Detection of microbes in the malting ecosystem

Early detection of changes in the microbial community is a significant component of quality control in the barley-malt-beer chain. For the maltster it is important to estimate and control microbial activities in order to obtain products

with predetermined malt specifications and suitable quality. However, the current microbial detection and identification approaches are too laborious and time-consuming to be used for routine process control. Furthermore, they often result in an incomplete picture of the true microbial diversity present. Therefore, there is a need for rapid and selective detection and quantification tools providing a reliable estimate of microbial dynamics in the malting process.

Combination of different culture-dependent and -independent methods is often necessary in order to obtain a realistic view of the microbial ecology in a specific environment such as barley and the malting ecosystem. Table 3 compiles the benefits and limitations linked to current culture-dependent and -independent microbial community analyses.

1.4.1 Culture-dependent approach

After harvesting, the microbiological quality of malting barley is normally evaluated by visual and organoleptical inspection by the trader or maltster (Angelino & Bol 1990). Furthermore, the standard methods to assess microbial diversity are based on the enumeration and isolation of species growing on selective or non-selective growth media. Both direct and dilution plating are applied in barley and malting research (Flannigan 2003, Noots et al. 1999).

Selected microbial isolates are then characterized and identified with phenotypic (physiological and biochemical) and genotypic (such as species-specific PCR, DNA fingerprinting, sequencing) approaches (Giraffa & Neviani 2001).

Currently, the standard methods for barley and malt analyses only include detection of fusaria, storage fungi and general field fungi (Abildgren et al. 1987, Gyllang et al. 1981, EBC Analytica Microbiologica 2001). The other microbial groups are not routinely monitored. Colony forming unit estimation is not reliable for filamentous fungi, since it tends to emphasise fungi which readily fragment or produce large numbers of spores. Therefore, filamentous fungi are generally determined by direct plating (Gyllang et al. 1981, Rabie et al. 1997, EBC Analytica Microbiologica 2001). The results are given as percentages of kernels contaminated with different mould genera, also known as the Mold Frequency Index (MFI) (Flannigan & Healy 1983). However, this approach only gives an estimation of the species present, not the degree of infection.

Table 3. Benefits and limitations of culture-dependent and -independent microbial community analyses.

Culture-dependent analysis Culture-independent analysis Cultivation on selective and

non-selective growth media followed by

Visual and organoleptic properties, microscopy, biomass, microbial metabolites (volatile compounds, toxins etc.), antibody techniques or

Direct DNA/RNA approaches such as PCR (PCR-DGGE, RT-PCR, real-time PCR), hybridization (FISH), cloning/sequencing and transcriptional profiling

Benefits Limitations Benefits Limitations + microbes

FISH; fluorescence in situ hybridization, DGGE; denaturing gradient gel electrophoresis, RT-PCR; reverse-transcriptase-polymerase chain reaction

The great advantages of the culture-dependent approach are that individual microbial isolates can be identified, and these are then available for further characterization and exploitation. The major disadvantage is that only few microbes in nature can be isolated in pure cultures (Amann et al. 1995). This is mainly due to the current lack of knowledge of the growth conditions under which certain microbial populations live in their natural habitat. Therefore, only certain microbial groups can be assessed by a culture-dependent approach. In addition, fast-growing organisms can overgrow the slower species in the plate assays, thus hindering their detection.

1.4.2 Culture-independent approach

New powerful analytical tools enable us to investigate complex microbial ecosystems in their natural environment without the need to isolate and culture individual components (Giraffa & Neviani 2001). Generally these are nucleic acid-based methods, although direct microscopy and analyses of microbial metabolites such as mycotoxins can also be included in this category.

Furthermore, immunochemical procedures have been established for the detection of field and storage fungi such as fusaria in barley and malt samples (Vaag 1991). Direct DNA/RNA extraction approaches from environmental samples, coupled with polymerase chain reaction (PCR) amplification and community profiling techniques have become widely applied in studying microbial ecology in complex environments (Ercolini 2004, Muyzer & Smalla 1998). PCR-based methods are more rapid and convenient than the traditional culture-based methods. Furthermore, they also allow the detection of non-culturable species. PCR-primers can be targeted to specific microbial groups, and therefore it is possible to monitor the presence, succession and persistence of certain microbial populations within a complex ecosystem. Recently, diagnostic and quantitative PCR assays have been developed to detect and quantify individual pathogenic fungi within polymicrobial infections, and to detect trichothecene-producing fusaria in barley and malt (Bluhm et al. 2004, Nicholson et al. 2003, Sarlin et al. 2006).

At present, denaturing gradient gel electrophoresis (DGGE) is perhaps the most commonly used culture-independent fingerprinting technique for studying the response of microbial community dynamics. In DGGE, PCR-amplified DNA products with the same length but different sequence can be separated on a gel, resulting in unique fingerprints of environmental DNA samples (Muyzer &

Smalla 1998). Universal PCR-DGGE targeting to ribosomal genes of bacteria and fungi detects the predominant species of a community without discriminating living from dead cells or cells in a non-culturable state. The main populations, which constitute 90–99% of the total community, are displayed in the profiles. This technique has also demonstrated its potential in food-related ecosystems (Ercolini 2004, Giraffa & Neviani 2001) and has been applied in beverage fields such as whisky production (van Beek & Priest 2002, 2003) and wine fermentations (Lopez et al. 2003). Advantages and disadvantages of PCR-DGGE were reviewed by Ercolini (2004) and Muyzer (1999).