The development of standardized and reproducible methodologies is crucial for translating microbiome research into clinically useful diagnostic tools

The gap

Evidence profile

Sourced from the future work and inline gaps and future-work section and stated challenges and limitations section of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 7 journals. Those papers have been cited 58 times in total.

Supporting evidence — 8 representative gaps

• Tumor-resident bacteria in gastrointestinal cancers: from regulatory mechanisms to clinical implications (2026) · Cancer Biology & Medicine · doi

  The understanding of intratumoral microbiota is funda- mentally reshaping current views of gastrointestinal cancer biology. Tumor-associated microbes exhibit diverse origins, substantial inter-individual variability, and distinct organ- and tissue-specific distribution patterns. However, based on avail- able evidence, knowledge of intratumoral microbiota remains incomplete. This emerging field holds considerable promise but is also accompanied by significant challenges. Rational utilization of intratumoral microbiota may enable the devel- opment of new frameworks for early cancer diagnosis, multi- modal treatment strategies, and assessment of prognosis and therapeutic response, which represent central directions for future research. At present, many studies rely on relatively low-resolution detection approaches and limited sample sizes to character- ize disease-associated changes in intratumoral microbiota. As a result, conclusions drawn from such studies may not fully capture the true biological landscape. Future investigations should apply advanced technologies, including metagen- omic sequencing, spatial transcriptomics, and microbial in situ imaging, to achieve high-resolution and comprehensive profiling of intratumoral microbiota and the interactions with host cells in large-scale, multicenter cohorts. Many existing studies primarily describe associations between intratumoral microbiota composition and clini- cal phenotypes or outcomes, while underlying mechanisms remain largely unexplored. Future work should integrate experimental models, such as organoids and xenograft sys- tems with germ-free animals, to mechanistically define how specific microbes or the components drive tumorigenesis, immune modulation or evasion, and therapy resistance. Such approaches will be essential for identifying concrete molecular mechanisms and actionable therapeutic targets. The ultimate objective is to develop precise and personal- ized therapies targeting intratumoral microbiota. With deeper functional insight into intratumoral microbial activity, a new generation of precision microecologic therapies may emerge. Potential strategies include engineered phages designed to selectively eliminate pro-carcinogenic bacteria, as well as bac- teria-drug combination therapies aimed at reversing treat- ment resistance through microbiota modulation. In addition, intratumoral microbiota shows promise as a biomarker for predicting therapeutic response and guiding patient stratifica- tion. Nevertheless, translation of these approaches into clini- cal practice will require high-quality prospective studies with larger cohorts and extended follow-up periods.

  generalfuture work
  Keywords: intratumoral microbiota therapeutic future approaches therapies cancer associated microbes specific promise strategies response resolution microbial
• Gut–kidney axis in IgA nephropathy: mechanisms linking microbiota dysbiosis to immune dysregulation, Gd-IgA1 generation, and renal injury (2026) · Frontiers in Immunology · doi

  6.1 Methodological challenges and limitations 6.1.1 The gut microbiota is highly heterogeneous and dynamic Its composition is shaped by multiple factors, including diet, age, geographic location, and medication use. A single time-point stool sample is therefore inadequate to capture the long-term, stable, disease-relevant features of the microbial community (125, 128). 6.1.2 Study design shortcomings are prevalent Most available investigations are cross-sectional in nature, involve small sample sizes, and are performed at single centers. They also lack extended follow-up (≥1–2 years) and standardized protocols for sample collection, sequencing, and data analysis (42, 126). 6.1.3 Technical limitations The resolution of 16S rRNA sequencing is limited, making it difficult to reach the strain level and functional prediction; the costs of metagenomics and metabolomics are high, and they are still not widely available (129, 130). 6.1.4 Insufficient control for confounding factors Concurrent use of medications (such as RAS blockers, immunosuppressants, and antibiotics) and comorbidities (hyper- tension and diabetes) may independently affect the microbiota, leading to false associations (126, 131). 6.2 Key knowledge gaps Despite the substantial progress reviewed above, several key knowledge gaps remain unresolved. 6.2.1 Certainty of causal relationship Although MR studies and FMT experiments in animals support dysbiosis as a driving factor, the long-term and dynamic causal sequence in humans has yet to be established. Longitudinal time- series investigations are required to monitor microbial shifts during the early phases of disease, including the preclinical period, and to align these changes chronologically with IgAN onset (25, 132). 6.2.2 Unclear molecular mechanisms of IgA1 O- glycosylation The regulation of IgA1 O-glycosylation by the microbiota is poorly understood. In addition to the deglycosylase activity of AKK reported in a recent study, other bacterial enzymes may also be involved. It also remains unknown whether host glycosyltransfer- ases such as C1GALT1 and ST6GalNAc-II are modulated by microbial metabolites (109, 110). These questions warrant further mechanistic exploration. 6.2.3 Unidentified upstream microbial ligands The identity of the upstream microbial ligands that engage the TLR4/TLR9–BAFF/APRIL pathway is not yet clear. Potential can- didates include LPS, flagellin, or other PAMPs, but this remains to be determined (22, 60). 6.2.4 Unclear contribution of AhR signaling The direct contribution of AhR signaling to renal injury in IgAN is still unclear. In particular, it is uncertain whether IS- induced trained immunity via AhR occurs in monocytes or mac- rophages of IgAN patients (54). 6.2.5 Limited understanding of complement– microbiota interplay The interplay between complement activation and the gut microbiota remains poorly defined. It is not known whether intestinal-derived PAMPs or metabolites directly modulate the alternative and lectin complement pathways (66, 67). 6.2.6 Translational gaps between animal models and human disease Although humanized mouse models such as a1KI-CD89Tg partially recapitulate IgAN, the complexity of the human microbi- ota, interspecies immune differences, and the prolonged disease course in patients preclude complete replication. Consequently, many interventions that show efficacy in animal models, including probiotics and FMT, exhibit considerably weaker effects in humans than anticipated (24, 28). 6.2.7 Synergistic effect of mucosal microbiota at multiple sites The microbiota in the oral, pharyngeal, and intestinal regions may interact with each other and jointly drive the systemic mucosal immune response. Currently, there is a lack of studies that simul- taneously collect data from multiple sites and conduct longitudinal tracking (84, 133). 6.2.8 Lack of predictive biomarkers Despite the promising performance of diagnostic models, microbiota-based biomarkers for predicting disease progression, response to immunosuppressive therapy, or recurrence risk remain scarce and require further development (119, 134). Addressing these knowledge gaps is critical for translating mech- anistic insights into clinical practice. Notably, recent 2026 multi-omics advances have identified the terminal ileum as the primary source of Gd-IgA1-producing cells, yet the safety and efficacy of targeting the

  generalfuture work
  Keywords: microbiota disease microbial gaps igan models multiple including sample lack knowledge unclear remains whether complement
• Nutrition phenotypes in inflammatory bowel disease: emerging concepts and future directions to guide clinical practice (2026) · Frontiers in Nutrition · doi

  Future studies are needed to translate the nutrition phenotype framework into routine clinical practice. Formal validation through a structured consensus process involving gastroenterologists, dietitians, and patients may help refine phenotype definitions and establish clinically meaningful diagnostic criteria. Incorporation of phenotype identification into clinical workflows, such as electronic health record–based prompts during nutrition screening or IBD clinic visits, could facilitate consistent assessment and longitudinal reassessment as patients transition between phenotypes over time. The framework may also provide a foundation for future clinical trials by enabling stratification of participants according to nutrition phenotype, thereby reducing population heterogeneity and improving evaluation of dietary interventions within more homogeneous patient groups. Such an approach may help identify which patients are most likely to benefit from specific nutritional therapies. In addition, integration of emerging precision nutrition tools, including microbiome profiling, metabolomics, and host genomics, may further refine phenotype classification and support more individualized dietary recommendations.

  generalfuture work
  Keywords: phenotype nutrition clinical patients cation future framework help dietary needed translate routine practice formal validation
• Population-scale analysis reveals limited and non-generalizable associations between the gut microbiome and obesity in Asian adults (2026) · medRxiv · doi

  integrating long-read or strain-aware metagenomic profiling, 571 metatranscriptomics, and stool or serum metabolomics will be necessary to determine 572 whether obesity-associated microbial differences are being masked by the resolution 573 limits of conventional shotgun analysis. 574 Several considerations delimit the scope and interpretation of our findings. First, 575 this study is cross-sectional in design, using baseline stool samples from a prospective 576 cohort; we can therefore infer association but not direction of causation between 577 microbiome composition and adiposity. Second, residual heterogeneity in diet, 578 medication exposure, socioeconomic factors, and lifestyle may obscure associations 579 present only within narrower strata. To probe this, we repeated the differential- 580 abundance analysis within the two subgroups best powered in this cohort (ethnicity 581 and sex) each adjusted for the remaining demographic covariates, including age as a 582 continuous term. The null persisted in every stratum: the conservative method 583 (MaAsLin2) recovered at most one species, and no taxon was reproducible across 584 methods beyond chance (Fisher's exact P ≥ 0.18, Supplementary Table 2). It 585 nonetheless remains plausible that associations are more detectable within finer or 586 differently defined strata, dietary patterns or metabolically unhealthy obesity, that we 587 were not powered to resolve. Third, obesity is a heterogeneous phenotype. Although 588 BMI is standard for epidemiological comparability, our null results were robust to the 589 choice of anthropometric adiposity metric. Waist circumference, WHR, and WHtR 590 each reproduced the near-null compositional variance, yielded no differential- 591 abundance associations that replicated across methods, and supported only near- 592 chance classification; where a taxon recurred (B. adolescentis), it did so as a nominal, 593 single-method signal that failed cross-method and enrichment testing 594 (Supplementary Table 1). Deeper adiposity phenotypes such as DEXA-derived body 595 composition, HOMA-IR-based insulin resistance, liver fat fraction, and inflammatory or 596 cardiometabolic biomarkers, may reveal stronger or qualitatively different microbiome medRxiv preprint preprint (which was not certified by peer review) doi: https://doi.org/10.64898/2026.08.12.26358109

  generalfuture work
  Keywords: obesity adiposity associations within null stool cross cohort microbiome composition strata differential abundance powered taxon
• Microbiota as diagnostic biomarkers: advancing early cancer detection and personalized therapeutic approaches through microbiome profiling (2025) · Frontiers in Immunology · cited 45× · doi

  Future research should focus on addressing these challenges by establishing standardized protocols, expanding diverse patient cohorts, and exploring the roles of underrepresented microbial domains, such as viruses and fungi, in cancer biology. Significant challenges remain in spite of these developments, such as the inherent variability of microbiota composition between individuals and populations, the lack of standardized procedures, and the requirement for complete verification of biomarkers obtained from microbiota.

  generalinline gaps
  Keywords: challenges standardized microbiota future focus addressing establishing protocols expanding diverse patient cohorts exploring roles underrepresented
• Microbiome‑based diagnostic biomarkers in pancreatic ductal adenocarcinoma: Current evidence and translational challenges (Review) (2026) · Oncology Letters · doi

  The development of standardized and reproducible methodologies is crucial for translating microbiome research into clinically useful diagnostic tools. The identification of potential diagnostic biomarkers and the development of new diagnostic tests and therapies for PDAC are areas that require further research. The use of multi-omics approaches, such as metagenomics, metatranscriptomics, and metabolomics, may advance PDAC-associated microbiome research.

  generalfuture-work sectionevidence 5/5
  Keywords: development standardized reproducible methodologies crucial translating microbiome research
• Gut dysbiosis in difficult-to-treat rheumatoid arthritis: hypothesized microbial endotypes, persistent inflammation, and pharmacological treatment resistance (2026) · Frontiers in Pharmacology · doi

  Reverse causation is a major concern because chronic inflammation, disease duration, diet, comorbidity, and repeated exposure to DMARDs, glucocorticoids, antibiotics, proton pump inhibitors, and analgesics can all alter the microbiome. Methodological resolution is another constraint, as 16S rRNA sequencing characterizes taxonomic composition, while PICRUSt2 estimates rather than measures functional potential. The study is limited by its cross-sectional, single-sample design and the small number of patients with D2T RA.

  generalstated challengesevidence 5/5
  Keywords: reverse causation major concern because chronic inflammation disease
• The impact of dysbiosis in oropharyngeal and gut microbiota on systemic inflammatory response and short-term prognosis in acute ischemic stroke with preceding infection (2024) · Frontiers in Microbiology · cited 13× · doi

  Our study has several limitations that should be considered. First, while we observed changes in the composition of oropharyngeal and gut microbiota in AIS-PI patients, and noted associations between dysbiotic microbiota and systemic inflammation, stroke severity, and adverse prognosis, we utilized 16S rRNA amplicon sequencing instead of shotgun metagenomic sequencing. This choice limited our ability to identify specific bacteria at the species level. Second, we collected oropharyngeal and fecal microbiota as well as serum samples, at a single time point, restricting our capacity to observe dynamic changes in inflammation levels and microbiota, as well as their real-time interactions with stroke severity and functional outcomes.

  generallimitations sectionevidence 5/5
  Keywords: study has several limitations considered first observed changes

Questions about this gap