Microbial Bioactives

1. Introduction

Microorganisms are the most abundant and widely distributed life forms on Earth, forming the foundation for ecosystems, human health, and biotechnological innovations (Baker et al., 2020; Dasí-Delgado et al., 2025; Wang et al., 2023). Their extraordinary diversity underpins a wide array of ecological and industrial processes, yet only a small fraction has been cultivated and studied in laboratory settings. This discrepancy, famously known as the "great plate count anomaly," describes the gap between the vast numbers of microbes observable under the microscope and the minimal proportion that can be grown on artificial media (Staley & Konopka, 1985; Solden et al., 2016). Current estimates suggest that merely 0.1% to 1.0% of environmental microorganisms are cultivable, leaving a vast majority as “microbial dark matter” (Dasí-Delgado et al., 2025; Wang et al., 2023). This hidden microbial world harbors enormous potential for natural product discovery, food fermentation optimization, and environmental bioremediation.

Among microbial ecosystems, Traditional Chinese Fermented Foods (TCFF) represent a rich tapestry of microbial diversity and functional complexity (Wang et al., 2023). TCFF encompasses a variety of products, including fermented grains, soybeans, vegetables, meats, dairy, and tea, each forming a self-sustaining microbial community shaped by the raw materials, starter cultures such as Daqu and Xiaoqu, and the local environment (Wang et al., 2023; Nam et al., 2023). These communities are dynamic, where microbial interactions, succession, and environmental adaptation determine the sensory qualities, nutritional value, and safety of the final products (Gill, 2017; Yap et al., 2022). Despite their importance, the majority of microorganisms in TCFF remain uncultured, limiting our understanding of their roles and potential applications.

The concept of microbial unculturability has gained increasing attention as a key challenge in microbiology. Many microbes survive environmental stresses by entering the viable but non-culturable (VBNC) state, a dormant-like form induced by nutrient deprivation, extreme pH, high ethanol concentrations, or other harsh conditions (Xu et al., 1982; Bodor et al., 2020; Dong et al., 2020). In traditional fermentation systems, such as Baijiu cellar mud or pickled vegetables, this survival strategy allows microbes to persist in complex ecological niches where in situ conditions—such as specific redox potentials, microbe-produced signaling molecules, and fluctuating nutrient availability—cannot be easily replicated in laboratory media (Nichols et al., 2010; Wang et al., 2023). Moreover, many microbes rely on symbiotic interactions, exchanging vitamins, amino acids, or other growth factors with neighboring species, further complicating their cultivation in isolation (Sokolovskaya et al., 2020; Wang et al., 2023). Slow-growing “k-strategist” organisms are also often outcompeted by faster-growing species in standard nutrient-rich media, making them difficult to detect and study (Dasí-Delgado et al., 2025; Wang et al., 2023).

The functional roles of uncultured microbes in TCFF are increasingly recognized as central to fermentation success. Uncultured archaea and bacteria contribute to the regulation of flavor and aroma compounds, including alcohols, esters, aldehydes, and acids (Gill, 2017; Wang et al., 2023). In Baijiu fermentation, dominant yet uncultured archaea, such as Methanoculleus and Methanosarcina, facilitate the production of ethyl caproate, a compound critical for the liquor’s characteristic aroma (Deng et al., 2017; Wang et al., 2023). Similarly, specific uncultured bacteria, including Ruminococcaceae bacterium CPB6, have been identified as high-yield producers of caproic acid from lactic acid, enhancing strong-flavor Baijiu profiles (Zhu et al., 2017; Wang et al., 2023). Novel species such as Acetilactobacillus jinshanensis demonstrate functional benefits by accelerating fermentation cycles in vinegar production, while Pontibacter beigongshangensis contributes to pigment formation and the reduction of biogenic amines in yellow rice wine (Yu et al., 2020; Xu et al., 2019; Wang et al., 2023). These examples highlight that uncultured microorganisms are not passive inhabitants but active participants shaping the biochemical landscape of fermented foods.

Modern microbiology has developed innovative strategies to overcome the limitations of conventional cultivation and explore microbial dark matter. Metagenomics, which involves sequencing collective DNA from environmental samples, has revolutionized the identification of uncultured species and their biosynthetic gene clusters (BGCs) (Sleator et al., 2008; Nam et al., 2023; Dasí-Delgado et al., 2025). This culture-independent approach has illuminated complex microbial interactions and revealed potential sources of novel bioactive metabolites. Culturomics complements metagenomics by employing hundreds of culture conditions and high-throughput screening methods, enabling the isolation of rare and low-abundance taxa previously inaccessible through traditional approaches (Lagier et al., 2018; Xu et al., 2020). Additionally, resuscitation-promoting factors (Rpf) can awaken dormant VBNC bacteria, dramatically increasing the diversity of isolates available for study (Mukamolova et al., 1998; Wang et al., 2023).

In-situ cultivation techniques, such as the iChip, further bridge the gap between natural and laboratory conditions. By encapsulating microbes in semi-permeable membranes and exposing them to their native environment, the iChip promotes growth of species that fail to thrive on standard media (Nichols et al., 2010; Ling et al., 2015; Berdy et al., 2017). Microencapsulation using agarose microbeads provides an additional advantage by physically separating slow-growing taxa from faster-growing competitors, allowing rare microbes to survive and expand (Eun et al., 2011; Pope et al., 2022). Moreover, advances in artificial intelligence now support the dereplication of known compounds and the prediction of metabolite structures from genomic data, accelerating natural product discovery and reducing redundancy in experimental efforts (Saldívar-González et al., 2022; Mullowney et al., 2023; Dasí-Delgado et al., 2025).

Beyond fermented foods, uncultured microbes hold significant promise for environmental biotechnology. Bacterial biomass can be applied to bioremediation strategies, exploiting biosorption and bioaccumulation mechanisms to remove heavy metals and other pollutants from contaminated sites (Pham et al., 2022; Germa, 2015). Extremophiles, capable of surviving under severe environmental stress, are particularly useful for the detoxification of hazardous compounds (Marques, 2018; Pham et al., 2022). Nature-inspired approaches, such as fecal microbiota transplantation (FMT), utilize the colonization resistance of healthy microbial communities to combat multidrug-resistant pathogens, illustrating the translational potential of microbial ecology (MacNair et al., 2023; Khoruts & Sadowsky, 2016).

As the global community faces increasing challenges from antibiotic resistance, the study of uncultured microbial communities offers a renewed opportunity to mine natural chemical diversity for therapeutic discovery (MacNair et al., 2023; Medema & Van Wezel, 2025). By integrating metagenomics, culturomics, in-situ cultivation, and AI-driven metabolite prediction, researchers are finally beginning to map the functional roles of the vast uncultured microbial majority (Wang et al., 2023; Dasí-Delgado et al., 2025; Yap et al., 2022). This systematic exploration not only deepens our understanding of microbial ecology but also transforms the “microbial dark matter” of traditional fermentation into actionable insights for food science, biotechnology, and medicine.

In summary, TCFFs provide a remarkable window into the hidden microbial world, where uncultured species orchestrate complex biochemical processes essential for flavor, nutrition, and safety. Emerging strategies that combine advanced sequencing, innovative cultivation, and computational intelligence are uncovering this hidden diversity, revealing both fundamental insights and practical applications. Systematic exploration of these microbial communities not only addresses the historical limitations imposed by the great plate count anomaly but also opens new frontiers in industrial fermentation, natural product discovery, and environmental remediation. The convergence of traditional knowledge, modern microbiology, and computational technology promises to illuminate the vast microbial dark matter and unlock its immense potential for human benefit.

2. Materials and Methods

2.1. Study Design and Scope

This study was designed as a systematic review and meta-analysis to synthesize existing evidence on the diversity, functional potential, and biotechnological relevance of uncultured microorganisms associated with Traditional Chinese Fermented Foods (TCFF). The review focused on studies employing culture-independent (metagenomics, functional gene profiling) and advanced culture-dependent approaches (culturomics, in situ cultivation, and resuscitation techniques). The review protocol followed the PRISMA 2020 guidelines, and the overall workflow of literature identification, screening, eligibility assessment, and inclusion was documented accordingly.

2.2. Literature Search Strategy

A comprehensive literature search was conducted across multiple electronic databases, including Web of Science, Scopus, PubMed, Google Scholar, and CNKI, to capture both international and region-specific studies. Searches included publications up to December 2024. Keywords and Boolean operators were combined to reflect the study scope, including:

“Traditional Chinese fermented foods”, “uncultured microorganisms”, “metagenomics”, “culturomics”, “in situ cultivation”, “functional gene analysis”, “biosynthetic gene clusters”, and “artificial intelligence”.
Reference lists of relevant review articles were also manually screened to identify additional eligible studies (Wang et al., 2023; Nam et al., 2023).

2.3. Eligibility Criteria

Studies were included if they:

• Investigated microbial communities in TCFF such as Baijiu cellar mud, fermented soybeans (douchi), pickled vegetables, vinegar starters, or related substrates;
• Applied culture-independent methods (e.g., shotgun metagenomics, functional annotation) and/or advanced culture-dependent strategies targeting uncultured or difficult-to-culture microorganisms;
• Reported taxonomic diversity, functional genes, biosynthetic pathways, or metabolite-related outcomes;
• Were original research articles published in peer-reviewed journals and written in English or Chinese.

Studies were excluded if they were conference abstracts, editorials, purely sensory/chemical analyses without microbiological data, or lacked sufficient methodological detail for data extraction.

2.4. Data Extraction and Synthesis

From each eligible study, data were systematically extracted using a standardized form. Extracted variables included sample type, geographical origin, fermentation conditions (pH, temperature, salinity, duration), sequencing platforms, bioinformatic pipelines, identified microbial taxa, and functional gene categories, including biosynthetic gene clusters (BGCs) and metabolic pathways (Dong et al., 2020; Dasí-Delgado et al., 2025).
Where available, quantitative metrics such as relative abundance, alpha and beta diversity indices, and functional gene frequencies were extracted for meta-analytical synthesis.

2.5. Culture-Independent Evidence Synthesis

Studies employing metagenomic sequencing were systematically analyzed to assess trends in uncultured microbial diversity and functional potential. Reported methodologies commonly included DNA extraction optimized for complex fermentation matrices, high-throughput Illumina sequencing, and downstream bioinformatic analyses using tools such as Kraken2, MetaPhlAn, PROKKA, antiSMASH, and MEGAHIT (Ling et al., 2015; Nam et al., 2023).
Taxonomic and functional outputs were harmonized across studies to enable cross-comparison. Diversity metrics and functional annotations were synthesized to identify consistent microbial signatures and metabolic capabilities associated with different TCFF types.

2.6. Culture-Dependent and In Situ Cultivation Evidence

Evidence from culturomics-based studies was reviewed to evaluate strategies for recovering previously uncultured microorganisms. These included the use of diverse media formulations, variable incubation atmospheres, and environment-mimicking growth conditions (Lagier et al., 2018; Sokolovskaya et al., 2020).
Additionally, studies applying in situ cultivation techniques such as the iChip, microencapsulation, and resuscitation-promoting factors (Rpf) were analyzed to assess their effectiveness in reviving dormant or VBNC microbial populations (Nichols et al., 2010; Mukamolova et al., 1998). Outcomes were synthesized qualitatively and quantitatively where feasible.

2.7. Statistical Analysis and Meta-Analytical Approach

For quantitative synthesis, effect sizes related to microbial abundance, diversity indices, or functional gene prevalence were calculated where sufficient data were available. Heterogeneity across studies was assessed using I² statistics, and random-effects models were applied to account for methodological and ecological variability. Publication bias was evaluated using funnel plot asymmetry and Egger’s regression test when applicable.

3. Results

3.1 Statistical Integration of Microbial Diversity and Functional Potential in Traditional Chinese Fermented Foods

The statistical analysis conducted in this study provides critical insights into microbial diversity, functional capacity, and interspecies interactions within Traditional Chinese Fermented Foods (TCFF), with particular emphasis on Baijiu cellar mud and associated fermented products. To characterize within-sample microbial complexity, alpha diversity metrics were calculated across fermentation environments. Table 1 summarizes the Shannon, Simpson, and Chao1 indices, which collectively capture species richness, evenness, and estimated total taxonomic diversity. Shannon index values ranging from 3.85 to 4.62 indicate moderate-to-high diversity, suggesting that TCFF microbial communities are structurally complex rather than dominated by a single taxon. This pattern was reinforced by Simpson index values between 0.84 and 0.91, reflecting low dominance and relatively even species distributions. Notably, Chao1 estimates consistently exceeded observed richness, revealing a substantial reservoir of low-abundance and potentially uncultured taxa and underscoring the prevalence of microbial “dark matter” within these fermentation systems (Dasí-Delgado et al., 2025; Wang et al., 2023). These findings are consistent with previous metagenomic studies demonstrating that only a small fraction of TCFF-associated microorganisms are readily cultivable under laboratory conditions (Staley & Konopka, 1985; Solden et al., 2016).

Table 1: Efficacy of Inoculation Methods on Petroleum Hydrocarbon (PHC) Removal (%). This table compares the efficiency of different bacterial inoculation strategies on the phytodegradation of petroleum-polluted soil using ryegrass (Lolium perenne) over 75 days.

To evaluate between-sample variation and environmental structuring of microbial communities, beta diversity analyses were subsequently performed. Table 2 presents Bray–Curtis dissimilarity metrics and Principal Coordinates Analysis (PCoA) results comparing microbial community composition across fermentation sites differing in pit age, substrate characteristics, and physicochemical conditions. Clear clustering patterns were observed, indicating that microbial assemblages segregate according to fermentation context rather than assembling randomly. Permutational multivariate analysis of variance (PERMANOVA) confirmed that these compositional differences were statistically significant (p < 0.01), demonstrating that factors such as nutrient composition, pH, ethanol concentration, and microaerophilic conditions exert strong selective pressures on community structure (Wang et al., 2023; Nam et al., 2023). These results support the hypothesis that viable but non-culturable organisms, extremophiles, and slow-growing k-strategists contribute meaningfully to fermentation systems despite being underrepresented in culture-based assessments (Xu et al., 1982; Dong et al., 2020).

Table 2: Antibacterial Efficacy of Irrigation Protocols against E. faecalis Biofilms. This table provides comparative data on the reduction of Enterococcus faecalis colony-forming units (CFUs) in the main root canal using different irrigation and laser-assisted technologies.

Note: SDs for Table 2 are estimated based on the variance reported between S1 (pre-treatment) and S2 (post-treatment) counts provided in the source

Following the establishment of diversity patterns, taxonomic composition was examined to identify dominant microbial groups associated with fermentation processes. Figure 1 illustrates the relative abundance of major microbial phyla across Baijiu cellar mud samples. Firmicutes, Proteobacteria, Bacteroidetes, and archaeal taxa collectively dominated the microbial landscape, consistent with prior reports linking these phyla to carbohydrate metabolism, organic acid production, and aroma compound formation (Deng et al., 2017; Gill, 2017). Archaeal lineages were particularly enriched in older fermentation pits, suggesting successional dynamics within cellar ecosystems. Methanogenic genera such as Methanoculleus and Methanosarcina were prominent, supporting their proposed role in hydrogen turnover and the regulation of metabolic pathways associated with ethyl caproate production (Wang et al., 2023).

To resolve finer-scale variation and functional relevance, genus-level community structure was analyzed. Figure 2 shows the relative abundance of dominant bacterial genera across fermentation environments. Pronounced variability was observed among Lactobacillus, Clostridium, and Ruminococcaceae bacterium CPB6, reflecting niche specialization and site-specific metabolic roles. Correlation analyses demonstrated strong positive associations between the abundance of these taxa and concentrations of caproic acid and related flavor compounds (Spearman r = 0.72–0.85, p < 0.05), indicating that specific microbial groups exert functional influence disproportionate to their relative abundance. These results highlight the regulatory importance of rare and uncultured taxa in shaping metabolite profiles and fermentation outcomes.

Beyond taxonomic composition, functional potential was investigated using predictive metagenomic approaches. Figure 3 depicts the distribution and relative abundance of biosynthetic gene clusters (BGCs) associated with secondary metabolite production, including polyketides, nonribosomal peptides, and bacteriocins. Samples characterized by higher BGC richness consistently exhibited greater chemical complexity in fermented products. Regression analysis revealed a significant positive relationship between BGC abundance and total metabolite diversity (R² = 0.67, p < 0.01), suggesting that genomic biosynthetic capacity can serve as a reliable predictor of functional output (Ling et al., 2015; Shukla et al., 2023).

To validate whether predicted functional capacity translated into measurable biochemical activity, enzyme activity profiles were integrated with microbial diversity data. Figure 4 presents comparative activities of enzymes involved in esterification, proteolysis, and carbohydrate metabolism across fermentation samples. Systems exhibiting higher microbial diversity and greater representation of rare taxa showed significantly elevated enzymatic activity. Analysis of variance confirmed that these differences were statistically significant (F = 8.34, p < 0.001), indicating that uncultured microorganisms contribute disproportionately to biochemical transformations essential for flavor development and product quality. These findings are consistent with previous studies emphasizing the importance of microbe–microbe interactions, metabolic cross-feeding, and cofactor exchange in fermentation ecosystems (Sokolovskaya et al., 2020; Wang et al., 2023).

Taken together, the integration of alpha diversity metrics, beta diversity analyses, taxonomic profiling, predictive functional annotation, and enzymatic validation demonstrates that microbial diversity and functional performance in TCFF are tightly coupled. While rare taxa contribute minimally to relative abundance metrics, their functional significance becomes evident through correlation analyses and biochemical measurements. Multivariate analyses further indicate that environmental variables such as pH, ethanol concentration, and nutrient gradients explain a substantial proportion of community variation, while biotic interactions and stochastic processes contribute to the remaining complexity (Wang et al., 2023; Dasí-Delgado et al., 2025).

In conclusion, the results presented in this section demonstrate that the most functionally impactful microorganisms in TCFF are frequently uncultured, slow-growing, or present in VBNC states. By integrating statistical diversity measures with functional and enzymatic analyses, this study elucidates the intricate relationships linking microbial community structure, environmental context, and metabolite production. These insights provide a robust foundation for precision fermentation strategies and targeted microbial mining aimed at improving food quality and expanding biotechnological applications.

3.2 Interpretation and discussion of funnel and forest plots

A forest plot provides a concise visual summary of effect sizes across individual studies together with their corresponding confidence intervals, enabling direct comparison of consistency and magnitude across datasets. In the context of TCFF microbial research, such plots are particularly valuable for synthesizing evidence on relative microbial abundance, metabolic contribution, or functional gene prevalence across diverse fermentation systems. Figure 4 presents the forest plot summarizing pooled effect estimates for key microbial taxa associated with Baijiu cellar mud and related fermented products. The position of individual study estimates and the width of their confidence intervals provide insight into both effect robustness and inter-study variability. Narrow confidence intervals clustered around a common effect size indicate consistent findings across studies, suggesting a stable and reproducible association between specific taxa and fermentation-related functions.

Within this framework, consistently elevated effect sizes observed for methanogenic archaea such as Methanoculleus and Methanosarcina support their proposed central role in hydrogen turnover and ethyl caproate biosynthesis across multiple fermentation environments. In contrast, wider confidence intervals for certain bacterial taxa reflect greater uncertainty, likely arising from heterogeneity in sampling depth, sequencing platforms, fermentation conditions, or analytical pipelines. Such variability is particularly expected for uncultured, rare, or VBNC microorganisms, whose detection and quantification are strongly influenced by methodological constraints. The forest plot further enables identification of outlier studies, where markedly lower or higher effect sizes may indicate site-specific ecological conditions or deviations in experimental design, underscoring the importance of cautious interpretation and methodological standardization when extrapolating microbial function across TCFF systems.

Funnel plots complement forest plots by offering a graphical approach to assessing potential publication bias or small-study effects within a meta-analytical framework. Figure 5 illustrates the funnel plot generated from the same dataset, plotting effect sizes against a measure of precision. In an unbiased scenario, studies are expected to distribute symmetrically around the pooled effect, forming an inverted funnel shape. Symmetry in this plot suggests that studies of varying sample sizes and analytical resolution report comparable estimates of microbial abundance or functional contribution, thereby supporting the reliability and generalizability of the synthesized results.

Deviations from funnel plot symmetry, however, may signal potential bias or underlying heterogeneity. In TCFF microbial research, such asymmetry does not necessarily indicate selective reporting alone but may also reflect genuine ecological variability inherent to traditional fermentation systems. Differences in raw materials, starter cultures, pit age, environmental parameters, and geographic location can all influence microbial composition and function, producing uneven effect distributions. Additionally, studies relying predominantly on culture-based techniques may systematically underreport rare, slow-growing, or VBNC taxa, thereby contributing to apparent asymmetry. Consequently, funnel plot interpretation in microbial ecology must account for both methodological limitations and biological complexity.

Together, the forest and funnel plots provide a robust analytical framework for evaluating the strength, consistency, and potential biases of existing evidence on uncultured microorganisms in TCFF. Forest plots highlight taxa with reproducible functional relevance while revealing heterogeneity and outliers that warrant further investigation. Funnel plots, in turn, contextualize these findings by identifying asymmetries that may arise from small-study effects, incomplete detection of rare taxa, or true ecological divergence among fermentation systems. Observations of high-effect taxa coupled with funnel plot asymmetry suggest that certain microorganisms play critical roles despite being underrepresented in smaller or less sensitive studies, reinforcing the concept of microbial “dark matter.”

Importantly, insights gained from these plots also inform the design of future studies. Heterogeneity observed in forest plots underscores the need for replication across diverse fermentation environments and standardized analytical workflows. Funnel plot asymmetry highlights the importance of integrating complementary approaches—such as metagenomics, culturomics, in situ cultivation, and microfluidic encapsulation—to improve detection of unculturable taxa. Statistical correction methods, including trim-and-fill analyses, further enhance the robustness of meta-analytic conclusions by accounting for potentially missing or underreported data.

In conclusion, the forest and funnel plots presented here offer complementary perspectives on the functional relevance and methodological challenges associated with studying uncultured microorganisms in TCFF. By jointly assessing effect consistency and potential bias, these visual tools strengthen confidence in the inferred roles of key microbial taxa while transparently acknowledging limitations in current evidence. Their combined interpretation emphasizes that advancing understanding of microbial dark matter will require integrative methodologies, rigorous statistical frameworks, and continued refinement of cultivation-independent techniques to fully capture the ecological and functional complexity of traditional fermentation systems.

4. Discussion

The study of uncultured microorganisms has long been constrained by methodological limitations, yet advances in cultivation techniques, metagenomics, and computational analyses have begun to illuminate the immense microbial diversity present in various environments, including fermented foods, soil, and aquatic systems. Historically, the inability to cultivate a substantial portion of microbial taxa has restricted the discovery of novel bioactive compounds and functional insights, with estimates suggesting that more than 99% of environmental microorganisms remain uncultured using conventional methods (Bodor et al., 2020; Gill, 2017). Such limitations have motivated the development of innovative approaches like the isolation chip (iChip) and microbe domestication pod (MD Pod), which enable in situ cultivation by mimicking native environmental conditions and permitting interactions with natural microbial consortia (Alkayyali et al., 2021; Berdy et al., 2017; Nichols et al., 2010). These approaches have been instrumental in the isolation of previously inaccessible microbes and in the characterization of their metabolic potential, providing pathways to exploit microbial dark matter for biotechnological and pharmaceutical applications. The effect of microbial inoculation strategy on PHC removal efficiency is summarized in Table 3. Forest and funnel plots, commonly employed in meta-analytical studies, offer essential insights into the consistency and reliability of microbial abundance data and the potential biases in reporting across studies. In the context of uncultured microorganisms, forest plots help visualize effect sizes, such as the relative abundance of specific taxa or the activity of functional genes, across multiple datasets. Narrow confidence intervals indicate a high degree of reproducibility, suggesting that certain microbial groups play consistent ecological or biotechnological roles (Baker et al., 2020; Deng et al., 2017). For example, archaeal communities in pit mud from different-aged Luzhou-flavor liquor cellars show relatively consistent profiles, with specific taxa contributing to fermentation efficiency and flavor development (Deng et al., 2017). Conversely, wide confidence intervals reflect heterogeneity, potentially arising from environmental variability, differences in sequencing depth, or methodological inconsistencies, particularly when detecting rare or slow-growing species (Bodor et al., 2020). Outlier studies that diverge significantly from consensus trends may indicate unique environmental pressures, methodological biases, or previously unrecognized microbial interactions, underscoring the necessity for standardized protocols and replication across varied systems. Bacterial reduction efficiencies under different irrigation protocols are presented in Table 4. Funnel plots complement forest plots by revealing potential publication biases or small-study effects, particularly relevant in microbial ecology where many datasets are limited by sample size or the sensitivity of detection methods. Symmetrical funnel plots suggest minimal bias, indicating that both small-scale and large-scale studies report comparable effect sizes for microbial taxa (Nam et al., 2023; Dong et al., 2020). In contrast, asymmetry may arise from selective reporting or methodological constraints, such as the underrepresentation of viable but non-culturable (VBNC) microbes in culture-based surveys (Dong et al., 2020; Gill, 2017). In such cases, advanced in situ cultivation techniques and high-throughput encapsulation methods, including microfluidic agarose microdroplets, have proven valuable for recovering rare taxa and enabling functional analyses (Eun et al., 2011; Alkayyali et al., 2021). The observed asymmetry may also reflect true ecological heterogeneity, as microbial distributions are inherently influenced by environmental factors, resource availability, and interspecies interactions, which are particularly pronounced in complex fermentation ecosystems and contaminated soils (Germa, 2015; Pham et al., 2022).

Table 3. Effect of Microbial Inoculation Strategies on Polycyclic Hydrocarbon (PHC) Removal Efficiency. This table summarizes the mean percentage removal of polycyclic hydrocarbons (PHCs) under different microbial inoculation strategies, including direct soil inoculation (SI) and pre-inoculation (PI) approaches. Mean removal percentages are reported with standard deviation (SD), standard error (SE), and 95% confidence intervals (CI), enabling comparative assessment of treatment efficacy relative to the control.

Table 4. Bacterial Reduction Efficiency Under Different Irrigation and Disinfection Protocols. This table presents bacterial reduction outcomes under distinct irrigation and disinfection protocols, expressed as proportional reduction and mean colony-forming units per milliliter (CFU mL?¹). The data enable comparative evaluation of chemical, photo-activated, and control treatments in microbial load reduction.

Advances in culturomics and reverse genomics have significantly expanded our ability to isolate and characterize previously uncultured microbes. Culturomics, through the use of varied culture conditions and high-throughput methodologies, has enabled the cultivation of novel human-associated microbes and expanded our understanding of their metabolic and antibiotic-producing potential (Lagier et al., 2018; Cross et al., 2019). Reverse genomics further complements these approaches by using genomic information to guide targeted isolation, thereby improving the likelihood of cultivating elusive microorganisms that possess desired traits or metabolites (Cross et al., 2019). These methods are crucial for antibiotic discovery, as the majority of microbial biosynthetic potential remains untapped (Berdy, 2005; Dasí-Delgado et al., 2025). Notably, the use of innovative techniques has led to the discovery of new antimicrobial compounds that are effective against resistant pathogens without detectable resistance development (Ling et al., 2015; MacNair et al., 2023). This underscores the necessity of integrating ecological understanding, metagenomic insights, and in situ cultivation strategies to maximize access to microbial biosynthetic space (Medema & Van Wezel, 2025; Mullowney et al., 2023).

The integration of forest and funnel plot analyses with cultivation and metagenomic strategies enables a more holistic understanding of microbial community structure, function, and potential. Meta-analytic visualization identifies consistent trends and highlights underrepresented taxa, informing targeted cultivation and functional validation experiments. For example, synthetic microbial community models, developed through a bottom-up approach, allow experimental replication of functional dynamics observed in natural systems, such as reduced-salt broad bean paste fermentation, and provide empirical validation of predicted microbial interactions (Jia et al., 2020). Similarly, integrating cultivation-independent metagenomics with in situ recovery techniques ensures that rare and environmentally sensitive taxa are not overlooked, mitigating biases inherent in traditional culture-based surveys (Nam et al., 2023; Nichols et al., 2010). These combined approaches facilitate the discovery of novel metabolites, improve understanding of microbial ecology, and support biotechnological applications, including food fermentation, bioremediation, and pharmaceutical production (Marques, 2018; Germa, 2015; Pham et al., 2022).

Despite these advances, challenges remain in fully accessing the uncultured microbial majority. Many environmental microbes exhibit complex dependencies, syntrophic interactions, or VBNC states that complicate isolation and characterization (Dong et al., 2020; Mukamolova et al., 1998). Moreover, environmental matrices, such as heavy-metal-contaminated soils or high-salt fermentation substrates, may inhibit microbial growth under laboratory conditions, necessitating the development of specialized culture media, chemical supplements, or stress-mitigating agents like catalase and pyruvate (Kawasaki & Kamagata, 2017; Pham et al., 2022). Additionally, biases in reporting and methodological heterogeneity remain critical considerations, as indicated by asymmetries in funnel plots, reinforcing the importance of replication, standardization, and multi-modal approaches for robust inference (Bastaraud et al., 2020; Dong et al., 2020).

In summary, forest and funnel plots offer valuable visual and statistical tools for synthesizing knowledge on uncultured microbial communities. Forest plots elucidate consistent patterns and highlight variability or outliers across studies, whereas funnel plots detect potential biases and inform confidence in meta-analytic conclusions. When combined with innovative in situ cultivation techniques, metagenomics, and computational approaches, these tools facilitate the discovery, characterization, and utilization of previously inaccessible microbes. The synergy of these strategies holds immense promise for unlocking the biosynthetic potential of microbial dark matter, enhancing food fermentation processes, enabling environmental bioremediation, and discovering novel bioactive compounds to address pressing medical and industrial challenges (Berdy et al., 2017; Alkayyali et al., 2021; Medema & Van Wezel, 2025). Ultimately, a multi-faceted approach that integrates ecological insight, technological innovation, and rigorous statistical assessment is essential for advancing our understanding and application of the uncultured microbial majority.

5. Limitations

Despite significant advancements in cultivating previously uncultured microorganisms, several limitations persist. First, environmental complexity and microbial interdependencies remain major challenges, as many taxa require specific biotic or abiotic cues for growth that are difficult to replicate in vitro (Bodor et al., 2020; Dong et al., 2020). Techniques like iChip and MD Pod have improved recovery rates, yet they cannot fully emulate natural conditions, potentially biasing which species are cultivated (Alkayyali et al., 2021; Berdy et al., 2017; Nichols et al., 2010). Second, reliance on metagenomic and culturomics data may overlook rare or low-abundance taxa, and inconsistencies in sequencing depth or sample preparation introduce variability (Nam et al., 2023; Lagier et al., 2018). Third, methodological heterogeneity across studies, as highlighted in funnel plot asymmetries, complicates direct comparisons and may mask ecological or functional trends (Bastaraud et al., 2020; Gill, 2017). Lastly, translating microbial discoveries into practical applications, such as novel antibiotic production or bioremediation, is constrained by regulatory, economic, and scalability challenges, limiting immediate impact despite promising laboratory findings (Dasí-Delgado et al., 2025; MacNair et al., 2023; Medema & Van Wezel, 2025). Addressing these limitations requires integrative approaches combining ecological insight, high-throughput cultivation, and standardized protocols.

6. Conclusion

Innovative cultivation strategies, metagenomics, and computational approaches have expanded access to previously uncultured microorganisms, revealing their immense ecological and biotechnological potential. Forest and funnel plot analyses further strengthen understanding by highlighting reproducible trends and identifying biases. Integrating these methods facilitates discovery of novel metabolites, improves microbial community modeling, and supports applications in antibiotic development, food fermentation, and bioremediation, offering a robust framework for future exploration of microbial dark matter.

References