RNA-based sandwich hybridisation method for detection of lactic acid bacteria in brewery samples

Sandwich Hybridization Assay for In Situ Real-Time Cyanobacterial Detection and Monitoring: A Review

As cyanobacterial harmful algal bloom (cHAB) events increase in scale, severity, frequency, and duration around the world, rapid and accurate monitoring and characterization tools have become critically essential for regulatory and management decision-making. The composition of cHAB-forming cyanobacteria community can change significantly over time and space and be altered by sample preservation and transportation, making in situ monitoring necessary to obtain real-time and localized information. Sandwich hybridization assay (SHA) utilizes capture oligonucleotide probes for sensitive detection of target-specific nucleic acid sequences. As an amplification-free molecular biology technology, SHA can be adapted for in-situ, real-time or near real-time detection and qualitatively or semi-quantitatively monitoring of cHAB-forming cyanobacteria, owing to its characteristics such as being rapid, portable, inexpensive, and amenable to automation, high sensitivity, specificity and robustness, and multiplexing (i.e., detecting multiple targets simultaneously). Despite its successful application in the monitoring of marine and freshwater phytoplankton, there is still room for improvement. The ability to identify a cHAB community rapidly would decrease delays in cyanotoxin analyses, reduce costs, and increase sample throughput, allowing for timely actions to improve environmental and human health and the understanding of short- and long-term bloom dynamics. Real-time detection and quantitation of HAB-forming cyanobacteria is essential for improving environmental and public health and reducing associated costs. We review and propose to apply SHA for in situ cHABs monitoring.

Survey of microbes in industrial-scale second-generation bioethanol production for better process knowledge and operation

The microbes present in bioethanol production processes have been previously studied in laboratory-scale experiments, but there is a lack of information on full-scale industrial processes. In this study, the microbial communities of three industrial bioethanol production processes were characterized using several methods. The samples originated from second-generation bioethanol plants that produce fuel ethanol from biowaste, food industry side streams, or sawdust. Amplicon sequencing targeting bacteria, archaea, and fungi was used to explore the microbes present in biofuel production and anaerobic digestion of wastewater and sludge. Biofilm-forming lactic acid bacteria and wild yeasts were identified in fermentation samples of a full-scale plant that uses biowaste as feedstock. During the 20-month monitoring period, the anaerobic digester adapted to the bioethanol process waste with a shift in methanogen profile indicating acclimatization to high concentrations of ammonia. Amplicon sequencing does not specifically target living microbes. The same is true for indirect parameters, such as low pH, metabolites, or genes of lactic acid bacteria. Since rapid identification of living microbes would be indispensable for process management, a commercial method was tested that detects them by measuring the rRNA of selected microbial groups. Small-scale testing indicated that the method gives results comparable with plate counts and microscopic counting, especially for bacterial quantification. The applicability of the method was verified in an industrial bioethanol plant, inspecting the clean-in-place process quality and detecting viability during yeast separation. The results supported it as a fast and promising tool for monitoring microbes throughout industrial bioethanol processes.

Identification of beer-spoilage bacteria using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Applicability of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for identification of beer-spoilage bacteria was examined. To achieve this, an extensive identification database was constructed comprising more than 4200 mass spectra, including biological and technical replicates derived from 273 acetic acid bacteria (AAB) and lactic acid bacteria (LAB), covering a total of 52 species, grown on at least three growth media. Sequence analysis of protein coding genes was used to verify aberrant MALDI-TOF MS identification results and confirmed the earlier misidentification of 34 AAB and LAB strains. In total, 348 isolates were collected from culture media inoculated with 14 spoiled beer and brewery samples. Peak-based numerical analysis of MALDI-TOF MS spectra allowed a straightforward species identification of 327 (94.0%) isolates. The remaining isolates clustered separately and were assigned through sequence analysis of protein coding genes either to species not known as beer-spoilage bacteria, and thus not present in the database, or to novel AAB species. An alternative, classifier-based approach for the identification of spoilage bacteria was evaluated by combining the identification results obtained through peak-based cluster analysis and sequence analysis of protein coding genes as a standard. In total, 263 out of 348 isolates (75.6%) were correctly identified at species level and 24 isolates (6.9%) were misidentified. In addition, the identification results of 50 isolates (14.4%) were considered unreliable, and 11 isolates (3.2%) could not be identified. The present study demonstrated that MALDI-TOF MS is well-suited for the rapid, high-throughput and accurate identification of bacteria isolated from spoiled beer and brewery samples, which makes the technique appropriate for routine microbial quality control in the brewing industry.

Quantitative and sensitive RNA based detection of Bacillus spores

The fast and reliable detection of bacterial spores is of great importance and still remains a challenge. Here we describe a direct RNA-based diagnostic method for the specific detection of viable bacterial spores which does not depends on an enzymatic amplification step and therefore is directly appropriate for quantification. The procedure includes the following steps: (i) heat activation of spores, (ii) germination and enrichment cultivation, (iii) cell lysis, and (iv) analysis of 16S rRNA in crude cell lysates using a sandwich hybridization assay. The sensitivity of the method is dependent on the cultivation time and the detection limit; it is possible to detect 10 spores per ml when the RNA analysis is performed after 6 h of enrichment cultivation. At spore concentrations above 10(6) spores per ml the cultivation time can be shortened to 30 min. Total analysis times are in the range of 2-8 h depending on the spore concentration in samples. The developed procedure is optimized at the example of Bacillus subtilis spores but should be applicable to other organisms. The new method can easily be modified for other target RNAs and is suitable for specific detection of spores from known groups of organisms.

Identification of the bacterial community responsible for traditional fermentation during sour cassava starch, cachaça and minas cheese production using culture-independent 16s rRNA gene sequence analysis

We used a cultivation-independent, clone library-based 16S rRNA gene sequence analysis to identify bacterial communities present during traditional fermentation in sour cassava starch, cachaça and cheese production in Brazil. Partial 16S rRNA gene clone sequences from sour cassava starch samples collected on day five of the fermentation process indicated that Leuconostoc citreum was the most prevalent species, representing 47.6% of the clones. After 27 days of fermentation, clones (GenBank accession numbers GQ999786 and GQ999788) related to unculturable bacteria were the most prevalent, representing 43.8% of the clones from the bacterial community analyzed. The clone represented by the sequence GQ999786 was the most prevalent at the end of the fermentation period. The majority of clones obtained from cachaça samples during the fermentation of sugar cane juice were from the genus Lactobacillus. Lactobacillus nagelli was the most prevalent at the beginning of the fermentation process, representing 76.9% of the clones analyzed. After 21 days, Lactobacillus harbinensis was the most prevalent species, representing 75% of the total clones. At the end of the fermentation period, Lactobacillus buchneri was the most prevalent species, representing 57.9% of the total clones. In the Minas cheese samples, Lactococcus lactis was the most prevalent species after seven days of ripening. After 60 days of ripening, Streptococcus salivarius was the most prevalent species. Our data show that these three fermentation processes are conducted by a succession of bacterial species, of which lactic acid bacteria are the most prevalent.

Detection of Escherichia coli in meat with an electrochemical biochip

Detection of foodborne pathogenic and spoilage bacteria by RNA-DNA hybridization is an alternative to traditional microbiological procedures. To achieve high sensitivity with RNA-DNA-based methods, efficient bacterial lysis and release of nucleic acids from bacteria are needed. Here we report the specific detection of the hygiene indicator microorganism Escherichia coli in meat by use of electrochemical biochips. We improved RNA isolation from bacteria in meat juice from pork and beef. Samples, either naturally or artificially contaminated by E. coli, were enriched by incubation in full or minimal medium. A combined treatment of the samples with lysozyme, proteinase K, and sonication resulted in efficient cell disruption and high total RNA yields. Together with optimization of enrichment time, this ensures high sensitivity of electrochemical measurements on biochips. A short enrichment period and the triple-lysis regimen in combination with electrochemical biochip measurement were tested with 25 meat samples. The lower limit of detection of the biochip was approximately 2,000 CFU of E. coli per ml. The entire analysis procedure (5 h of enrichment, triple lysis, and biochip detection) has a lower limit of detection of 1 CFU of E. coli per ml within a total time needed for analysis of 7 h.

An easily-automated assay for the physiological state quantification of Pseudomonas sp. M18

In order to foreknow poorly performing cultures before wasting energy to scale them to large cultures, industrial microbial fermentation can greatly benefit from knowledge of the physiological state of cells. The method currently proposed is an easily automated physiological state determination method. We have designed one universal rRNA-specific probe for bacteria and developed novel signal probe hybridization (SPH) assay featuring no RNA extraction and no PCR amplification steps necessary to quantify the physiological state of microbial cells. The microbial cell was lysed with sonication and SDS. Signal probes were applied to hybridize and protect the rRNA target. S1 nuclease was then applied to remove the excessive signal probes, the single-stranded RNA and the mismatch RNA/DNA hybrids. The remaining signal probe was captured with a corresponding capture probe immobilized on a microplate and quantified with a horseradish peroxidase-conjugated color reaction. We then systemically optimized our assay. Results showed that the cell limit of detection (LOD) and the cell limit of quantification (LOQ) were 2.64 x 10(4) cells and 9.86 x 10(4) cells per well of microplate, respectively. The limit of detection (LOD) and the limit of quantification (LOQ) of signal probe were 49.0 fM and 344.0 fM respectively. Using this technique, we quantified the 16S rRNA levels during the fermentation process of Pseudomonas sp. M18. Our results indicate that the 16S rRNA levels can directly inform us about the physiological state of microbial cells. This technique has great potential for application to the microbial fermentation industry.

Sandwich hybridization assay for sensitive detection of dynamic changes in mRNA transcript levels in crude Escherichia coli cell extracts in response to copper ions

Transcript quantification techniques usually rely on purified mRNAs. We report here a solution-based sandwich hybridization assay for the quantification of mRNAs from Escherichia coli without the need of prior RNA isolation. This assay makes use of four DNA oligonucleotide probes adjacently hybridizing to target RNA in clarified cell extracts. Two helper probes facilitate the hybridization of a detection and a capture probe. The latter is biotin labeled, allowing binding to streptavidin-coated paramagnetic beads and the separation of the RNA-DNA hybrid from cellular constituents. Added antidigoxigenin Fab fragments conjugated to alkaline phosphatase bind to the digoxigenin-labeled detection probe, completing the sandwich of the paramagnetic bead, mRNA, probes, and alkaline phosphatase. The target transcript can be quantified by assessing phosphatase activity on a substrate that is converted into a fluorescent product. The amount of target mRNA is calculated from the fluorescence output and from a calibration curve for a known concentration of in vitro-synthesized target mRNA. This technique was used in time course experiments to investigate the expression of three genes responsible for the copper resistance of E. coli. The induction of gene expression by copper cations was rapid, but under aerobic conditions, the levels of expression returned to low, prestress levels within minutes. In anaerobiosis, high-level expression continued for at least 1 h. When cultures were shifted from anaerobiosis to aerobiosis, expression levels were diminished within minutes to prestress levels. The improved technique presented here is relatively simple, has very high degrees of sensitivity and robustness, is less laborious than other RNA quantification methods, and is not negatively affected by genomic DNA. These characteristics make it a powerful complementary application to genetic reporter fusions and to reverse transcription-PCR.