# Fermentation of Soy Juice by Lactiplantibacillus plantarum CIRM-BIA777 Produces Flavor-Related and Health-Promoting Metabolites

Olivier Harlé, Sandrine Parayre, Marie-Bernadette Maillard, Gwénaële Henry, Éric Guédon, Anne Thierry, Jérôme Niay, Stéphanie-Marie Deutsch, Hélène Falentin

► To cite this version:

Olivier Harlé, Sandrine Parayre, Marie-Bernadette Maillard, Gwénaële Henry, Éric Guédon, et al. Fermentation of Soy Juice by Lactiplantibacillus plantarum CIRM-BIA777 Produces Flavor-Related and Health-Promoting Metabolites. Food Frontiers, 2025, 10.1002/fft2.70118. hal-05311942

HAL Id: hal-05311942

https://hal.inrae.fr/hal-05311942v1

Submitted on 13 Oct 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
RESEARCH ARTICLE

OPEN ACCESS

# Fermentation of Soy Juice by *Lactiplantibacillus plantarum* CIRM-BIA777 Produces Flavor-Related and Health-Promoting Metabolites

Olivier Harlé<fnref n="1" /> | Sandrine Parayre<fnref n="1" /> | Marie-Bernadette Maillard<fnref n="1" /> | Gwenaële Henry<fnref n="1" /> | Éric Guédon<fnref n="1" /> | Anne Thierry<fnref n="1" /> |
Jérôme Niay² | Stéphanie-Marie Deutsch<fnref n="1" /> | Hélène Falentin<fnref n="1" /> ID |

**Correspondence:** Hélène Falentin (helene.falentin@inrae.fr)

**Received:** 12 August 2024 | **Revised:** 31 July 2025 | **Accepted:** 17 August 2025

**Funding:** This study was funded by "Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement" INRAE (France), Agence Natinale de Recherche Technologique ANRT (France) and the Olga-Triballat company.

**Keywords:** amino acids | aroma compounds | carbohydrates | fermentation | lactic acid bacteria | soy

## ABSTRACT

The fermentation of plant-based beverages, such as organic and locally produced soy juice (SJ), offers a sustainable way to develop dairy alternatives with a low carbon footprint. *Lactiplantibacillus plantarum* (*Lp*) can grow on different raw materials including SJ. The aim of this study was to decipher metabolic pathways involved in (i) the adaptation of *Lp*. CIRM-BIA777 during SJ fermentation, (ii) the formation of metabolites of interest in soy yogurt. The strategy was to sequence, annotate the CIRM-BIA777 genome, to follow its metabolism using transcriptomics and metabolomics targeting carboxylic acids, carbohydrates, free amino acids, volatile compounds, and some vitamins. CIRM-BIA777 used sucrose but only small amounts of galacto-oligosaccharides although alpha-galactosidase was highly expressed. Lactic, citric, and acetic acids were produced, leading to acidification and formation of a yogurt-like structure. The strain expressed several biosynthetic pathways of health-promoting molecules such as gamma-aminobutyric acid, folates and, riboflavin. Fermentation also increased (i) expression of many aroma precursor genes, that is, peptidases, and (ii) the levels of some aroma compounds, for example, phenylethanol and 2,3-butanedione, associated with floral and buttery notes, respectively, while decreasing the levels of some volatiles associated with green and beany off-flavors, for example, hexanal. In conclusion, the fermentation of SJ by CIRM-BIA777 improved its organoleptic and health-promoting properties. For the first time, transcriptomics was used to investigate the molecular mechanisms involved in the formation of aroma and health-promoting metabolites during *L. plantarum* fermentation in soy yogurt. This will help with the development of plant-based fermented foods, particularly legume-based yogurt.

## 1 | Introduction

Soy is a nutritionally interesting food that provides beneficial amino acids and polyunsaturated fatty acids. However, the consumption of soy-based products is limited because of

their "beany" off-flavor and non-digestible carbohydrate content (Fischer et al. 2022). The fermentation of soy juice (SJ) by lactic acid bacteria (LAB) selected to grow and acidify SJ can reduce disadvantages of soy-based products and enhance their acceptability (Fischer et al. 2022). It can also reduce the

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). *Food Frontiers* published by John Wiley & Sons Australia, Ltd and Nanchang University, Northwest University, Jiangsu University, Zhejiang University, Fujian Agriculture and Forestry University.

<footnote n="1">¹STLO, INRAE, Institut Agro, Rennes, France | ²Olga, R&D, Noyal-sur-Vilaine, France</footnote>
content of soy non-digestible oligosaccharides including fructo-
oligosaccharides (FOS) and galacto-oligosaccharides (GOS), like
stachyose and raffinose, thus leading to the reduction of digestive
discomfort (Guillon and Champ 2002).

However, only a limited number of LAB can grow and acidify SJ without added sugars as many of them are unable to use the sugars naturally present in SJ (Boulay et al. 2020; Harlé et al. 2020). In the industry, a rapid acidification and a gel-like texture in less than 8 h of fermentation is expected to produce a yogurt-like product (Harlé et al. 2020). A recent study showed that homolactic LAB species such as *Streptococcus thermophilus* allow a rapid acidification associated with bacterial growth thanks to an efficient fermentation of sucrose, which is the main sugar naturally present in SJ, but did not degrade GOS (Harlé et al. 2020). Moreover, most of the *Lactiplantibacillus plantarum* strains tested in the latter study were able to rapidly acidify SJ and to degrade sucrose and GOS.

The genetic basis of the sucrose, FOS, and GOS degradation have been investigated. It was shown that the sucrose-(phosphate) hydrolase SacA was the most frequently associated with the sucrose phosphotransferase system. The two corresponding genes are located on the same operon of *L. plantarum* genomes (Gänzle and Follador 2012) and are responsible for sucrose degradation. Fermentation of FOS by *L. plantarum* has been studied by several authors. A transcriptomic analyses revealed that *L. plantarum* grew in broth medium containing FOS by using successively homolactic and heterolactic metabolism (Chen et al. 2015). The catabolism of GOS, and particularly that of raffinose and stachyose, involves the expression and activity of an alpha-galactosidase. This pathway has been described in various LAB in a laboratory medium (Gänzle and Follador 2012), in soy whey (Azi et al. 2021), and in SJ (Harlé et al. 2020, 2024) but has not yet been completely elucidated in *L. plantarum* (Greppi et al. 2017; C.-J. Liu et al. 2019). In *L. plantarum* STIII cultures in broth medium containing FOS and glucose, a diauxic growth was observed, indicating a hierarchical utilization of carbohydrates with a preference for glucose. This was associated with a repression of genes involved in FOS degradation (Chen et al. 2015), suggesting a carbon catabolite repression of FOS utilization involving the major transcriptional regulator CcpA encoding the carbon catabolic protein A.

Genome analysis of several *L. plantarum* strains revealed a high potential to degrade many carbohydrates and synthesize amino acids and vitamins (Evanovich et al. 2019; Siezen et al. 2011), giving this species the ability to grow in a wide range of environments. Furthermore, some strains of *L. plantarum* also present interesting nutritional and health properties. For example, *L. plantarum* strains were found to be able to produce riboflavin in laboratory broth (Hernández-Alcántara et al. 2020) and folates in SJ (Greppi et al. 2017; C.-J. Liu et al. 2019).

Organoleptic properties of fermented soy-based products have also been investigated. Recently, *L. plantarum* T1 and CL80 strains have been shown to improve the texture by enhancing the viscosity of fermented SJ and to reduce the aldehyde content of soy, leading to the reduction of “beany” off-flavors (X. Zhang, Zhang, Xiao, et al. 2023). To the best of our knowledge, only one study has addressed the question at the transcriptomic level of the

change in flavor by *L. plantarum*. The transcriptomic study on a solid-state soybean matrix co-fermented with or without *Bacillus velezensis* revealed genes involved in the release of acetoin (Luo et al. 2023).

The aim of the present study was to decipher the metabolic pathways of *L. plantarum* CIRM-BIA777 (hereafter referred to as CIRM-BIA777) involved in (i) the adaptation during SJ fermentation and (ii) the formation of aroma compounds, free amino acids, and carboxylic acids in soy yogurt along the time-course of acidification. This strain was selected among 44 *L. plantarum* strains capable of fermenting SJ for its ability to utilize both stachyose and raffinose and to acidify SJ rapidly (Harlé et al. 2020). Its carbon and nitrogen metabolism during growth in SJ was studied, as well as some secondary metabolisms (vitamin synthesis) and the production of aroma compounds.

The strategy applied to unravel the metabolism of *L. plantarum*
consisted of making soy yogurts with *CIRM-BIA777*. Bacterial
growth and quantification of metabolites of interest were deter-
mined throughout fermentation. Sequencing and annotation of
the genome associated with transcriptomic analysis of genes
differentially expressed during the kinetics allowed to schematize
the metabolism implemented by *CIRM-BIA777* during SJ fermen-
tation and to highlight traits encoded by strain-specific genomic
islands and plasmids.

2 | Material and Methods

## 2.1 | Bacteria and Culture Conditions

*Lactiplantibacillus plantarum* (formerly *Lactobacillus plantarum*; Zheng et al. 2020) CIRM-BIA777 (hereafter referred to as CIRM-BIA777) was provided by the International Center for Microbial Resources-Food Associated Bacteria (CIRM-BIA, https://collection-cirmbia.fr/). Before use, the strain was activated from frozen glycerol stocks (−80°C) in de Man, Rogosa and Sharpe (MRS) (de Man et al. 1960) broth with two consecutive subcultures of 12 h inoculated at 1% v/v and incubated at 37°C.

The SJ used for fermentation was a commercial organic UHT SJ (Sojade, Triballat Noyal SAS, France), previously used by Harlé et al. (2024). The same batch of SJ was used throughout the study and before the expiration date indicated on the packaging. SJ contained 35 g/L of protein, 3.91 g/L of sucrose; 3.11 g/L of stachyose; 0.68 g/L of raffinose; 0.19 g/L of fructose; 0.18 g/L of glucose; and traces of melibiose, maltose, and galactose. Cultures were carried out under static conditions.

## 2.2 | Metabolic Profile

API gallery 50CH (API System, BioMerieux, Marcy l'Etoile, France) was used according to the manufacturer's instructions in order to analyze CIRM-BIA777 carbohydrate fermentation profiles.
## 2.3 | CIRM-BIA777 Whole-Genome Sequencing, Assembly, and Annotation

CIRM-BIA777 cell pellets cultured for 24 h in MRS at 37°C were recovered by centrifugation for 10 min at 5000 × g from 10 mL of a 10⁹ CFU/mL culture assessed by turbidimetry. DNA was extracted using DNeasy midi kit (Qiagen, Courtaboeuf, France) according to the protocol as previously described (Falentin et al. 2016). Genomes were sequenced by Illumina NovaSeq 2x150 pb and PacBio Sequel (Eurofins Genomics, Constance, Germany). Genomes were assembled using Unicycler (Wick et al. 2017) on Galaxy Genotoul bioinformatics platform (Toulouse, France). Genome sequences were integrated to the MicroScope platform hosted at Genoscope (CEA, Evry, France) for automatic annotation (Vallenet et al. 2019). Functional classification was performed using the Kyoto Encyclopedia of Genes and Genomes (Kanehisa et al. 2019), Metacyc annotations (Caspi et al. 2018), and EGGNOG mapper 2 (Cantalapiedra et al. 2021). Cloud and shell genome were determined using PPanGGoLiN tool (Gautreau et al. 2020) embedded in MicroScope platform. Raw sequences and assembly were deposited at European Bioinformatics Institut under accession PRJEB77707.

## 2.4 | SJ Fermentation

The experiments were repeated six times from independent subcultures: three times for monitoring of pH, enumeration, biochemical quantifications and RNA extraction, and three times for additional RNA extractions. SJ was inoculated with CIRM-BIA777 at 1% v/v to target an initial population level around 10⁶ CFU/mL since CIRM-BIA777 reached a plateau around 10⁸ CFU/mL after 12 h of culture in MRS laboratory medium in conditions described in Section 2.1. Cultures were incubated 24 h at 37°C without anoxic conditions to mimic industrial conditions, in glass bottles in static (without shaking) conditions under air atmosphere (without anaerocult, without nitrogen). Several bottles were inoculated and incubated at the same time. pH was monitored in one of them. Each bottle was sampled once when the targeted pH was reached. Samples of fermented SJ (FSJ) were collected throughout fermentation when the targeted pH values of 7.0 (S1), 6.5 (S2), 6.0 (S3), 5.0 (S4), and 4.5 (S5) were reached, that is, around 1.5, 4, 6, 10, and 13 h post inoculation, respectively. Each time, the cultures were sampled and cooled on ice for bacterial enumerations, RNA extractions, and to be further stored at -20°C in 40 mL straight containers with screw cap (Corning Gosselin) for carbohydrates, carboxylic, and free amino acid quantifications.

## 2.5 | Acidification Kinetics Monitoring

The monitoring of acidification was carried out in duplicate for 13 h using a iCINAC System (Ysebaert, Frepillon, France) and Mettler Toledo ISM probes (Ag/AgCl, E0 = 196 mV at 37°C, Paris, France). Before use, the pH probes were cleaned in pepsin 1% and HCl 10 mM for 1 h, disinfected with 0.1% sodium hypochlorite for 10 min, and then calibrated using reference solutions (pH 4, pH 7, and 220 mV at 37°C, Mettler Toledo, Viroflay, France).

API gallery 50 CH (Biomérieux, Marcy l'Etoile, France) was performed to determine which sugars were assimilable by CIRM-BIA777, according to the manufacturers' instructions.

## 2.6 | Microbial Cell Counts

One milliliter of FSJ was diluted in 9 mL of tryptone salt broth (0.1% Tryptone, AES Laboratoire, Combourg, France; 0.85% NaCl, Labogros, Buchs, France). Serial decimal dilutions were then realized by micromethod as previously described (Baron et al. 2006). CFU were counted on MRS agar after incubation under anaerobic conditions using Anaerocult (ATCO Biocult, Bretteville/Odon, France) for 48 h at 30°C.

## 2.7 | Carbohydrate Quantification

Aliquots (1 g) of FSJ were deproteinized by adding 40 mg of sulfosalicylic acid for 30 min at 0°C, followed by centrifugation for 5 min at 4000 × g, room temperature (RT). Supernatants were then diluted by 150-fold in milli-Q water (Merck, Darmstadt, Germany) and filtered (Chromafil Xtra PVDF 45/13 0.45 µm; Macherey-Nagel, Hoerdt, France). Carbohydrates (stachyose, raffinose), disaccharides (sucrose, maltose), and monosaccharides (glucose, fructose, and galactose) were quantified by high-performance anion-exchange chromatography (HPAEC) and pulsed amperometric detection (PAD) on an ICS-5000+ Dionex system (Fisher Scientific SAS—Illkirch, France) on a Dionex CarboPac PA210-Fast-4 mm column, as previously described (Harlé et al. 2024). Quantifications were performed with external multi-standard calibration.

## 2.8 | Organic Acid Quantification

Lactic, acetic, citric, succinic, pyruvic, and phenyllactic acids were analyzed by high-performance liquid chromatography (HPLC; Dionex, P680, Sunnyvale, CA, USA) as previously described (Harlé et al. 2024).

## 2.9 | Amino Acid Quantification

Free amino acids were analyzed by ion chromatography as previously described (Lorieau et al. 2018). Briefly, after a precipitation of protein using sulfosalicylic acid (10%) for 1 h at 0°C and centrifugation at 1000 × g for 15 min at room temperature, the supernatant was filtered on a 0.45-µm VWR centrifugal nylon membrane filter (VWR International, Radnor, PA, USA), and the flow-through was mixed with lithium citrate (0.2 M, pH 2.2) (1:4 vol/vol) and injected in the cation exchange column of the Biochrom 30 + Automatic Amino Acid Analyzer (Biochrom Ltd., Cambridge, UK) using lithium citrate buffer as eluent with post-column derivatization and ninhydrine as the revealing reagent (Ultra Ninhydrin Reagent Kit, Biochrom). Finally, a photometric detection at 570 nm (440 nm for proline) led to the detection of free amino acids. Amino acids were quantified by comparison with amino acid profiles from external amino acid standard (A9906; Sigma-Aldrich, St. Quentin Fallavier, France).
## 2.10 | Folates and Riboflavin Quantification

Vitamin quantifications were subcontracted to Aqualan laboratory (Bordeaux, France). Riboflavin was quantified by HPLC using the method as described in the French standard NF EN 14152: Food products—Determination of vitamin B2 content by high-performance liquid chromatography—Determination of vitamin B2 by high-performance liquid chromatography. In brief, riboflavin was extracted from foods after acid hydrolysis followed by an enzymatic treatment, separated by HPLC and detected by fluorescence. Folates were quantified in accordance with NF EN 14131: Foodstuffs—Determination of folate by microbiological methods. Briefly, samples were suspended in phosphate buffer and were heated to allow extraction of folates. Protease and alpha-amylase treatments were used to further digest the food matrix. Naturally occurring folylpolyglutamates were hydrolyzed with gamma-glutamyl hydrolase (conjugase) to folyl mono- or folyl di-glutamates. The extracted folates were then diluted with basal medium containing all growth nutrients required for the growth of *Lacticaseibacillus rhamnosus* (ATCC 7469) except folates, as described in detail in NF EN 14131. The growth response of this strain was followed turbidimetrically and was compared with the growth response of the calibration solution with known folate concentrations. This microbiological method allows the entire pool of bioavailable folates to be measured.

## 2.11 | Profile of Volatile Compounds

Volatile compounds were extracted by headspace using a Turbomatrix HS-40 trap (PerkinElmer, Courtaboeuf) as previously described in detail (Pogacic et al. 2015). Volatiles were analyzed by gas chromatography-mass spectrometry (GC-MS; Clarus 680 gas chromatograph, and Clarus 600 T quadrupole mass spectrometer, Perkin Elmer) on a polar column, as previously described (Harlé et al. 2020). They were identified by comparing their retention index and mass spectrum with those reported in the NIST 2008 Mass Spectral Library (Scientific Instrument Services, Ringoes, NJ, USA), and in the literature and, when available, with those of standards (Sigma-Aldrich) analyzed under the same conditions. The limit of detection (LOD), limit of quantification (LOQ), and linearity range were previously determined for varied neutral volatile compounds: LOD ranged between 2 and 8 ng/g, LOQ between 7 and 26 ng/g, and the linearity ranged between 100 and 1000 ng/g (Pogacic et al. 2015). In the present study, volatiles were semi-quantified based on the abundance of a specific *m/z* fragment, with the abundance expressed as arbitrary units. This method was designed to compare the abundance of volatiles across samples and is not intended to compare the concentrations of different volatile compounds.

## 2.12 | RNA Extraction

For the sample of inoculated but unfermented SJ (S1) and samples corresponding to each targeted pH (6.5, 6, 5 and 4.5 corresponding to S2, S3, S4 and S5, respectively) (Figure 1), RNA was extracted from three biological replicates from 1 mL of FSJ treated directly with 2 mL of RNA protect cell reagent (Qiagen, Hilden, Germany). Samples were centrifuged 5 min at 4°C, 10,000 × g to discard the supernatant. The pellet was frozen

at -80°C with 2 mL of RNA protect cell reagent. After a short thaw at room temperature, the samples were centrifuged again for 5 min at 4°C, 10,000 × g, and the supernatant was discarded. Cell pellets were suspended in 200 µL lysis buffer (50 mM Tris-HCl, 1 mM EDTA; pH 8.0) containing 20 mg/mL lysozyme (MP Biomedicals, Illkirch, France) and 50 U/mL mutanolysin (Sigma), and incubated at 24°C for 30 min. Suspensions were then transferred to 2-mL tubes containing 50 mg zirconium beads (diameter: 0.1 mm; BioSpec Products, Bartlesville) and 50 µL SDS (20%) and shaken in a Precellys Evolution bead beater (Bertin, Montigny-le-Brettonneux, France) for two cycles of 40 s at 6500 rpm. RNA was then extracted from the cell lysate using the RNeasy Mini Kit (Qiagen) followed by DNase treatment (Dnase RNase free, Ambion) according to the manufacturer's instructions. For S3 and S4 samples, two additional extractions were performed, but not pooled with previous ones, using phenol-chloroform as no single method was optimal for extracting RNA at these two pH values. In this case, an additional step was performed before the extraction using RNeasy Mini kit: lysates were transferred to Phase Lock Gel Heavy with 900 µL QIAzol (Qiagen) to which 200 µL chloroform was added, for 2 min and centrifuged for 15 min at 12,000 × g.

RNA integrity (RIN) was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). RNA concentrations were quantified using Qubit fluorometric quantification (Thermofisher, France). The absence of contaminating DNA was also checked using Qbit and DNA quantification protocol according to the manufacturer's instructions. RNA samples with a RIN value comprised between 8.3 and 9.5 indicated good RNA integrity. Two unfermented SJ and one CIRM-BIA777 FSJ at pH 6.0 (S3) that did not meet these criteria were excluded from the sequencing.

## 2.13 | RNA Sequencing

The preparation of RNA library and the sequencing reactions were conducted at GENEWIZ, LLC. (Leipzig, Germany). Whole-transcriptome RNA enrichment was performed using NEBNext rRNA Depletion Kit (Bacteria) and NEBNext Ultra II RNA Library Prep Kit for Illumina according to the manufacturer's recommendations (NEB, Ipswich, MA, USA). Briefly, enriched RNAs were fragmented for 15 min at 94°C. First- and second-strand cDNA were then synthesized. cDNA fragments were end-repaired and adenylated at 3'ends, and a universal adapter was ligated to cDNA fragments, followed by index addition and library enrichment by limited cycle polymerase chain reaction (PCR). The sequencing libraries were validated using the Agilent Tapestation 4200 (Agilent Technologies, Palo Alto, CA, USA), and quantified by using Qubit 2.0 fluorometer (Invitrogen, Carlsbad, CA, USA).

The sequencing libraries were multiplexed and clustered on one lane of a flowcell. After clustering, the flowcell was loaded onto the Illumina HiSeq 2500 instrument according to the manufacturer's instructions. The samples were sequenced using a 2x150 paired-end (PE) configuration. Image analysis and base calling were conducted by the HiSeq Control Software on the HiSeq 2500 instrument. Raw sequence data (.bcl files) were generated by Illumina HiSeq 2500 and were converted into fastq files and
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /><figcaption>**FIGURE 1** | (A) Kinetic of fermentation of soy juice by *Lactiplantibacillus plantarum* CIRM-BIA777 (CIRM-BIA777). S numbers correspond to sample names in the text, data.inrae and EBI repositories. Fermentation was followed by: (i) enumeration of the CIRM-BIA777 population level (in dark and in the left axis, CFU/g); (ii) acidification (in orange curve and right axis). (B) Kinetic of acid productions. All results were expressed as a mean of three biological replicates. Differentially expressed genes were identified between S2 and S3 and between S3 and S4, as indicated with green arrows.</figcaption></figure>

de-multiplexed using the Illumina CASSAVA 1.8.2 program. One mismatch was allowed for index sequence identification.

## 2.14 | Mapping RNA Sequences Against the Reference Genome

Sequenced reads were trimmed, adapted using Trim Galore and mapped against reference genome using Bowtie 2 (Langmead et al. 2009). No mismatches were allowed, and only reads that mapped to a unique sequence were further analyzed. Reads mapping to each coding sequence were counted using HTSeq-count (-stranded = reverse, -a 0, -t CDS, -i db_xref, -m union) (Anders et al. 2015).

Due to difficulties in extracting bacterial RNA from fermented SJ (see Section 2 for details), only three steps of the fermentation were analyzed by transcriptomics, while biochemical data were available throughout the kinetics of acidification.

Five FSJ samples (two at pH 6.5 and three at pH 4.5) were discarded from the study because more than 10% of the reads did not map to the reference genome, making RNA-seq analysis at pH 4.5 impossible. The data have been deposited at EBI in ArrayExpress under accession number MTAB-14345.

## 2.15 | RNA-Seq Data Analysis

RNA-seq data were filtered to remove samples with less than 100,000 reads mapping to reference genomes. Differential expression analysis was performed with DESeq2 (Love et al. 2014) using SARTools (Varet et al. 2016) using Rstudio (RStudio Team, 2016, posit.co/downloads/). DESeq2 analysis was performed to compare expression levels with default parameters but with a blocking factor (batch parameter) according to the extraction protocol (with or without phenol-chloroform). Gene transcripts were considered to be differentially expressed (DE) between two consecutive sampling times that were set according to FSJ pH (pH

6 [S3] vs. pH 6.5 [S2] and pH 5 [S4] vs. pH 6 [S3]) with a *p* value corrected for false discovery rate (Benjamini and Hochberg 1995) less than 0.05. Fold changes expressed how many times genes were induced or repressed.

## 2.16 | Statistical Analysis

Mean of the three biological replicates of carbohydrate, organic acid, and amino acid concentrations were compared across stages (S0–S5) using R script deposited in (“IBIS-Dataset 2-Genome-transcriptomics and biochemical data of SJ fermented with *Lactiplantibacillus plantarum* CIRM-BIA777”; https://doi.org/10.57745/88TNI3). The script used the following libraries: multcompView, dplyr, and ggplot2. For volatile compounds, one-way analysis of variance (ANOVA) was performed to determine whether the concentrations of volatile compounds differed according to the stage of culture using the aov R function of the car package (RStudio Inc.). Means of replicates were compared using a Sidak post hoc test (*p* value < 0.05).

Principal component analysis (PCA) was performed by using the FactoMineR and Factoshiny R packages to illustrate the global changes in the profile of volatiles and main other metabolites using the abundance of a specific mass fragment for each compound.

## 2.17 | Repositories for Data Retrieval

Biochemical data and the list of DE genes with their corresponding annotations have been deposited in data.gouv.fr (“IBIS-Dataset 2-Genome-transcriptomics and biochemical data of SJ fermented with *Lactiplantibacillus plantarum* CIRM-BIA777”; https://doi.org/10.57745/88TNI3). Assembly and annotation of the genome sequence can be retrieved at EBI: on Microscope platform: https://image.genoscope.cns.fr/microscope/image/viewer.php?O_id = 12210.
# 3 | Results and Discussion

## 3.1 | Overview of the Study

The aim of the study was to decipher the metabolism of *CIRM-BIA777* during SJ fermentation. *CIRM-BIA777* was selected from 44 *L. plantarum* strains previously screened for their ability to ferment SJ (Harlé et al. 2020). According to this study, *CIRM-BIA777* was able to utilize the main sugars naturally present in SJ, that is, sucrose, stachyose, and raffinose, and rapidly acidify SJ to reach pH 5.4 in less than 10 h. In the present study, soy yogurts inoculated with *CIRM-BIA777* were prepared in triplicate and sampled throughout the kinetics of acidification. Bacterial growth, carbohydrates, amino and carboxylic acids, and volatile compounds were analyzed throughout the fermentation. To decipher the genetic basis of sugar utilization, carboxylic acids releases, and amino acid metabolism, the genome was sequenced and differential expression of genes was quantified at three steps of the fermentation. Carbon metabolism was studied and in particular the utilization of sucrose, glucose, fructose, stachyose, raffinose, and melibiose. Nitrogen metabolism was studied to explain the release of free amino acids in yogurts. Secondary metabolism was also deciphered to identify (i) the expression of pathways involved in the production of metabolites beneficial to human health such as vitamins, GABA, and bile salt hydrolase and (ii) the molecular basis of the production of some aroma compounds potentially involved in the flavor of soy yogurt.

## 3.2 | Overview on CIRM-BIA777 Genomic Data

The genome of *CIRM-BIA777* consists of one circular chromosome of 3.2 megabases and eight circular plasmids ranging from 7.8 to 64.2 kb for a total of 3492 coding DNA sequences (CDS) (Table S1). Genome features are provided in Table S2. EGGNOG-mapper annotation assigned each gene to cluster of orthologous groups (COG) categories.

## 3.3 | Overview on Differential Expression of CIRM-BIA777 Genes Throughout SJ Acidification

The differential expression of each gene was compared between two consecutive points (Figure 1), that is, between S2 (pH 6.58) and S3 (pH 6.03) corresponding to the start of the fermentation, and between S3 (pH 6.03) and S4 (pH 5.11) corresponding to the middle of the fermentation. Transcriptomic results showed that 80 and 859 genes out of 3492 were found to be DE at the beginning and middle of the fermentation, respectively (Table S2). DE genes were found in all COG categories. Table 1 shows the distribution of induced and repressed genes across the COG categories. All induction and repression of genes mentioned are significant (p value adjusted below 0.05) and expressed as fold change. At the beginning of the fermentation (between S2 and S3), the most induced COG categories were “metabolism of nucleotide” (F) and “amino acid” (E). In the middle of the fermentation (between S3 and S4), both categories remained the most induced, followed by “transport of inorganic ions” (P) and “metabolism of carbohydrate” (G), “lipid,” (I), and “coenzyme” (H) (Table 1).

## 3.4 | Growth and Acidification of SJ by Production of Lactic Acid as Main End Product

The SJ used was the same as in Harlé et al. (2024), and its pH was 7.2. After inoculation with *CIRM-BIA777*, the pH decreased from 7.2 to 4.4 within 15 h (Figure 1A), while the *CIRM-BIA777* population increased from 1.15 $10^6$ to 3.70 $10^8$ CFU/mL at the end of the fermentation. The utilization of sugars (see the next paragraph for details) resulted mainly in the production of lactic acid as expected, with a concentration of 4.1 g/L at pH 4.4 (S5). Fermentation also produced small concentrations of acetic, succinic, and phenyllactic acids, which together were also responsible for the pH drop (Figure 1B). Below pH 6 (from S4), the presence of citric (1.5 g/L), acetic (0.3 g/L), succinic (0.1 g/L), and phenyllactic (0.006 g/L) acid was detected.

The genes encoding central carbon catabolism involved in glycolysis, heterolactic fermentation, and the pentose phosphate pathway were expressed at different levels throughout the fermentation and collectively led to pyruvate and subsequently to the release of the various acids mentioned above. In detail, genes encoding enzymes of the glycolysis, that is, *tpiA* for triose phosphate isomerase, *gapA* for glyceraldehyde 3-phosphate dehydrogenase, *pgk* for phosphoglycerate kinase, *eno* for enolase, were stably expressed between pH 6.58 (S2) and pH 6.03 (S3) and later significantly repressed around 1.5-fold between pH 6.03 (S3) and pH 5.11 (S4). The genes encoding the heterolactic pathway, including the specific phosphoketolase (4.1.2.9) enzyme, were stably expressed, with the exception of the genes coding for aldehyde dehydrogenase that convert acetyl CoA to acetaldehyde, which were induced 10.6-fold (LBPLA777_0287) and 5.3-fold (LBPLA777_3162) between pH 6.03 (S3) and pH 5.11 (S4). The gene *tktA* (LBPLA777_0904) encoding the transketolase (2.2.1.1) enzyme involved in the pentose-phosphate pathway was induced sixfold between pH 6.03 (S3) and pH 5.11 (S4). Further details on the fermentation pathways are shown in Figure S1. Produced pyruvate was then converted to L-lactate or/and D-lactate by lactate dehydrogenase, encoded by two stably expressed genes (LBPLA777_0921 and LBPLA777_1765) and the gene LBPLA777_0715, induced 1.8-fold between pH 6.03 (S3) and pH 5.11 (S4) (Table 1). In summary, *CIRM-BIA777* first implemented a homolactic metabolism, with only lactic acid production, *via* glycolysis, followed by a heterolactic metabolism, with additional production of acetic acid and acetaldehyde. The production of lactic, acetic, succinic, and phenyllactic acids contributed to the acidification of SJ and led to its gelation, forming a gel with a yogurt-like texture at a pH around 5, as previously observed (Grygorczyk and Corredig 2013).

## 3.5 | CIRM-BIA777 Mainly Utilized Sucrose, Glucose, Fructose, Melibiose, and Expressed Genes Involved in Stachyose and Raffinose That Are Naturally Present in SJ

The initial total carbohydrate content of SJ was 8 g/L. It included 3.91 g/L of sucrose, 0.19 g/L of fructose, 0.18 g/L of glucose and several GOS: 3.11 g/L of stachyose, 0.68 g/L of raffinose and small amounts of melibiose (0.02 g/L), maltose (0.01 g/L), and galactose (0.001 g/L) (Figure 2). CIRM-BIA777 is able to utilize all these carbohydrates, according to the results of API
<table><caption>TABLE 1 | Number of genes and differentially expressed genes (induced in green or repressed in red) for any functional classes of COG categorization (computed using Eggnog mapper 2) between S3 and S2 (pH 6.0 vs. pH 6.5) and between S4 and S3 (pH 5.0 vs pH 6.0) during SJ fermentation.</caption><thead><tr><th rowspan="2">Functions</th><th colspan="2">COG</th><th colspan="2">Genes</th><th colspan="2">Induced S3 vs. S2</th><th colspan="2">Repressed S3 vs. S2</th><th colspan="2">Induced S4 vs. S3</th><th colspan="2">Repressed S4 vs. S3</th></tr><tr><th>Value</th><th>Value</th><th>Value</th><th>Value</th><th>(induced/genes)</th><th>%</th><th>Value</th><th>(repressed/genes)</th><th>Value</th><th>(induced/genes)</th><th>Value</th><th>(repressed/genes)</th></tr></thead><tbody><tr><td>Non assigned</td><td>—</td><td>291</td><td>5</td><td>2</td><td></td><td></td><td>0</td><td>0</td><td>34</td><td>12</td><td>29</td><td>13</td></tr><tr><td>Defense mechanisms</td><td>V</td><td>58</td><td>1</td><td>2</td><td></td><td></td><td>0</td><td>0</td><td>6</td><td>10</td><td>12</td><td>6</td></tr><tr><td>Intracellular trafficking, secretion, and vesicular transport</td><td>U</td><td>54</td><td>2</td><td>4</td><td></td><td></td><td>0</td><td>0</td><td>7</td><td>13</td><td>11</td><td>5</td></tr><tr><td>Signal transduction mechanisms</td><td>T</td><td>45</td><td>0</td><td>0</td><td></td><td></td><td>1</td><td>2</td><td>4</td><td>9</td><td>4</td><td>2</td></tr><tr><td>Function unknown</td><td>S</td><td>538</td><td>6</td><td>1</td><td></td><td></td><td>3</td><td>1</td><td>57</td><td>11</td><td>49</td><td>15</td></tr><tr><td>Secondary metabolites biosynthesis, transport, and catabolism</td><td>Q</td><td>11</td><td>0</td><td>0</td><td></td><td></td><td>1</td><td>9</td><td>3</td><td>27</td><td>0</td><td>0</td></tr><tr><td>Inorganic ion transport and metabolism</td><td>P</td><td>118</td><td>2</td><td>2</td><td></td><td></td><td>6</td><td>5</td><td>22</td><td>19</td><td>18</td><td>12</td></tr><tr><td>Posttranslational modification, protein turnover, and chaperones</td><td>O</td><td>45</td><td>0</td><td>0</td><td></td><td></td><td>1</td><td>2</td><td>5</td><td>11</td><td>7</td><td>2</td></tr><tr><td>Cell motility</td><td>N</td><td>4</td><td>0</td><td>0</td><td></td><td></td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Cell wall/membrane/envelope biogenesis</td><td>M</td><td>129</td><td>3</td><td>2</td><td></td><td></td><td>3</td><td>2</td><td>15</td><td>12</td><td>14</td><td>5</td></tr><tr><td>Replication, recombination and repair</td><td>L</td><td>191</td><td>0</td><td>0</td><td></td><td></td><td>0</td><td>0</td><td>19</td><td>10</td><td>24</td><td>4</td></tr><tr><td>Transcription</td><td>K</td><td>246</td><td>0</td><td>0</td><td></td><td></td><td>1</td><td>0</td><td>7</td><td>3</td><td>55</td><td>28</td></tr><tr><td>Translation, ribosomal structure, and biogenesis</td><td>J</td><td>165</td><td>0</td><td>0</td><td></td><td></td><td>0</td><td>0</td><td>4</td><td>2</td><td>38</td><td>16</td></tr><tr><td>Lipid transport and metabolism</td><td>I</td><td>50</td><td>3</td><td>6</td><td></td><td></td><td>0</td><td>0</td><td>14</td><td>28</td><td>3</td><td>2</td></tr></tbody></table>

(Continues)
<table><caption>TABLE 1 | (Continued)</caption><thead><tr><th rowspan="2">Functions</th><th rowspan="2">COG</th><th colspan="2">Genes</th><th colspan="2">Induced S3 vs. S2</th><th colspan="2">Repressed S3 vs. S2</th><th colspan="2">Induced S4 vs. S3</th><th colspan="2">Repressed S4 vs. S3</th></tr><tr><th>Value</th><th>Value</th><th>% (induced/genes)</th><th>Value</th><th>% (repressed/genes)</th><th>Value</th><th>% (induced/genes)</th><th>Value</th><th>% (repressed/genes)</th></tr></thead><tbody><tr><td>Coenzyme transport and metabolism</td><td>H</td><td>83</td><td>0</td><td>0</td><td>1</td><td>1</td><td>12</td><td>14</td><td>3</td><td>1</td></tr><tr><td>Carbohydrate transport and metabolism</td><td>G</td><td>130</td><td>2</td><td>2</td><td>0</td><td>0</td><td>17</td><td>13</td><td>16</td><td>6</td></tr><tr><td>Nucleotide transport and metabolism</td><td>F</td><td>119</td><td>9</td><td>8</td><td>0</td><td>0</td><td>33</td><td>28</td><td>13</td><td>7</td></tr><tr><td>Amino acid transport and metabolism</td><td>E</td><td>157</td><td>10</td><td>6</td><td>1</td><td>1</td><td>31</td><td>20</td><td>22</td><td>17</td></tr><tr><td>Cell cycle control, cell division, and chromosome partitioning</td><td>D</td><td>38</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>5</td><td>3</td><td>0</td></tr><tr><td>Energy production and conversion</td><td>C</td><td>104</td><td>1</td><td>1</td><td>0</td><td>0</td><td>12</td><td>12</td><td>5</td><td>1</td></tr></tbody></table>

Note: Only DE genes with *p* value adjusted <0.05 and $log2(FC) \ge 1$ were considered.

gallery 50 CH. Accordingly, all the genes encoding transporters and enzymes of the corresponding degradation pathways were identified on CIRM-BIA777 chromosome (Table S2). An additional alpha-galactosidase gene was also found on plasmid 4 (LBPLA777_pd0008).

The use of these different carbohydrates by CIRM-BIA777 during fermentation was revealed both by carbohydrate quantification throughout the kinetics of acidification (Figure 2) and transcriptional analysis (Table S2).

Sucrose was the main sugar catabolized during SJ fermentation. Sucrose concentration decreased progressively but was not completely depleted at the end of the fermentation (Figure 2A). Genes encoding sucrose degradation were constantly transcribed throughout the kinetics. The sucrose operon contains LBPLA777_0164_crSA, which encodes a PTS transporter responsible for the internalization of sucrose in its phosphorylated form; LBPLA777_0165_crSB encoding a sucrose hydrolase, which cleaves the phosphorylated sucrose into a phosphorylated glucose and a fructose moiety; and LBPLA777_0162_crSK encoding a fructokinase, which phosphorylates the fructose moiety. A second fructokinase gene, LBPLA777_2824_crSK, located outside the operon may contribute to fructose phosphorylation. Sucrose metabolism by CIRM-BIA777 was in line with that previously described for L. plantarum LP-F1 strain (Cui et al. 2021) and close to that expressed by L. delbrueckii subsp. delbrueckii CIRM-BIA865 in SJ (Harlé et al. 2024). Phosphorylated glucose and fructose were further degraded via glycolysis, the pentose phosphate pathway, and heterolactic fermentation as described above.

Glucose and fructose were detected at concentrations <1 g/L in SJ and raised transiently at the middle of the fermentation at pH 6.03 (S3) (Figure 2B,C), suggesting that sucrose may be also extracellularly hydrolyzed or secreted in addition to the intracellular hydrolysis described above. However, no sucrose hydrolase was predicted to be surface-exposed according to the annotation step (Psort results available on Microscope platform). Genes of the glycolysis were activated throughout the fermentation period. The *ccpA* gene, which encodes a global regulatory protein involved in carbon catabolic repression, was stably expressed. This supports the hypothesis of a different glycolytic regulation from that described in the L. plantarum WCFS1 strain in DML laboratory medium containing glucose (Rud et al. 2011). In contrast, the central glycolytic gene regulator (*cggR*) was repressed between S3 and S4. Regulation involving *ccpA* was also suggested for GOS degradation below.

Galactose was detected in trace amounts in SJ (Figure 2D). However, the galTEK operon encoding a component of the Leloir pathway that ensures the internalization and degradation of galactose was stably transcribed between S2 and S3 and induced four to eightfold between S3 and S4.

Galacto-oligosaccharides, also named as GOS, are not digestible by humans due to the lack of alpha-1,6-galactosidase enzyme in the intestinal tract. They are present in some cereals and legumes and are abundant in SJ (3.8 g/L in the present study). Among them, raffinose, stachyose, and verbascose consist of one, two, and three alpha-(1,6)-D-galactose units linked to sucrose,
<figure><img src="image_4.png" /><figcaption>**FIGURE 2** | (A–H) Boxplots represent the changes in the concentrations in the carbohydrates during soy juice fermentation by *Lactiplantibacillus plantarum* CIRM-BIA777 (*CIRM-BIA777*). Values are means of independent triplicate experiments, expressed in g/L. The barplot represents the cumulative concentration of each carbohydrate at each sampling time.</figcaption></figure>

respectively. They can be fermented by the colonic microbiota mainly by species belonging to the genera *Clostridium* and *Bacteroidetes*, producing gas and potentially causing abdominal pain. This concern has led to the search for technological solutions to reduce the GOS of SJ. Some LAB strains are able to degrade GOS and to convert them into digestible carbohydrates (Teixeira et al. 2013). GOS hydrolysis can be ensured by alpha-1,6-galactosidase enzyme, which releases galactose units and by the levansucrase enzyme which cleaves sucrose and releases glucose units (Gänzel and Follador 2012).

In the present study, raffinose and stachyose concentrations increased transiently at the beginning of SJ fermentation, before pH 6 was reached, and decreased further between stages S3 and S4 to reach their initial levels in un-fermented SJ (Figure 2E,F). This could be due to the hydrolysis of verbascose, which was not analyzed in the present study. GOS hydrolysis in SJ is in line with the results of SJ fermentation by *Limosilactobacillus fermentum* (LeBlanc et al. 2004), which showed an optimal activity of alpha-galactosidase at pH 5.5, and with those of Bhatia et al. (2020), who showed its possible activity between pH 5.5 and pH 8. In our study, the degradation

did not proceed below pH 5. Since the three corresponding genes, LBPLA777_0163_agaS and LBPLA777_3049_agaR on the chromosome and LBPLA777_pd0008_agaR on plasmid 4, were stably expressed in our study, we hypothesize that either the pH or the low concentration of inhibitory monosaccharides could favor GOS degradation only between pH6 and pH5. Alpha-galactosidase activity has been scarcely identified in LAB (Canon et al. 2020; Silvestroni et al. 2002). *Latilactobacillus curvatus* and *Leuconostoc mesenteroides* have been shown to be able to successfully reduce GOS content in SJ (Yoon and Hwang 2008). Optimal alpha-galactosidase activities were observed at temperatures between 35 and 45°C and from pH 5.5 to pH 8.0 in LAB (Bhatia et al. 2020; Garro et al. 1996; LeBlanc et al. 2004; Yoon and Hwang 2008). Alpha-galactosidase activity can also be inhibited by the simultaneous presence of GOS and sucrose or glucose or fructose (Bau et al. 2015; Carevic et al. 2016; Garro et al. 1996; Yoon and Hwang 2008) or Cu²⁺, Zn²⁺, and Fe²⁺ (Bhatia et al. 2020; Han et al. 2014). *CIRM-BIA777* has previously been shown to be able to grow at 30°C on stachyose and raffinose (Harlé et al. 2020), when these carbohydrates were provided as the sole carbon source. In the present study, the presence of residual sucrose, the preferred sugar of *CIRM-BIA777*, may also account for the absence of
GOS degradation. This mechanism is known as carbon catabolite repression and is a conserved bacterial mechanism that optimizes nutrient use. In low-GC Gram-positive bacteria, carbon catabolite repression is mediated by CcpA, a key regulator that binds to phosphorylated HPr in the presence of glucose or sucrose. This CcpA-(HPr-Ser-P) complex then binds to the consensus sequence named "*cre* sites" on DNA, thus modulating gene expression. Transcriptomic analysis of *L. plantarum* ST-III and its corresponding *ccpA* knockout strain showed that genes encoding PTS transporters involved in FOS and cellobiose internalization were induced in the mutant strain compared to the wild-type strain in a medium containing glucose or FOS (Lu et al. 2018). This experiment revealed the role of CcpA in inhibiting the internalization of both of these oligosaccharides. In order to decipher the cause(s) of the low alpha-galactosidase activity observed in the present study, different controlled conditions of culture could be used, with and without mono- and disaccharides and divalent ions at different concentrations, with or without pH control. A *ccpA* mutant strain of CIRM-BIA777 could be tentatively obtained and used to ferment SJ to check if the GOS degradation could be enhanced in the absence of carbon catabolite repression.

The low amount of melibiose initially present was degraded early (from stage S0 to S2, Figure 2G) and then the concentration of melibiose increased again to reach the initial concentration. The initial degradation is probably provided by both invertase and alpha-galactosidase (induced as described in the sucrose and GOS sections above). The increase in melibiose concentration could be due to stachyose or raffinose degradation. The lack of melibiose internalization during the culture at 37°C and its accumulation in soy yogurt is in agreement with that previously described in *L. plantarum* ATCC 8014 at 30°C (Tamura and Matsushita 1992).

The maltose concentration decreased slightly at the end of the fermentation, below pH 5 (Figure 2H) between S3 and S4. However, the PTS maltose (LBPLA777_3085 and LBPLA777_3086) and maltose phosphorylase (LBPLA777_0154_mdxK) genes were constantly transcribed. The oligo-1,4-1,6-alpha-glucosidase gene (maltase, LBPLA777_0171_mdxL) was stably expressed between S2 and S3 and further repressed twofold between S3 and S4 when maltose was almost depleted (<0.01 g/L).

In summary, *CIRM-BIA777* expressed genes potentially involved in the degradation of mono-, di-, and oligo-saccharides present in SJ. While *CIRM-BIA777* mainly utilized sucrose in our experimental conditions (75% depletion), all the genes corresponding to glucose, fructose, galactose, maltose, and GOS degradation pathways were transcribed at least during one stage of the fermentation. Except for GOS degradation, which is a rare ability among *L. plantarum* strains (Mao et al. 2021), other SJ carbohydrates can be degraded by most of *L. plantarum* strains, suggesting that this species can be very useful for soy fermentation purposes. The gene expression regulations should be thoroughly deciphered using mixtures of these different carbohydrates and systematic gene knock-out experiments before a comprehensive model of carbohydrate degradation by this strain can be drawn up. The diversity of *CIRM-BIA777* carbon catabolism could also be tentatively exploited to ferment different juices, fruits, or flours

containing less sucrose than SJ, as demonstrated with tomatoes and olives (Yu et al. 2021).

## 3.6 | Amino Acid Transport and Metabolism

Soy beans are classified into proteinaceous seeds. The SJ used in this study is rich in protein (35 g/L according to the nutritional information present on the package), peptides, and free amino acids (Figure 3). *CIRM-BIA777* reached a maximum cell number of 3.70 10⁸ CFU/mL in 13 h without the addition of any nitrogen source, showing that the organic nitrogen content of SJ was sufficient to ensure the growth of the strain. We did not identify any cell wall protease in the *CIRM-BIA777* genome and the total number of amino acids remained unchanged (data not shown), suggesting that this strain is not capable of hydrolyzing native soy proteins.

Figure 3 (panels A–J) illustrates the evolution patterns of free amino acid concentrations in the extracellular medium along the fermentation kinetics for the 10 amino acids that showed significantly different concentrations over time. Serine, threonine, tryptophan, glycine, and methionine were utilized throughout the fermentation (Figure 3, panel I, subsections A–E). Arginine, histidine, and lysine were initially utilized by S3 and then probably coming from peptidase activity (Figure 3, panel II, subsections F–H), while proline and GABA were synthetized and/or released and accumulated in the soy yogurt (Figure 3, panel III, subsections I and J).

Transcriptomic results suggest that the demand for nitrogen compounds could be met by both amino acid and peptide ABC transporters, which were induced throughout the fermentation. Genes encoding peptide transporter were identified on the chromosome (LBPLA777_0177) or the plasmid (LBPLA777Pe0040) and were induced two- and fivefold between S2 and S3 and between S3 and S4, respectively. Regarding the transport of amino acids into the cytoplasm, the 7.4-fold induction of the serine transport gene (LBPLA777_2910SerP) was observed from stage S2 to S3. The proline permease gene (LBPLA777_2559) was induced 3.7-fold between S2 and S3 and 4.6-fold between S3 and S4. The transport of methionine involved the induction of nine genes encoding ABC transporter proteins, which were 3- to 19-fold overexpressed. At least 12 different peptidases with different specificities were induced with fold changes between 1.3 and 7, including eight peptidases with Log2(fold change)>1. The genes encoding arginine synthesis were progressively induced up to 10-fold along the fermentation time, while arginine was progressively released from S4 until the end of the fermentation (Figure 3F). This capacity of arginine synthesis is known to be (i) rare among Lactobacillus-related species which are known to be highly auxotrophic, (ii) strain-dependent among L. plantarum strains, and (iii) mostly associated with non-dairy strains (Bringel and Hubert 2003). Histidine and lysine were released in SJ (Figure 3G,H) during fermentation from stage S3, but the corresponding pathways were stably expressed, suggesting that they probably resulted from peptidolysis rather than from de novo synthesis. This release of lysine was also reported during the fermentation of oat flake beverage by *L. plantarum* strain LP09 (Luana et al. 2014).
<figure><img src="image_5.png" /><figcaption>**FIGURE 3** | Changes in the amino acid concentrations during soy juice fermentation by *Lactiplantibacillus plantarum* CIRM-BIA777 (CIRM-BIA777). Boxplots were grouped (I, II, and III) according to the evolution patterns of concentrations along the kinetic of fermentation. Group I includes serine (A), threonine (B), tryptophane (C), glycine (D), and methionine ('E'). Group II includes arginine (F), histidine (G), and lysine (H). Group III includes proline (I) and GABA (J). Values are means of independent triplicates, expressed in mg/L.</figcaption></figure>

## 3.7 | CIRM-BIA777 Could Biofortify Soy Yogurt (B2, B9, and GABA)

Riboflavin (vitamin B2) is one of the water-soluble B vitamins and is essential for cellular energy metabolism. Riboflavin is also involved in FADH synthesis and respiration. *Lactiplantibacillus plantarum* has been shown to significantly increase riboflavin levels in SJ (up to 700 µg/L), making it a potential source of this essential vitamin (Bhushan et al. 2020; Juarez Del Valle et al. 2014). Riboflavin synthesis is encoded on the *ribDEBAH* locus (LBPLA777_1221-1224). In our study, several genes of the riboflavin synthesis pathway were induced during fermentation between stages S3 and S4. The *ribD* and *ribBA* genes, which encode enzymes involved in the first steps of the riboflavin synthesis pathway, were induced 5.5 and 6-fold, respectively. The last steps of the riboflavin synthesis, encoded by *ribE* and *ribH*, were stably expressed. Quantification of riboflavin, performed at stages S0 and S5, showed the same concentration, that is, 0.2 mg/L. This result suggests that riboflavin, if synthesized, could remain in the cytoplasm. If riboflavin could be released during digestion after consumption of fermented SJ, soy yogurt could play a role in fortification. Auxotrophy for riboflavin is strain-dependent among *L. plantarum* (Siezen et al. 2011) and only 6% of *L. plantarum* strains can produce riboflavin (Bhushan et al. 2020). In contrast to CIRM-BIA777, the type strain WCFS1 lacks *ribD* and *ribE*, thus probably leading to its auxotrophy. To conclude, the absence of production and/or release of riboflavin by *L. plantarum* strains could result either from the absence of key biosynthetic genes (like for WCFS1), or from post transcriptional

regulation, or from the lack of a specific transporter ensuring the its release outside the cell. In the latter case, strains with a lytic behavior may present an advantage to release riboflavin in food

The ability to produce folates vary between bacterial species. *Lactiplantibacillus plantarum* was described as capable of producing folates during soy fermentation (Greppi et al. 2017; C.-J. Liu et al. 2019). This ability is known to be strain-specific among *L. plantarum* species (Crittenden et al. 2003). This potential contributes to the enrichment of folates in soy-based products (Kariluoto et al. 2014). The genome of CIRM-BIA777 contains eight out of nine genes responsible for tetrahydrofolate biosynthesis (Supplementary table, Table S2-DE-genes.tab in data.inrae, by selecting of "ko00790" in the "KEGG_Pathway" field). The gene corresponding to aminodeoxychorismate lyase (4.1.3.38) was not found in the genome. In addition to tetrahydrofolate biosynthesis, folate transformation pathways I and III were reconstructed from Metacyc database. These pathways were induced between stages S3 and S4. They convert tetrahydrofolate to 5-methyl tetrahydrofolate and 5,10-methylene tetrahydrofolate. In our study, although these pathways were induced up to 15-fold (homocysteine S-methyltransferase/5,10-methylenetetrahydrofolate reductase, LBPLA777_1170_yit), the concentration of total folates was stable, around 158 µg/L, from S0 to S5 stage. Since folate is required for methionine synthesis from homoserine, a pathway that was significantly overexpressed, we hypothesized that folate may be used intracellularly and not released into the medium.
GABA is a neurotransmitter with a positive impact on cognitive health, and its synthesis has already been observed in *L. plantarum* in a strain-dependent manner (Shekh et al. 2016). GABA is not present in proteins and its synthesis results from the decarboxylation of glutamic acid. During SJ fermentation, a transient but significant release of GABA (4.5 mg/L) was observed from stage S4 (Figure 3J). Consistent with this, the LBPLA777_2985_gadB gene encoding a glutamate decarboxylase was induced 1.8-fold also between S3 and S4 stages.

It has been shown that certain strains of *L. plantarum* (ECGC13110402 and HT121) have cholesterol-lowering properties in rats and humans (Keleszade et al. 2022; M. Liu et al. 2012). Consumption of *L. plantarum* HT121 strain for 7 weeks was shown to be associated with lower triacylglycerols and higher glycocholic acid in hypercholesterolemic rats. A twofold increase in the expression of a conjugated bile acid hydrolase gene (LBPLA777_3104, cbh) was observed in SJ fermented by CIRM-BIA777, suggesting potential bile salt hydrolytic activity. Given that HT121, a *L. plantarum* strain known to reduce triacylglycerols and induce hepatic Cyp7a1 expression in hypercholesterolemic rats, also harbors similar activity. It is possible that SJ fermented by CIRM-BIA777 could hypothetically contribute to cholesterol metabolism, though in vivo validation is needed, because of high content in unsaturated lipids and the potential activity of the CIRM-BIA777 bile acid hydrolase.

## 3.8 | Production of Aroma Compounds During SJ Fermentation by CIRM-BIA777

A total of 34 volatile compounds were identified in fermented SJ: 10 acids, eight carbonyl compounds, six alcohols (butan-1-ol, propan-1-ol, pentan-1-ol, hexan-1-ol, 2-methylpropan-1-ol, phenylmethanol, 1-phenylethanol), five aldehydes (3-methylbutanal, pentanal, hexanal, benzaldehyde, hepten-2-alk), one ester (ethyl acetate), and four other compounds (Table S3). Eight of these, including three aldehydes (3-methylbutanal, hexanal, and benzaldehyde), are considered to be potentially involved in the “green and/or beany” off-flavor of legume proteins (Fischer et al. 2022). During fermentation, the volatile profile changed. Concentration of six compounds significantly decreased, including three aldehydes, while concentration of 22 compounds increased (Table S3). The largest fold-changes, that is, the ratio of the final to initial concentration, were observed for a number of compounds with diverse odors: 1-hydroxybutan-2-one (also called acetoin), 2,3-butanedione (diacetyl), and 1-hydroxypropan-2-one, all associated with a buttery odor; acetic acid, associated with a sour and vinegary odor; some other fatty acids (i.e., pentanoic and hexanoic acids, associated with sweaty odors); and some alcohols (hexan-1-ol, phenylmethanol and 1-phenylethanol), associated with fruity and/or floral odors (Table S3 and Figure 4). Recent studies (Fang et al. 2024) showed that a soy yogurt prepared from soymilk by adding inulin and inoculating lactic acid bacteria mixture and *L. plantarum* had the optimal overall acceptance with lower beany flavor and higher yogurt aroma.

A PCA was performed by using the abundance of the 34 volatiles, plus five acids quantified by HPLC (lactic, acetic, citric, succinic, and phenyllactic acids) to illustrate the main changes. It showed

that the first axis, which accounted for 56.2% of the total variance, separated the samples according to the stage of fermentation (Figure 4). The first axis was positively correlated with most of the compounds that increased in abundance over time, and negatively correlated with a few compounds that decreased in abundance, including three aldehydes (3-methylbutanal, pentanal, and hexanal).

The pathways leading from pyruvate to diacetyl and acetoin have been very well described in *L. lactis* (García-Quintans et al. 1998; García-Quintáns et al. 2008) and more recently in *L. plantarum* (Lecomte et al. 2024). They implicate acetolactate synthase and acetolactate decarboxylase, which convert pyruvate to acetolactate, and acetolactate to acetoin, respectively (Figure S1 and Figure 5). The genes LBPLA777_0844_als and LBPLA777_1738 encoding these two enzymes were stably expressed throughout fermentation. Since the concentration of acetoin increased 69-fold and 33-fold between stages S2 and S3 and stages S3 and S4, respectively, its increase could be attributed to a higher availability of precursors. Between pH 6 and 5, acetylCoA can be converted to acetaldehyde and then to ethanol (Figure S1 and Figure 5) thanks to the 10- and 5-fold induction of the acetyl dehydrogenase genes Lbpla777-0287 and Lbpla777-3162_adhE, respectively. Some LAB can also convert dihydroxyacetone phosphate to methylglyoxal. Methylglyoxal, an unstable compound, is further partially or completely reduced to acetol and 1,2-propanediol, respectively (Gandhi et al. 2018). *Lactiplantibacillus plantarum* was shown to produce higher amounts of acetol in a cheese-based media supplemented with methylglyoxal, compared to the other lactobacilli-related strains tested (Gandhi et al. 2018).

Ethanol can be produced by heterofermentative LAB that possess the enzyme alcohol dehydrogenase, which converts acetaldehyde to ethanol (Figure S1 and Figure 5). *Lactiplantibacillus plantarum* synthesizes alcohol from carbohydrates via the phosphoketolase pathway. The concentration of hexan-1-ol increased dramatically between pH 6.5 and 6 (12.3-fold). In okara (soybean pulp containing less sugar and less protein than SJ) fermented by either *Lactobacillus acidophilus*, *L. rhamnosus*, or *Pediococcus acidilactici*, the concentration of hexan-1-ol was 206.7, 217, and 217.5 µg/g, respectively, compared to 64.2 µg/g in the unfermented okara (Rajendran et al. 2023). In the present study, the concentration of hexan-1-ol at the end of fermentation was 12 times higher than in unfermented SJ. This compound is often found in fermented foods (K. Zhang, Zhang, Guo, et al. 2023). For example, it was produced in kiwifruit juice fermented by several LAB strains including *L. plantarum* (Wang et al. 2022). This concentration is low, but the metabolite is known for its deleterious effect on health. In the present study, the concentration of phenylethanol, which is associated with a floral aroma, increased ~10-fold between stage S2 and S3 (Figure 4). Phenylethanol production has been reported in Chinese wolfberry juice (a non-leguminous fruit) fermented by *L. plantarum*, which produced 246.4 mg/L, whereas phenylethanol was not produced by the other four LAB strains tested (Qi et al. 2021). This production in SJ probably results from phenylalanine catabolism, which has been extensively studied in cheese (Yvon and Rijnen 2001).

The reduction of some volatiles associated with beany and/or green off-flavors, such as several aldehydes, and, conversely, the production of some volatile compounds associated with different
<figure><img src="image_6.png" /><figcaption>**FIGURE 4** | Principal component analysis performed for the data of volatile abundance and organic acid concentration (in black and blue, respectively, on the graph of variables) at five stages (S0, S2, S3, S4, and S5, see Figure 1) during soy juice fermentation by *Lactiplantibacillus plantarum* CIRM-BIA777. Individuals are colored according to the stage of culture. Only the best represented variables are shown (cos² > 0.3).</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**FIGURE 5** | Schematic overview of *CIRM-BIA777* functioning in soy juice. The degradation of sucrose, glucose, fructose, and galactose from soy juice was deduced from their concentration decrease in yogurt during fermentation and confirmed by transcriptomic analysis. Utilization of stachyose, raffinose, melibiose, maltose, and cellobiose was suspected according to transcriptomic analysis but was not confirmed by biochemical analysis. All of the pathways encoding the biosynthesis of aroma compounds, carboxylic acids, arginine, histidine, lysine, proline, GABA, and bile salt hydrolase were annotated in the genome, induced during the fermentation. All these metabolites were quantified in the yogurt, except for bile salt hydrolase. Biosynthetic pathways of riboflavin and methionine—involving folate and homoserine—were induced during fermentation, but their concentration in yogurt were not increased suggesting an intracellular utilization. Consumption of phenylalanine and production of phenylethanol were quantified by chromatography. Green ellipse for PTS transporter, orange ellipse for ABC transporter, dotted ellipse for presumptive transporters those corresponding genes were not identified in the genome, yellow ellipse for aroma compounds released in extracellular medium. The text in blue corresponds to sugars which are known to be degraded in a strain-dependent manner according to literature.</figcaption></figure>
flavors, for example, buttery flavor for acetoin and diacetyl, floral flavor for phenylmethanol and phenylethanol, and cheesy flavor for short-chain fatty acids, probably contribute to the improvement of SJ flavor, as reported in a recent paper (Ritter et al. 2024) citing the same effects of *L. plantarum* strain L879 on lupin. However, this should be further confirmed by sensory analysis.

4 | Conclusion and Future Prospects

In summary, CIRM-BIA777 in SJ fermentation induced genes corresponding to the catabolic pathways of sucrose, fructose, glucose, and biosynthetic pathways of riboflavin and folates (Figure 5). The corresponding genes were highly expressed during the fermentation of SJ. The presence of genes encoding alpha-galactosidase and the complete pathway for arginine synthesis is known to be rare among *L. plantarum* strains (Table S4). The CIRM-BIA777 strain, harboring these genes, appears to be particularly adapted to the fermentation of SJ. In addition, CIRM-BIA777 fermentation reduced the concentration of some aldehydes known to be associated with beany off-flavor, and also led to the release of pleasant aroma compounds such as diacetyl and phenylethanol (Figure S1 and Figure 5).

The use of CIRM-BIA777 enables to obtain the benefits of (i) gelation; (ii) phenylethanol, diacetyl, acetoin, GABA, bile salt hydrolase production; and (iii) the limitation of deleterious organoleptic quality (beany notes). We advise to carry out the fermentation within less than 7 h to limit acetic acid production. To ensure a good preservation of the soy yogurt, an additional homolactic acid species could be added to reach the typical yogurt pH of 4.5.

The stachyose and raffinose content remained unchanged at the end of fermentation. Factors preventing the utilization of stachyose and raffinose deserve much more attention. pH-regulated fermentations in bioreactors could help to explain the lack of GOS degradation under the conditions of this study. The ability of the strain to degrade GOS in the presence of different monosaccharides at different concentrations could also help to identify the regulatory mechanism that ensures the sequential utilization of carbohydrates.

To the best of our knowledge, this study is the first study to tentatively explain the molecular mechanisms involved in aroma formation, and GOS degradation regulation during *L. plantarum* fermentation in organic soy yogurt, using transcriptomic data. This knowledge opens up new avenues to help with the development of plant-based fermented foods in general, and legume-based yogurt in particular.

Author Contributions

**Olivier Harlé**: formal analysis, methodology, writing – review and editing. **Jérôme Niay**: conceptualization, methodology, supervision, funding acquisition. **Sandrine Parayre**: data collection and curation, methodology, validation. **Gwenäèle Henry**: data collection and curation, methodology. **Marie-Bernadette Maillard**: data collection and curation, methodology. **Anne Thierry**: data curation, methodology,

supervision, writing – review and editing. **Éric Guédon**: supervision, validation, writing – review and editing. **Stéphanie-Marie Deutsch**: conceptualization, data collection, curation and brokering, funding acquisition, project administration, supervision. **Hélène Falentin**: conceptualization, funding acquisition, project administration, supervision, data collection, curation and brokering, writing – original draft, writing – review and editing.

Acknowledgments

We are grateful to (i) the Genotoul bioinformatics platform Toulouse Occitanie (Bioinfo Genotoul, https://doi.org/10.15454/1.5572369328961167E12) for providing help and computational and storage resources and (ii) the LABGeM bioinformatics team that developed MicroScope web interface and in particular to David Vallenet for his help in visualizing transcriptomic data on pathways. We greatly appreciate the tutorials by Peter Karp and Ron Caspi and the availability of the Standalone PathwayTools software which allowed us to reconstruct and visualize transcriptomic data of CIRM-BIA777 genome. We are grateful to Anne-Sophie Bage and Daniel Jacob for advices on depositing data and metadata on data.inrae and to Aurélie Nicolas for assistance in depositing the annotated genome of CIRM-BIA777. This study was funded by "Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement" INRAE (France), Agence Natinale de Recherche Technologique ANRT (France), and the Olga-Triballat company.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are openly available in https://entrepot.recherche.data.gouv.fr at https://doi.org/10.57745/88TNI3.

References

Anders, S., P. T. Pyl, and W. Huber. 2015. "HTSeq—A Python Framework to Work With High-Throughput Sequencing Data." *Bioinformatics* 31, no. 2: 166–169. https://doi.org/10.1093/bioinformatics/btu638.

Azi, F., C. Tu, L. Meng, et al. 2021. "Metabolite Dynamics and Phytochemistry of a Soy Whey-Based Beverage Bio-Transformed by Water Kefir Consortium." *Food Chemistry* 342: 128225. https://doi.org/10.1016/j.foodchem.2020.128225.

Baron, F., M. F. Cochet, W. Ablain, et al. 2006. "Rapid and Cost-Effective Method for Microorganism Enumeration Based on Miniaturization of the Conventional Plate-Counting Technique." *Le Lait* 86, no. 3: 251–257. https://doi.org/10.1051/lait:2006005.

Bau, T. R., S. Garcia, and E. I. Ida. 2015. "Changes in Soymilk During Fermentation With Kefir Culture: Oligosaccharides Hydrolysis and Isoflavone Aglycone Production." *International Journal of Food Sciences and Nutrition* 66, no. 8: 845–850. https://doi.org/10.3109/09637486.2015.1095861.

Benjamini, Y., and Y. Hochberg. 1995. "Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing." *Journal of the Royal Statistical Society Series B-Methodological* 57, no. 1: 289–300.

Bhatia, S., A. Singh, N. Batra, and J. Singh. 2020. "Microbial Production and Biotechnological Applications of α-Galactosidase." *International Journal of Biological Macromolecules* 150: 1294–1313. https://doi.org/10.1016/j.ijbiomac.2019.10.140.

Bhushan, B., C. R. Kumkum, M. Kumari, J. J. Ahire, L. M. T. Dicks, and V. Mishra. 2020. "Soymilk Bio-Enrichment by Indigenously Isolated Riboflavin-Producing Strains of *Lactobacillus plantarum*." *LWT* 119: 108871. https://doi.org/10.1016/j.lwt.2019.108871.

Boulay, M., M. Al Haddad, and F. Rul. 2020. "*Streptococcus thermophilus* Growth in Soya Milk: Sucrose Consumption, Nitrogen Metabolism, Soya
Protein Hydrolysis and Role of the Cell-Wall Protease PrtS." *International Journal of Food Microbiology* 335: 108903. https://doi.org/10.1016/j.ijfoodmicro.2020.108903.

Bringel, F., and J.-C. Hubert. 2003. "Extent of Genetic Lesions of the Arginine and Pyrimidine Biosynthetic Pathways in *Lactobacillus plantarum*, *L. paraplantarum*, *L. pentosus*, and *L. casei*: Prevalence of CO₂-Dependent Auxotrophs and Characterization of Deficient Arg Genes in *L. plantarum*." *Applied and Environmental Microbiology* 69, no. 5: 2674-2683. https://doi.org/10.1128/AEM.69.5.2674-2683.2 003.

Canon, F., M. Mariadassou, M.-B. Maillard, et al. 2020. "Function-Driven Design of Lactic Acid Bacteria Co-Cultures to Produce New Fermented Food Associating Milk and Lupin." *Frontiers in Microbiology* 11: 584163. https://doi.org/10.3389/fmicb.2020.584163.

Cantalapiedra, C. P., A. Hernández-Plaza, I. Letunic, P. Bork, and J. Huerta-Cepas. 2021. "eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale." *Molecular Biology and Evolution* 38, no. 12: 5825-5829. https://doi. org/10.1093/molbev/msab293.

Carevic, M., K. Banjanac, M. Ćorović, et al. 2016. "Selection of Lactic Acid Bacteria Strain for Simultaneous Production of α- and β-Galactosidases." *Zastita Materijala* 57, no. 2: 265-273. https://doi.org/10. 5937/ZasMat1602265c.

Caspi, R., R. Billington, C. A. Fulcher, et al. 2018. "The MetaCyc Database of Metabolic Pathways and Enzymes." *Nucleic Acids Research* 46, no. D1: D633--D639. https://doi.org/10.1093/nar/gkx935.

Chen, C., G. Zhao, W. Chen, and B. Guo. 2015. "Metabolism of Fructooligosaccharides in *Lactobacillus plantarum* ST-III via Differential Gene Transcription and Alteration of Cell Membrane Fluidity." *Applied and Environmental Microbiology* 81, no. 22: 7697-7707. https://doi.org/10.1128/ AEM.02426-15.

Crittenden, R. G., N. R. Martinez, and M. J. Playne. 2003. "Synthesis and Utilisation of Folate by Yoghurt Starter Cultures and Probiotic Bacteria." *International Journal of Food Microbiology* 80, no. 3: 217-222. https://doi. org/10.1016/S0168-1605(02)00170-8.

Cui, Y., M. Wang, Y. Zheng, K. Miao, and X. Qu. 2021. "The Carbohydrate Metabolism of *Lactiplantibacillus plantarum*." *International Journal of Molecular Sciences* 22, no. 24: 13452. https://doi.org/10.3390/ ijms222413452.

Evanovich, E., P. J. De Souza Mendonça Mattos, and J. F. Guerreiro. 2019. "Comparative Genomic Analysis of *Lactobacillus plantarum*: An Overview." *International Journal of Genomics* 2019: 1-11. https://doi.org/ 10.1155/2019/4973214.

Falentin, H., S.-M. Deutsch, V. Loux, et al. 2016. "Permanent Draft Genome Sequence of the Probiotic Strain *Propionibacterium freudenreichii* CIRM-BIA 129 (ITG P20)." *Standards in Genomic Sciences* 11, no. 1: 6. https://doi.org/10.1186/s40793-015-0120-z.

Fang, X., H. Ye, M. Chen, et al. 2024. "Effects of Co-Fermentation of Lactobacillus Plantarum and Inulin on Beany Flavor and Physicochemical Quality of soy Yogurt in a Multiple Lactic Acid Bacteria Fermentation System." *Cereal Chemistry*, 101, no. 1: 248-262. https://doi.org/10.1002/ cche.10741.

Fischer, E., N. Cayot, and R. Cachon. 2022. "Potential of Microorganisms to Decrease the "Beany" Off-Flavor: A Review." *Journal of Agricultural and Food Chemistry* 70, no. 15: 4493-4508. https://doi.org/10.1021/acs.jafc. 1c07505.

Gänzle, M. G., and R. Follador. 2012. "Metabolism of Oligosaccharides and Starch in Lactobacilli: A Review." *Frontiers in Microbiology* 3: 340. https://doi.org/10.3389/fmicb.2012.00340.

Gandhi, N. N., P. F. Cobra, J. L. Steele, J. L. Markley, and S. A. Rankin. 2018. "*Lactobacillus* Demonstrate Thiol-Independent Metabolism of Methylglyoxal: Implications Toward Browning Prevention in Parmesan Cheese." *Journal of Dairy Science* 101, no. 2: 968-978. https://doi.org/10.3168/jds. 2017-13577.

García-Quintáns, N., G. Repizo, M. Martín, C. Magni, and P. López. 2008. "Activation of the Diacetyl/Acetoin Pathway in *Lactococcus lactis* subsp. *lactis* Bv. Diacetylactis CRL264 by Acidic Growth." *Applied and Environmental Microbiology* 74, no. 7: 1988--1996. https://doi.org/10.1128/ AEM.01851-07.

García-Quintans, N., C. Magni, D. de Mendoza, and P. López. 1998. "The Citrate Transport System of *Lactococcus lactis* subsp. *lactis* Biovar Diacetylactis Is Induced by Acid Stress." *Applied and Environmental Microbiology* 64, no. 3: 850--857. https://doi.org/10.1128/AEM.64.3.850-857. 1998.

Garro, M. S., G. F. De Valdez, G. Oliver, and G. S. De Giori. 1996. "Purification of α-Galactosidase From *Lactobacillus fermentum*." *Journal of Biotechnology* 45, no. 2: 103--109. https://doi.org/10.1016/0168-1656(95) 00149-2.

Gautreau, G., A. Bazin, M. Gachet, et al. 2020. "PPanGGOLiN: Depicting Microbial Diversity via a Partitioned Pangenome Graph." *PLOS Computational Biology* 16, no. 3: e1007732. https://doi.org/10.1371/journal.pcbi. 1007732.

Greppi, A., F. Saubade, C. Botta, C. Humblot, J.-P. Guyot, and L. Cocolin. 2017. "Potential Probiotic *Pichia kudriavzevii* Strains and Their Ability to Enhance Folate Content of Traditional Cereal-Based African Fermented Food." *Food Microbiology* 62: 169--177. https://doi.org/10.1016/j.fm.2016. 09.016.

Grygorczyk, A., and M. Corredig. 2013. "Acid Induced Gelation of Soymilk, Comparison Between Gels Prepared With Lactic Acid Bacteria and Glucono-δ-Lactone." *Food Chemistry* 141, no. 3: 1716-1721. https://doi. org/10.1016/j.foodchem.2013.03.096.

Guillon, F., and M. M.-J Champ. 2002. "Carbohydrate Fractions of Legumes: Uses in Human Nutrition and Potential for Health." *British Journal of Nutrition* 88, no. S3: 293-306. https://doi.org/10.1079/ BJN2002720.

Han, Y. R., S. Y. Youn, G. E. Ji, and M. S. Park. 2014. "Production of Alpha- and Beta-Galactosidases From *Bifidobacterium longum* subsp. *longum* RD47." *Journal of Microbiology and Biotechnology* 24, no. 5: 675-682. https://doi.org/10.4014/jmb.1402.02037.

Harlé, O., H. Falentin, J. Niay, et al. 2020. "Diversity of the Metabolic Profiles of a Broad Range of Lactic Acid Bacteria in Soy Juice Fermentation." *Food Microbiology* 89: 103410. https://doi.org/10.1016/j.fm.2019.103410.

Harlé, O., J. Niay, S. Parayre, et al. 2024. "Deciphering the Metabolism of *Lactobacillus delbrueckii* subsp. *delbrueckii* During Soy Juice Fermentation Using Phenotypic and Transcriptional Analysis." *Applied and Environmental Microbiology* 90: e0193623. https://doi.org/10.1128/aem. 01936-23.

Hernández-Alcántara, A. M., S. Pardo, M. L. Mohedano, et al. 2020. "The Ability of Riboflavin-Overproducing *Lactiplantibacillus plantarum* Strains to Survive Under Gastrointestinal Conditions." *Frontiers in Microbiology* 11: 591945. https://doi.org/10.3389/fmicb.2020.591945.

Juarez Del Valle, M., J. E. Laiño, G. Savoy De Giori, and J. G. LeBlanc. 2014. "Riboflavin Producing Lactic Acid Bacteria as a Biotechnological Strategy to Obtain Bio-Enriched Soymilk." *Food Research International* 62: 1015-1019. https://doi.org/10.1016/j.foodres.2014.05.029.

Kanehisa, M., Y. Sato, M. Furumichi, K. Morishima, and M. Tanabe. 2019. "New Approach for Understanding Genome Variations in KEGG." *Nucleic Acids Research* 47, no. D1: D590--D595. https://doi.org/10.1093/ nar/gky962.

Kariluoto, S., M. Edelmann, L. Nyström, et al. 2014. "In Situ Enrichment of Folate by Microorganisms in Beta-Glucan Rich Oat and Barley Matrices." *International Journal of Food Microbiology* 176: 38--48. https:// doi.org/10.1016/j.ijfoodmicro.2014.01.018.

Keleszade, E., S. Kolida, and A. Costabile. 2022. "The Cholesterol Lowering Efficacy of *Lactobacillus plantarum* ECGC 13110402 in Hypercholesterolemic Adults: A Double-Blind, Randomized, Placebo Controlled, Pilot Human Intervention Study." *Journal of Functional Foods* 89: 104939. https://doi.org/10.1016/j.jff.2022.104939.
Langmead, B., C. Trapnell, M. Pop, and S. L. Salzberg. 2009. "Ultrafast and Memory-Efficient Alignment of Short DNA Sequences to the Human Genome." *Genome Biology* 10, no. 3: R25. https://doi.org/10.1186/gb-2009-10-3-r25.

LeBlanc, J. G., M. S. Garro, and G. Savoy de Giori. 2004. "Effect of pH on *Lactobacillus fermentum* Growth, Raffinose Removal, α-Galactosidase Activity and Fermentation Products." *Applied Microbiology and Biotechnology* 65, no. 1: 119-123. https://doi.org/10.1007/s00253-003-1532-z.

Lecomte, M., W. Cao, J. Aubert, et al. 2024. "Revealing the Dynamics and Mechanisms of Bacterial Interactions in Cheese Production With Metabolic Modelling." *Metabolic Engineering* 83: 24-38. https://doi.org/10.1016/j.ymben.2024.02.014.

Liu, C.-J., B. Wu, S.-Y. Zhang, et al. 2019. "Transcriptomic Analysis of *de Novo* Folate Biosynthetic Genes in *Lactobacillus plantarum* Strain 4_3 in Fermented Soybean." *Food & Function* 10, no. 5: 2426-2438. https://doi.org/10.1039/C8FO01952E.

Liu, M., C. Prakash, A. Nauta, R. J. Siezen, and C. Francke. 2012. "Computational Analysis of Cysteine and Methionine Metabolism and Its Regulation in Dairy Starter and Related Bacteria." *Journal of Bacteriology* 194, no. 13: 3522-3533. https://doi.org/10.1128/JB.06816-11.

Lorieau, L., L. Le Roux, F. Gaucheron, et al. 2018. "Bioaccessibility of Four Calcium Sources in Different Whey-Based Dairy Matrices Assessed by in Vitro Digestion." *Food Chemistry* 245: 454-462. https://doi.org/10.1016/j.foodchem.2017.10.108.

Love, M. I., W. Huber, and S. Anders. 2014. "Moderated Estimation of Fold Change and Dispersion for RNA-Seq Data With DESeq2." *Genome Biology* 15, no. 12: 550. https://doi.org/10.1186/s13059-014-0550-8.

Lu, Y., S. Song, H. Tian, H. Yu, J. Zhao, and C. Chen. 2018. "Functional Analysis of the Role of CcpA in *Lactobacillus plantarum* Grown on Fructooligosaccharides or Glucose: A Transcriptomic Perspective." *Microbial Cell Factories* 17, no. 1: 201. https://doi.org/10.1186/s12934-018-1050-4.

Luana, N., C. Rossana, J. A. Curiel, P. Kaisa, G. Marco, and C. G. Rizzello. 2014. "Manufacture and Characterization of a Yogurt-Like Beverage Made With Oat Flakes Fermented by Selected Lactic Acid Bacteria." *International Journal of Food Microbiology* 185: 17-26. https://doi.org/10.1016/j.ijfoodmicro.2014.05.004.

Luo, Y.-Y., Y. Guo, X.-Y. Hu, et al. 2023. "Flavor Improvement of Fermented Soybean Foods by Co-Fermentation With *Bacillus velezensis* and *Lactiplantibacillus plantarum*." *LWT* 186: 115257. https://doi.org/10.1016/j.lwt.2023.115257.

de Man, J.-C., M. Rogosa, and E. Sharpe. 1960. "A Medium for the Cultivation of Lactobacilli." *Journal of Applied Bacteriology* 23: 130-135.

Mao, B., R. Yin, X. Li, et al. 2021. "Comparative Genomic Analysis of *Lactiplantibacillus plantarum* Isolated From Different Niches." *Genes* 12, no. 2: 241. https://doi.org/10.3390/genes12020241.

Pogacic, T., M.-B. Maillard, A. Leclerc, et al. 2015. "A Methodological Approach to Screen Diverse Cheese-Related Bacteria for Their Ability to Produce Aroma Compounds." *Food Microbiology* 46: 145-153. https://doi.org/10.1016/j.fm.2014.07.018.

Qi, J., H. Huang, J. Wang, et al. 2021. "Insights Into the Improvement of Bioactive Phytochemicals, Antioxidant Activities and Flavor Profiles in Chinese Wolfberry Juice by Select Lactic Acid Bacteria." *Food Bioscience* 43: 101264. https://doi.org/10.1016/j.fbio.2021.101264.

Rajendran, S., P. Silcock, and P. Bremer. 2023. "Flavour Volatiles of Fermented Vegetable and Fruit Substrates: A Review." *Molecules*, 28, no. 7: 3236. https://doi.org/10.3390/molecules28073236.

Ritter, S., C. Luber, M. Gastl, and T. Becker. 2024. "Identification of Promising Lactic Acid Bacteria for the Fermentation of Lupine- and Faba Bean-Based Substrates to Produce Refreshing Protein-Rich Beverages—A Strain Screening." *Food Frontiers* 5: 2094-2121. https://doi.org/10.1002/fft2.452.

Rud, I., K. Naterstad, R. S. Bongers, D. Molenaar, M. Kleerebezem, and L. Axelsson. 2011. "Functional Analysis of the Role of CggR (Central Glycolytic Gene Regulator) in *Lactobacillus plantarum* by Transcriptome Analysis." *Microbial Biotechnology* 4, no. 3: 345-356. https://doi.org/10.1111/j.1751-7915.2010.00223.x.

Shekh, S. L., J. M. Dave, and B. R. M. Vyas. 2016. "Characterization of *Lactobacillus plantarum* Strains for Functionality, Safety and γ-Amino Butyric Acid Production." *LWT* 74: 234-241. https://doi.org/10.1016/j.lwt.2016.07.052.

Siezen, R. J., J. R. Bayjanov, G. E. Felis, et al. 2011. "Genome-Scale Diversity and Niche Adaptation Analysis of *Lactococcus lactis* by Comparative Genome Hybridization Using Multi-Strain Arrays: Genome-Scale Diversity and Niche Adaptation Analysis of *Lactococcus Lactis*." *Microbial Biotechnology* 4, no. 3: 383-402. https://doi.org/10.1111/j.1751-7915.2011.00247.x.

Silvestroni, A., C. Connes, F. Sesma, G. S. de Giori, and J.-C. Piard. 2002. "Characterization of the *melA* Locus for α-Galactosidase in *Lactobacillus plantarum*." *Applied and Environmental Microbiology* 68, no. 11: 5464-5471. https://doi.org/10.1128/AEM.68.11.5464-5471.2002.

Tamura, C., and O. Matsushita. 1992. "Melibiose Transport System in *Lactobacillus plantarum*." *Microbiology and Immunology* 36, no. 11: 1119-1128. https://doi.org/10.1111/j.1348-0421.1992.tb02116.x.

Teixeira, J. S., R. Abdi, M. S.-W. Su, C. Schwab, and M. G. Gänzle. 2013. "Functional Characterization of Sucrose Phosphorylase and *scrR*, a Regulator of Sucrose Metabolism in *Lactobacillus reuteri*." *Food Microbiology* 36, no. 2: 432-439. https://doi.org/10.1016/j.fm.2013.07.011.

Vallenet, D., A. Calteau, M. Dubois, et al. 2019. "MicroScope: An Integrated Platform for the Annotation and Exploration of Microbial Gene Functions Through Genomic, Pangenomic and Metabolic Comparative Analysis." *Nucleic Acids Research* 48: D579-D589. https://doi.org/10.1093/nar/gkz296.

Varet, H., L. Brillet-Guéguen, J.-Y. Coppée, and M.-A. Dillies. 2016. "SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data." *PLoS ONE* 11, no. 6: e0157022. https://doi.org/10.1371/journal.pone.0157022.

Wang, Z., Y. Feng, N. Yang, T. Jiang, H. Xu, and H. Lei. 2022. "Fermentation of Kiwifruit Juice From Two Cultivars by Probiotic Bacteria: Bioactive Phenolics, Antioxidant Activities and Flavor Volatiles." *Food Chemistry*, 373: 131455. https://doi.org/10.1016/j.foodchem.2021.131455.

Wick, R. R., L. M. Judd, C. L. Gorrie, and K. E. Holt. 2017. "Unicycler: Resolving Bacterial Genome Assemblies From Short and Long Sequencing Reads." *PLoS Computational Biology* 13, no. 6: e1005595. https://doi.org/10.1371/journal.pcbi.1005595.

Yoon, M., and H. Hwang. 2008. "Reduction of Soybean Oligosaccharides and Properties of α-D-galactosidase From *Lactobacillus curvatus* R08 and *Leuconostoc mesenteroides* JK55." *Food Microbiology* 25, no. 6: 815-823. https://doi.org/10.1016/j.fm.2008.04.008.

Yu, A. O., E. A. Goldman, J. T. Brooks, et al. 2021. "Strain Diversity of Plant-Associated *Lactiplantibacillus plantarum*." *Microbial Biotechnology* 14, no. 5: 1990-2008. https://doi.org/10.1111/1751-7915.13871.

Yvon, M., and N. Rijnen. 2001. "Cheese Flavour Formation by Amino Acid Catabolism." *International Dairy Journal* 11: 185-201.

Zhang, K., T.-T. Zhang, R.-R. Guo, Q. Ye, H.-L. Zhao, and X.-H. Huang. 2023. "The Regulation of Key Flavor of Traditional Fermented Food by Microbial Metabolism: A Review." *Food Chemistry: X* 19: 100871. https://doi.org/10.1016/j.fochx.2023.100871.

Zhang, X., C. Zhang, L. Xiao, et al. 2023. "Effects of *Lactiplantibacillus plantarum* With Different Phenotypic Features on the Nutrition, Flavor, Gel Properties, and Digestion of Fermented Soymilk." *Food Bioscience* 55: 103026. https://doi.org/10.1016/j.fbio.2023.103026.

Zheng, J., S. Wittouck, E. Salvetti, et al. 2020. "A Taxonomic Note on the Genus *Lactobacillus*: Description of 23 Novel Genera, Emended Description of the Genus *Lactobacillus beijerinck* 1901, and Union of Lactobacillaceae and Leuconostocaceae." *International Journal of Systematic
and Evolutionary Microbiology 70, no. 4: 2782--2858. https://doi.org/10.1099/ijsem.0.004107.

**Supporting Information**

Additional supporting information can be found online in the Supporting Information section.

**Supplementary Table S1:** Characteristics of *Lactiplantibacillus plantarum* CIRM-BIA777 genome features. **Supplementary Table S3:** Volatile compounds identified in soy juice fermented by *Lactiplantibacillus plantarum* CIRM-BIA777 at 37°C

**Supplementary Table S2:** see on data.gouv repository see 7-DE-genes.tab **Supplementary Table S4:** Pangenomes features (core and specific genome) of *L. plantarum* species including *CIRM-BIA777* genome. **Supplementary Figure S1:** Induction and repression of different fermentation pathways between pH6 (S3) and pH5 (S4) expressed in log2 fold change according to Pathway Tool and Metacyc pathways.