Evaluating the Cytometric Detection and Enumeration of the Wine Bacterium, Oenococcus oeni

A flow cytometry method for safe detection of bacterial viability

Flow cytometry is a relevant tool to meet the requirements of academic and industrial research projects aimed at estimating the features of a bacterial population (e.g., quantity, viability, activity). One of the remaining challenges is now the safe assessment of bacterial viability while minimizing the risks inherent to existing protocols. In our core facility at the Paris-Saclay University, we have addressed this issue with two objectives: measuring bacterial viability in biological samples and preventing bacterial contamination and chemical exposure of the staff and cytometers used on the platform. Here, we report the development of a protocol achieving these two objectives, including a viability labeling step before bacteria fixation, which removes the risk of biological exposure, and the decrease of the use of reagents such as propidium iodide (PI), which are dangerous for health (CMR: carcinogenic, mutagenic, and reprotoxic). For this purpose, we looked for a non-CMR viability dye that can irreversibly label dead bacteria before fixation procedures and maintain intense fluorescence after further staining. We decided to test on the bacteria, eFluor Fixable Viability dyes, which are usually used on eukaryotic cells. Since the bacteria had size and granularity characteristics very similar to those associated with flow cytometry background signals, a step of bacterial DNA labeling with SYTO or DRAQ5 was necessarily added to differentiate them from the background. Three marker combinations (viability-DNA) were tested on LSR Fortessa and validated on pure bacterial populations (Gram+ , Gram- ) and polybacterial cultures. Any of the three methods can be used and adapted to the needs of each project and allow users to adapt the combination according to the configuration of their cytometer. Having been tested on six bacterial populations, validated on two cytometers, and repeated at least two times in each evaluated condition, we consider this method reliable in the context of these conditions. The reliability of the results obtained in flow cytometry was successfully validated by applying this protocol to confocal microscopy, permeabilization, and also to follow cultures over time. This flow cytometry protocol for measuring bacterial viability under safer conditions also opens the prospect of its use for further bacterial characterization.

A rapid and reliable method for the determination of Lactiplantibacillus plantarum during wine fermentation based on PMA-CELL-qPCR

Real-time monitoring of microbial dynamics during fermentation is essential for wine quality control. This study developed a method that combines the fluorescent dye propidium monoazide (PMA) with CELL-qPCR, which can distinguish between dead and live microbes for Lactiplantibacillus plantarum. This method could detect the quantity of microbes efficiently and rapidly without DNA extraction during wine fermentation. The results showed that (1) the PMA-CELL-qPCR enumeration method developed for L. plantarum was optimized for PMA treatment concentration, PMA detection sensitivity and multiple conditions of sample pretreatment in wine environment, and the optimized method can accurately quantify 10⁴-10⁸ CFU/mL of the target strain (L. plantarum) in multiple matrices; (2) when the concentration of dead bacteria in the system is 10⁴ times higher than the concentration of live bacteria, there is an error of 0.5-1 lg CFU/mL in the detection results. The optimized sample pretreatment method in wine can effectively reduce the inhibitory components in the qPCR reaction system; (3) the optimized PMA-CELL-qPCR method was used to monitor the dynamic changes of L. plantarum during the fermentation of Cabernet Sauvignon wine, and the results were consistent with the plate counting method. In conclusion, the live bacteria quantification method developed in this study for PMA-CELL-qPCR in L. plantarum wines is accurate in quantification and simple in operation, and can be used as a means to accurately monitor microbial dynamics in wine and other fruit wines.

Challenges and perspectives of quantitative microbiome profiling in food fermentations

Spontaneously fermented foods are consumed and appreciated for thousands of years although they are usually produced with fluctuated productivity and quality, potentially threatening both food safety and food security. To guarantee consistent fermentation productivity and quality, it is essential to control the complex microbiota, the most crucial factor in food fermentations. The prerequisite for the control is to comprehensively understand the structure and function of the microbiota. How to quantify the actual microbiota is of paramount importance. Among various microbial quantitative methods evolved, quantitative microbiome profiling, namely to quantify all microbial taxa by absolute abundance, is the best method to understand the complex microbiota, although it is still at its pioneering stage for food fermentations. Here, we provide an overview of microbial quantitative methods, including the development from conventional methods to the advanced quantitative microbiome profiling, and the application examples of these methods. Moreover, we address potential challenges and perspectives of quantitative microbiome profiling methods, as well as future research needs for the ultimate goal of rational and optimal control of microbiota in spontaneous food fermentations. Our review can serve as reference for the traditional food fermentation sector for stable fermentation productivity, quality and safety.

Organizing the bacterial annotation space with amino acid sequence embeddings

BACKGROUND

Due to the ever-expanding gap between the number of proteins being discovered and their functional characterization, protein function inference remains a fundamental challenge in computational biology. Currently, known protein annotations are organized in human-curated ontologies, however, all possible protein functions may not be organized accurately. Meanwhile, recent advancements in natural language processing and machine learning have developed models which embed amino acid sequences as vectors in n-dimensional space. So far, these embeddings have primarily been used to classify protein sequences using manually constructed protein classification schemes.

RESULTS

In this work, we describe the use of amino acid sequence embeddings as a systematic framework for studying protein ontologies. Using a sequence embedding, we show that the bacterial carbohydrate metabolism class within the SEED annotation system contains 48 clusters of embedded sequences despite this class containing 29 functional labels. Furthermore, by embedding Bacillus amino acid sequences with unknown functions, we show that these unknown sequences form clusters that are likely to have similar biological roles.

CONCLUSIONS

This study demonstrates that amino acid sequence embeddings may be a powerful tool for developing more robust ontologies for annotating protein sequence data. In addition, embeddings may be beneficial for clustering protein sequences with unknown functions and selecting optimal candidate proteins to characterize experimentally.

QTL mapping: an innovative method for investigating the genetic determinism of yeast-bacteria interactions in wine

The two most commonly used wine microorganisms, Saccharomyces cerevisiae yeast and Oenococcus oeni bacteria, are responsible for completion of alcoholic and malolactic fermentation (MLF), respectively. For successful co-inoculation, S. cerevisiae and O. oeni must be able to complete fermentation; however, this relies on compatibility between yeast and bacterial strains. For the first time, quantitative trait loci (QTL) analysis was used to elucidate whether S. cerevisiae genetic makeup can play a role in the ability of O. oeni to complete MLF. Assessment of 67 progeny from a hybrid S. cerevisiae strain (SBxGN), co-inoculated with a single O. oeni strain, SB3, revealed a major QTL linked to MLF completion by O. oeni. This QTL encompassed a well-known translocation, XV-t-XVI, that results in increased SSU1 expression and is functionally linked with numerous phenotypes including lag phase duration and sulphite export and production. A reciprocal hemizygosity assay was performed to elucidate the effect of the gene SSU1 in the SBxGN background. Our results revealed a strong effect of SSU1 haploinsufficiency on O. oeni's ability to complete malolactic fermentation during co-inoculation and pave the way for the implementation of QTL mapping projects for deciphering the genetic bases of microbial interactions. KEY POINTS: • For the first time, QTL analysis has been used to study yeast-bacteria interactions. • A QTL encompassing a translocation, XV-t-XVI, was linked to MLF outcomes. • S. cerevisiae SSU1 haploinsufficiency positively impacted MLF by O. oeni.