Based on this finding, a nitrogen-free medium was designed, leading to the successful isolation of Leptospirillum Group III. Additionally, incorporating antibiotics into the culture medium is another effective strategy to inhibit non-target bacterial growth. The comprehensive antibiotic research database (CARD) facilitates this by predicting resistance genes present in target bacteria based on genomic sequences. CARD is continuously updated, with its current version 3.2.4 encompassing 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 detection models (Alcock et al. Reference Alcock, Huynh and Chalil2023; McArthur et al. Reference McArthur, Waglechner and Nizam2013). In addition to identifying individual functional genes, MAG and SAG sequences can be used to reconstruct metabolic pathways, aiding in selecting appropriate substrates for the medium. The antibiotics and secondary metabolite analysis shell, a powerful tool for mining bacterial secondary metabolites based on genomic data, allows for the analysis of biosynthetic gene clusters in bacterial genomes (Blin et al. Reference Blin, Shaw and Augustijn2023; Medema et al. Reference Medema, Blin and Cimermancic2011). For instance, Viacava et al. (Reference Viacava, Qiao and Janowczyk2022) performed metagenomic and metatranscriptomics analyses on enriched soil bacteria, annotating 17 key enzymes of MAGs and their involved metabolic pathways. This data was instrumental in designing a selective medium tailored for isolating the anaerobic arsenic-methylating soil bacterium Paraclostridium sp. strain EML.

It is also possible to derive information about genomic deficiencies to optimize medium composition, enabling the growth of target bacteria under non-in situ culture conditions. Tropheryma whipplei, the pathogen of Whipple’s disease, is particularly challenging to cultivate under laboratory conditions and has been isolated only in association with eukaryotic cells. Renesto et al. (Reference Renesto, Crapoulet and Ogata2003) predicted the metabolic pathways of T. whipplei from its genome sequence, revealing the absence of all genes required for synthesizing nine amino acids. This genomic deficiency indicated that T. whipplei relies on exogenous sources for these amino acids. Consequently, by supplementing the culture medium with these nine amino acids, the researchers successfully isolated a new strain of T. whipplei.

Culture conditions optimizing

Genomic data offers valuable insights into bacterial adaptations to the environment. Weimann et al. (Reference Weimann, Mooren and Frank2016) developed Traitar, a fully automated software package designed to predict phenotypic traits from genomic sequences. This tool can predict various microbial characteristics, including substrate utilization for carbon and energy sources, morphology, antibiotic susceptibility, proteolysis, enzymatic activities, oxygen requirements, and optimal growth temperature. Traitar’s accuracy was confirmed with data from 572 species spanning eight phyla. Sauer et al. (Reference Sauer and Wang2019) expanded on the principles of reverse ecology through big data analysis, demonstrating that genomic data can predict not only the optimal growth temperature of bacteria but also other quantifiable environmental parameters. These parameters include pH, salinity, osmolality, and oxygen concentration. By uncovering these characteristics from genomic data, their approach can facilitate culturomics studies. Genomic data contains a vast amount of information that can guide the refinement of culture conditions, suggesting that future software could be developed to predict comprehensive, quantifiable culture conditions based on MAG or SAG sequences guiding culturomics studies.

Post-culture screening

The use of extreme dilution combined with 96-well plates has proven to be an effective method for isolating a single bacterium per well, ensuring that each well contains no more than one bacterium due to the high dilution factor. Following high-throughput culture in 96-well plates, Liu et al. (Reference Liu, Yu and Zhong2023) used ureC-specific primers for post-culture screening, which efficiently and conveniently identified candidate urea-degrading bacteria. Functional genes identified from MAG or SAG data can be used to design specific primers to guide the isolation process. Additionally, pre-culture screening methods, including fluorescently labeled antibodies, can also be applied after the culture to further refine isolation and identification.

Furthermore, different genera of colonies exhibit distinct morphological characteristics. For example, Dorea, Bacteroides, and Collinsella form larger colonies on agar with dense hyphae but vary in colony diameters, whereas Faecalibacterium produces smaller, darker colonies and is less culturable. Therefore, the colony characteristics of the target bacteria on the plate can be predicted based on taxonomic information from target MAGs or SAGs, especially at the genus level. Huang et al. (Reference Huang, Sheth and Zhao2023a) developed the automated CAMII system, which collects microbial morphological data, learns from it, and integrates morphological and genomic data to guide preliminary screening, thus reducing the workload when picking bacteria. Although such advanced systems are not yet widely available in traditional laboratories, further research should focus on designing specific primers or probes and predicting morphological characteristics from genome sequences to guide post-culture screening.