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Turning cheese whey into value: a sustainable substrate for probiotic biomass production

 

Authors: Eider Fernandez & Igor Baroja-Careaga, Esneki Zentroa (Leartiker S.COOP)

 

Probiotics are part of a rapidly expanding field of research. They are live microorganisms that, when administered in adequate amounts, may confer health benefits[1]. Among the most extensively studied probiotics, some species of Lactobacillus and Bifidobacterium have been associated with the maintenance of gut microbiota balance and with several physiological functions[2]. Producing these microorganisms usually requires nutrient-rich culture media. But what if such bacteria could be obtained from a food by-product nowadays regarded as waste? This question formed the starting point of a study carried out by Esneki Dairy Centre – Leartiker to assess the potential of cheese whey as a substrate for producing microbial biomass enriched in microorganisms with probiotic potential.

The challenge of cheese whey

Cheesemaking inevitably generates substantial amounts of whey: a yellowish liquid released from the curd that still carries lactose, soluble proteins, minerals and other valuable compounds. In fact, whey can represent around 85% of the original milk volume used in cheese production[3].

Despite this nutritional richness, whey remains a difficult stream to manage for many artisanal dairies. This is particularly true in the Basque Country, where many cheesemaking farms are small, family-run businesses located in rural areas[4]. Its highly perishable nature means that whey must be preserved or processed soon after production, making storage, collection and transport especially challenging when volumes are small and geographically dispersed.

Moreover, uncontrolled whey discharge results in a high organic load that can affect aquatic ecosystems. Paradoxically, the same nutrients that make cheese whey a potential pollutant are also what give it considerable biotechnological value.

A natural culture medium

From a microbiological standpoint, cheese whey is not merely a residual stream, but a naturally nutrient-rich matrix[5]. Its lactose content, together with soluble proteins, minerals and other available compounds, provides a favourable environment for the growth of lactic acid bacteria, widely used microorganisms in fermented foods and increasingly explored for their probiotic potential.

The working hypothesis was simple: by steering whey fermentation under controlled conditions, it could be possible to recover a biomass enriched in microorganisms of interest, while at the same time increasing the stability and value of the by-product itself.

To explore this possibility, several fermentation strategies were tested using whey generated during the production of blue cheese from pasteurised cow’s milk. The study compared three different approaches:

  • Fermentation of previously pasteurised whey (Protocol 1).
  • Fermentation of whey after a deproteinisation step (Protocol 2).
  • Direct fermentation of raw whey, without any prior treatment (Protocol 3).

Two different blends of commercial microorganisms, inspired by the naturally diverse microbial communities found in kefir, were also evaluated. These included; Choozit Kefir DV LYO 1000L (Danisco) (starter culture A) and Ferlac Kefir Type C (Abiasa) (starter culture B). Additionally, unfermented whey (that is, whey to which no starter cultures were added and which was not subjected to fermentation) from each protocol was analysed as a control sample. Controlled fermentation processes were carried out under monitored conditions. Throughout the fermentation, key parameters were monitored, including temperature (25 ± 1 °C), incubation time (16 ± 1 h for starter culture A and 21 ± 1 h for starter culture B) and pH evolution, with fermentation being considered complete once the pH fell below 4,6. These measurements allowed the identification of the conditions that most effectively supported the growth and enrichment of the target microbial populations.

 

Exploring the microbiome through metagenomics

However, assessing the success of a fermentation process requires more than simply determining how many microorganisms grow. It is also essential to identify which species are present and how the microbial community changes over time.

Traditional culture-based microbiological methods remain fundamental tools for quantifying and isolating viable microorganisms. Yet they have important limitations when complex microbial communities need to be characterised, as they only detect microorganisms able to grow under the selected culture conditions. As a result, part of the microbial diversity present in the sample may remain undetected. To obtain a more comprehensive view of the microbial community, the study incorporated high-throughput amplicon sequencing, an approach that enables the direct analysis of DNA present in a sample and the identification of microorganisms regardless of their ability to grow under laboratory conditions.

Bacterial communities were characterised by amplifying the V4 region of the 16S rRNA gene, one of the most widely used markers in bacterial diversity studies. Fungal and yeast communities were analysed through the ITS region — the Internal Transcribed Spacer — which is considered the standard marker for fungal diversity studies.

Sequencing was performed using Illumina technology, generating approximately 100,000 reads per sample for bacteria and around 40,000 reads for fungi and yeasts. These sequences were then compared against specialised databases to determine the identity of the microorganisms present and estimate their relative abundance.

Before interpreting the results, sequencing depth was assessed using rarefaction curves. These curves showed a clear trend towards saturation, indicating that most of the microbial diversity present in the samples had been adequately captured.

Which protocol worked best?

High-throughput amplicon sequencing revealed clear differences among the fermentation strategies tested.

Fermentations carried out using raw whey (Protocol 3) maintained a more diverse bacterial community than those in which the whey had first been subjected to thermal treatment (Protocol 1 and Protocol 2), as can be seen in Figure 1, as can be seen in Figure 1, the number of observed microbial taxa increases with sequencing depth. This suggests that the partial preservation of the native microbiota originating from the cheesemaking process may play an important role in shaping the fermentation outcome.

 

 

whey
Figure 1. Rarefaction curve illustrating the observed bacterial species richness as the number of sequences increases.

 

In contrast, the diversity of moulds and yeasts decreased. This trend may be related to the origin of the whey, which was obtained from blue cheese production, where specific mould (Penicillium roquefoti) species are deliberately enriched during manufacture. The competitive advantage of these dominant fungi appears to favour the development of a more specialised microbial community, reducing the abundance and diversity of other microbial populations present in the whey (Figure 2).

 

whey
Figure 2: Rarefaction curve showing the number of observed mould and yeast species as a function of sequencing depth

 

Principal coordinates analysis (PCoA) based on Jaccard distances (Figure 3) showed a clear separation among the different fermentation protocols, indicating that each strategy gave rise to distinct microbial communities. In parallel, the relative abundance of profiles (Figure 4) made it possible to visualise how particular species increased or decreased depending on the conditions applied.

Figure 3. PCoA based on Jaccard distances, used to assess similarities among samples. Bacterial profiles based on 16S data are shown on the left, and fungal/yeast profiles based on ITS data on the right.

 

 

 

Figure 4. Relative microbial diversity observed across the different fermentation protocols.

 

Amplicon sequencing also enabled the identification of the dominant microorganisms during the process. In most samples, Lactococcus lactis was particularly abundant. This result was expected, as this bacterium was included in the commercial starts cultures used and is widely employed in dairy fermentations. However, some fermentation conditions, particularly those involving starter culture B, also favoured the development of species such as Lacticaseibacillus rhamnosus and Bifidobacterium animalis, wich were also present in the commercial starter culture. These microorganisms are frequently associated with probiotic applications[6],[7],[8].

To identify the most suitable protocol for producing a fermented whey enriched in microorganisms with probiotic potential, both microbial abundance (including aerobic mesophilic bacteria, yeasts and moulds) and the diversity of the resulting microbial communities were evaluated. The highest microbial counts were obtained in whey samples produced using Protocol 3, which was based on raw whey, and fermented with starter culture B. (Average counts of 8.2 log CFU/mL were obtained with starter culture A, and average counts of 8.5 log CFU/mL with starter culture B).

Furthermore, as mentioned previously, the highest levels of microbial diversity were observed in the samples produced using Protocol 3, where fermentation was carried out directly on raw whey without prior heat treatment.

 

Overall, the results pointed to the most effective strategy also being the simplest from a technological perspective: the direct fermentation of raw whey, without prior thermal treatment using starter culture B. This approach maintained high microbial diversity while reducing energy requirements and simplifying the overall process.

An opportunity for the circular economy

Beyond the microbiological results, the broader relevance of this work lies in showing that the role of whey within the cheesemaking chain can be reconsidered.

Rather than being treated as a waste stream associated with management costs, whey can be viewed as a raw material capable of supporting valuable biotechnological processes. Controlled fermentation not only helps stabilise whey but also makes it possible to harness the nutrients it still contains to generate added-value microbial biomass.

Such strategies are closely aligned with the principles of the circular bioeconomy, in which by-products are no longer seen as the end of a production chain, but as the starting point for another. In a context where sustainability and efficient resource use are increasingly important, initiatives of this kind show how microbiology and omics technologies can help turn an environmental challenge into an opportunity for innovation.

 

The PRO2O project (grant agreement No. 00003-BIO2022-48) was funded through the 2022 Bioeconomy Innovation Projects funding programme of the Basque Government’s Department of Economic Development, Sustainability and Environment.

References

[1] Guarner F, Requena T, Marcos A. Consensus statements from the Workshop “Probiotics and Health: Scientific evidence”. Nutr Hosp. 2010 Sep-Oct;25(5):700-4. PMID: 21336423.

[2] Martin, A. J. M., Serebrinsky-Duek, K., Riquelme, E., Saa, P., & Garrido, D. (2023). Microbial interactions and the homeostasis of the gut microbiome: the role of Bifidobacterium. Microbiome Research Reports, 2. https://doi.org/10.20517/mrr.2023.10

[3] González Siso, M. I. (1996). The biotechnological utilization of cheese whey: A review. Bioresource Technology, 57(1), 1–11. https://doi.org/10.1016/0960-8524(96)00036-3

[4] Esneki Zentroa – Leartiker (2022). “El sector quesero en Euskadi 2021”. Available at: El-sector-quesero-en-Euskadi.pdf

[5] Figueroa Pires, A., garcía Marnotes, N., Díaz Rubio, O., Cobos García, A., Dias Pereira, C. (2021). Dairy by-products: A review on the valorization of whey and second cheese whey. Foods, 10: 1067

[6]Neethu, M., Bunt, C., Hussain, M., 2015. Comparison of Microbiological and Probiotic Characteristics of Lactobacilli Isolates from Daity FOod Products and Animal Rumen Contens Microorganims 3, 198-212.

[7] Rama, G.R., Kuhn, D., Beux, S., aciel, M.J., Volken de Souz, C.F., 2019. Potential apllications of dairy why for the production of lactic acid bacteira cultures. Int Dairy J.

[8] Rodriguez-Palacios, 1., Staemplfli, H.R., Duffield, T., Weese, J.S., 009. Isolation of bovine intestinal Lactobacillus plantarum and Pediococcus acidilactici with inhibitory activity against Escherichia coli O157 and F5. J. Appl. Mcrobiol. 106, 393-401

 

The BRTA is a consortium that remains a step ahead of future socio-economic challenges worldwide and in the Basque Autonomous Community; it addresses them through research and technological development, thus projecting itself internationally. The BRTA centres collaborate to generate knowledge and transfer it to Basque society and industry so as to make them more innovative and competitive. The BRTA is an alliance of 17 R&D centres and cooperative research centres with the support of the Basque Government, the SPRI and the Chartered Provincial Councils of Araba, Bizkaia and Gipuzkoa.

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Overcoming bottlenecks in bio-interface simulations: The MartiniSurf Approach

Enzymes and other biomolecules are often anchored onto solid materials so they can be reused, purified more easily, and made more stable, a strategy biotechnology has relied on since industrial-scale immobilized enzymes first appeared in chemical manufacturing in the mid-twentieth century. Immobilized enzymes today drive processes from food and pharmaceutical production to biosensors and medical diagnostics. Fixing a biomolecule in place, however, is not as simple as gluing it down. The exact spot where it attaches, the direction it faces, and how much freedom it retains to move can all change how well it works. Testing every possible arrangement in the laboratory is slow and costly, which is why computer simulation has become such a valuable complement to experiments.

The Martini force field

One of the main tools for this kind of study is molecular dynamics simulation, which calculates how atoms move over time by applying the basic laws of physics. Simulating every single atom of a protein, its surrounding water, and a supporting material gives rich detail, but is extremely demanding on computing power, especially when many attachment geometries need comparing. A widely used shortcut is coarse-grained modeling, in which small clusters of atoms are grouped into single, simplified particles. This keeps the essential physical behavior of the system while making the calculations far cheaper. The most established coarse-grained approach for biological molecules is the Martini force field, first developed in 2004 to describe fatty, membrane-forming molecules and later extended to proteins and, more recently, to a more accurate third generation of the model. Martini has since become a standard tool for simulating large biological assemblies that would otherwise be out of reach.

Introducing MartiniSurf

A team of researchers now introduces MartiniSurf 1, an open-source software package that automates the preparation of these coarse-grained simulations for biomolecules attached to surfaces. Building such a system by hand normally involves several separate programs and many manual steps, which makes it hard to reproduce results or compare different setups fairly. MartiniSurf instead combines the whole process into a single, streamlined workflow. Starting from the structure of a protein or a DNA strand, it converts the molecule into its coarse-grained form, builds a model of the supporting surface, positions the molecule in a chosen orientation, adds water and dissolved ions, and produces all the files needed to run the simulation with GROMACS, a molecular dynamics program that has been developed and refined for decades. Because every step is controlled by explicit settings rather than manual adjustments, two researchers using the same settings should obtain the same starting system, making comparisons across studies far more reliable.

MartiniSurf
Overview of the MartiniSurf workflow for constructing surface-immobilized biomolecular systems for coarse-grained molecular dynamics.

Restraining forces or linkers

A central feature of the software is its flexibility in representing how a biomolecule is attached. In one mode, selected regions of the molecule are held near the surface through simple restraining forces, without modeling the physical connector itself. In another mode, an explicit molecular linker is placed between the biomolecule and the surface, so that the linker’s own length and flexibility can influence the simulation. Because the properties of such linkers are known to affect how active and stable an attached enzyme remains, this second option offers a more realistic picture whenever the necessary coarse-grained description of the linker is available.

Variety of supporting surfaces

The supporting surfaces themselves can also be varied widely. The software can generate simple flat reference surfaces or draw on previously developed coarse-grained models of real materials such as graphene, graphite, carbon nanotubes, and agarose-like gels, the type of porous material commonly used to immobilize enzymes in the laboratory. Properties such as surface chemistry, electric charge, particle spacing, and added chemical groups can all be adjusted. Recent studies have shown that surfaces built without care can cause water molecules near the interface to line up in unrealistic, almost frozen patterns, an artifact rather than genuine physical behavior. The software includes options that let users introduce controlled irregularity into the surface to reduce this problem, while staying consistent with the wider Martini modeling framework.

In practice

To demonstrate how the approach works in practice, the study presents examples involving both proteins and DNA. For an enzyme attached to an agarose-like surface, the software reproduces several different attachment arrangements, including a complete system containing the enzyme together with its natural helper molecule and reaction substrate. These examples show how changing the attachment point or adding chemical groups to the surface can be explored systematically, without needing to reconstruct every model from scratch by hand.

The approach is also extended to DNA tethered to a graphene-like surface, comparing an electrically neutral surface with a positively charged one. The coarse-grained simulations reproduce the same general behavior previously reported in much more computationally demanding all-atom studies: the DNA strand remains mostly upright above the neutral surface but bends progressively toward the surface when it carries a positive charge, drawn in by electrostatic attraction. This comparison is not meant to reproduce exact experimental values, but rather to confirm that the automated setup captures the right physical trends, providing a check on the reliability of the workflow.

Reproducibility

Every simulation generated by the software automatically records the settings, software versions, and modeling choices used to build it, so that another researcher can repeat or directly compare a given calculation later. Importantly, the software does not introduce new physical models or new force-field parameters of its own. Instead, it draws on already validated Martini tools and organizes them into a consistent, automated pipeline.

Overall, MartiniSurf addresses a practical bottleneck in computational chemistry rather than proposing a new simulation method. By automating the construction of surface-bound protein and DNA systems, it makes coarse-grained molecular dynamics studies faster to set up, easier to reproduce, and simpler to scale across many attachment geometries. This kind of tool should make it easier to systematically study how surface properties, attachment geometry, and molecular flexibility shape the behavior of immobilized biomolecules, supporting the design of better catalysts, biosensors, and other biotechnology applications.

Author: César Tomé López is a science writer and the editor of Mapping Ignorance

Disclaimer: Parts of this article may have been copied verbatim or almost verbatim from the referenced research paper/s.

References

  1. J. C. Jimenez-Garcia, F. Lopez-Gallego, X. Lopez, and D. De Sancho (2026) MartiniSurf: Automated simulations of surface-immobilized biomolecular systems with Martini J. Chem Inf. Model. doi:10.1021/acs.jcim.6c00953 ↩

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