The relationship between diet, the microbiota and metabolic health is now one of the most dynamic fields of translational research. The most recent reviews show that the microbiota is not merely an accessory component of the gut ecosystem, but contributes to the co-digestion of nutrients, the production of bioactive metabolites and the modulation of immune, intestinal and cardiometabolic functions.[1][2]

This evidence, however, must be communicated with rigour. Enthusiasm for the microbiota has led to a proliferation of oversimplified products on the market, often presented as tools capable of converting a microbial profile into direct nutritional recommendations. The international consensus statement published in 2025 in Lancet Gastroenterology & Hepatology emphasises, however, that whilst interest in microbiome testing is growing, its clinical utility requires clear guidelines, standardisation of pre-analytical procedures, robust methods and reporting criteria that prevent inappropriate testing and over-interpretation.[3]

For this reason, when discussing “microbiota-guided nutritional personalisation”, the right question is not whether the microbiota is of interest. It is. The right question is: in what context of use, with which biomarkers, using which analytical method, and leading to what kind of downstream decision? In this context, microbiota profiling should not be treated as a consumer gadget, but as a potential component of more structured B2B services: professional nutritional programmes, nutraceutical development, quality control of botanical ingredients or probiotics, co-development of targeted panels, and monitoring of OEM workflows.

The gut microbiota is a key biological mediator in the relationship between diet and the body’s response. Different dietary patterns — Western, Mediterranean, high-fibre, plant-based, high-protein or ketogenic — can alter the composition, function and stability of the microbial ecosystem, with potential effects on energy metabolism, the intestinal barrier, inflammation and immune signalling.[1] [2]

This perspective helps to explain the heterogeneity of individual responses. Two individuals with apparently similar clinical characteristics may respond differently to the same dietary pattern, partly because they differ in microbial composition, fermentative capacity, production of short-chain fatty acids or the presence of functionally relevant species.[1] [6]

The microbiota, therefore, can enhance personalised nutrition by adding a biological dimension to demographic, anthropometric, metabolic, behavioural and dietary data. But precisely for this reason, the quality of the test becomes crucial. The more microbiological data is used to guide a service, the more robust, reproducible, interpretable and consistent with a specific application it must be.[3]

One of the limitations of the public debate on the microbiota is the tendency to pit qPCR against NGS as if one technology were destined to replace the other. In reality, the two technologies serve different purposes within the same workflow. Sequencing is essential when the objective is exploratory: characterising complex microbial communities, identifying biological signatures, generating hypotheses, selecting new biomarkers and evaluating as yet undefined patterns. It is therefore particularly relevant during the discovery and early development phases.

Targeted qPCR can be particularly useful when the analytical question is already defined and the objective is to measure selected targets in a rapid, repeatable and operational manner. A 2024 study developed a qPCR panel for 45 core microbes of the human gut microbiota and compared the method with metagenomics, demonstrating the potential of qPCR as a simple and rapid tool for quantifying relevant targets.[4]

The study remains methodological and does not in itself demonstrate clinical utility, but it supports the technical rationale for targeted panels. Also in 2024, a study published in Microbiome showed that qPCR approaches using kit-based extraction can achieve good accuracy in the absolute quantification of bacterial strains in faecal samples, with advantages in terms of sensitivity, reproducibility, cost and turnaround time compared to other solutions for specific targets. [5]

Here too, the correct message is not that qPCR ‘solves’ microbiota testing, but that it can be a highly suitable technology when targets are selected and the workflow is validated. For a serious personalised nutrition programme, the complementarity is clear: NGS can help identify which signals warrant attention; qPCR can help translate selected signals into targeted, scalable panels that are more compatible with operational workflows.

The idea that the microbiota may help explain the heterogeneity of the dietary response does not stem from a single publication. The work by Zeevi and colleagues in *Cell* showed that the postprandial glycaemic response varies widely between individuals and that a model incorporating clinical parameters, lifestyle habits, anthropometric data, physical activity and the microbiota can better predict these differences than universal recommendations. [6]

More recently, a randomised trial published in Nature Medicine evaluated a personalised nutrition programme based on multiple individual data points, including the microbiome, clinical history and postprandial responses. The programme produced improvements in certain cardiometabolic and body composition parameters compared to standard dietary advice, although there were no significant differences for all endpoints assessed. [7]

This point is important: the study supports the potential of multifactorial personalised nutrition, not the idea that a single microbiota test is sufficient to determine what a person should eat. Regarding the stratification of responders, research on the Prevotella/Bacteroides ratio remains of interest. In a post-hoc study on diets with varying fibre intakes, subjects with a higher Prevotella/Bacteroides ratio showed greater weight and fat mass loss, suggesting that certain microbiota profiles may help identify responders to specific nutritional strategies.[8]

However, as these are post-hoc analyses involving limited populations, this type of evidence should be communicated as a promising signal, not as a general clinical rule. The most defensible message is therefore this: the literature supports the direction, not a shortcut. The microbiota can contribute to more biologically informed nutritional programmes, but only if integrated with other individual data and interpreted within the limits of the available evidence. [3]

Within the new organisational structure of Helyx Industries S.p.A., the microbiota–nutraceuticals focus is not merely an afterthought: it is one of the key elements through which the group’s industrial structure can be understood coherently. The company operates through three divisions — Hyris, Vytro and Mytho — which cover complementary areas of molecular biology, ranging from qPCR to deep multiplexing and NGS. [9]

For this article, the key division is Hyris. Hyris oversees the Hyris System™ (bCUBE™, bAPP™ and proprietary reagents), solutions for distributed qPCR, the Agrifood & Nutraceuticals sector, and Development Services & OEM.[10]

In its nutraceuticals catalogue, Hyris offers kits for the genetic identification of botanicals and probiotics intended for quality control and supply chain management in the nutraceutical sector.[11]

This foundation is strategically significant because it positions Helyx Industries S.p.A. within an existing dialogue with nutraceutical operators: biomass identification, ingredient control, support for more traceable supply chains and OEM development. However, this is not evidence of clinical validation of a microbiota test: it is evidence of industrial positioning, platform capability and presence in a related B2B segment. Mytho, the division dedicated to custom NGS projects, may be the most appropriate solution when the issue is exploratory and requires discovery or highly complex panels. [9]

Vytro may, in the long term, represent the most appropriate framework for any regulated clinical applications, but only once the intended use, analytical performance, clinical performance and regulatory requirements have been defined and met. This distinction is essential: research, nutraceutical OEM and regulated clinical use are not on the same level.

If one strips away the pseudoscientific hype, the most credible use cases in the nutraceutical sector are less spectacular but more robust. The first is the quality control of botanical ingredients and probiotics, an area already explicitly covered by Hyris. [11]

The second is the co-development of targeted panels for specific application questions: response to fibre or prebiotics, monitoring of selected strains, verification of microbial biomarkers linked to professional nutritional programmes. The third is the integration of testing into structured OEM services, with workflows that are designed, verified and monitored. Hyris’s OEM model is significant because it is presented not merely as the supply of equipment, but as a structured process: scientific brief, target definition, panel design, experimental validation, OEM production and post-market monitoring via software layers.[12]

This model can be very useful for nutraceutical partners seeking to build more robust services that are less reliant on generic claims. The bAPP™ platform can support operational management, data aggregation, monitoring, reporting and assisted interpretation of results, within workflows configured and controlled for the specific intended use.[13]

In a sensitive field such as microbiota and nutrition, the key word is not absolute automation, but governance: who interprets the data, by what rules, within what limits and with what responsibility. The portability of bCUBE™ has also been described in peer-reviewed literature in specific molecular applications, particularly SARS-CoV-2.[14][15]

This evidence supports the operational rationale of the platform in decentralised workflows, but does not automatically demonstrate the validity of any potential microbiota test. Each panel, indication and context of use requires its own validation. For a nutraceutical OEM, therefore, the point is not to resell a generic ‘microbiota test’. The point is to build an offering with greater scientific rigour: selecting relevant biomarkers, defining a concrete application, designing a coherent panel, validating the workflow, integrating the data into a professional programme and communicating the result without exceeding the limits of the evidence.

Microbiome profiling applied to personalised nutrition is a field with great potential, but only if it is freed from the logic of consumer simplification. The latest evidence confirms that the microbiome, diet and metabolic response are interconnected; some personalised nutrition programmes based on multiple individual data points have demonstrated measurable benefits in specific outcomes.[1][6] [7]

At the same time, the international clinical consensus calls for the avoidance of vague tests, redundant reports and conclusions that go beyond the strength of the available data. [3]

The key distinction is therefore between generic profiling and targeted measurement. The most defensible future lies not in ‘all-encompassing’ tests without clear downstream decisions, but in well-designed panels linked to precise questions and integrated into robust workflows. Within the new structure of Helyx Industries S.p.A., this scenario finds concrete industrial coherence. Mytho can support the NGS discovery phase; Hyris is the division naturally positioned for distributed qPCR, OEM co-development and nutraceutical applications; Vytro can represent the scope for potential clinical developments, when supported by appropriate validation and regulatory requirements.[9][10][11][12]

From this perspective, the microbiota is not merely an interesting editorial topic. It is a sector in which Helyx Industries S.p.A. can demonstrate technological continuity, scientific rigour and B2B potential, whilst adhering to a firm principle: not to transform a promising signal into a clinical promise, and not to transform a technological platform into specific evidence for every possible application.