Sophie Verstraeten

Séverine Layec

Sandrine Auger

Catherine Juste

Céline Henry

Sawiya Charif

Yan Jaszczyszyn

Harry Sokol

Laurent Beney

Philippe Langella

Muriel Thomas

Eugénie Huillet
email: eugenie.huillet@inrae.fr

C Robert

R Mayeur

J M Martin

Chatel

Faecalibacterium duncaniae A2-165 regulates the expression of butyrate synthesis, ferrous iron uptake, and stress-response genes based on acetate consumption

Bacteria in the genus Faecalibacterium (phylum Bacillota 1 , class Clostridia, family Oscillospiraceae) are commensal, strictly anaerobic bacteria, that are ubiquitous and abundant in the gastrointestinal tracts of humans and animals [START_REF] Duncan | Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb[END_REF][START_REF] Miquel | Faecalibacterium prausnitzii and human intestinal health[END_REF] . This genus is currently recognized as one of the most important commensals for human health [START_REF] Lopez-Siles | Faecalibacterium prausnitzii: From microbiology to diagnostics and prognostics[END_REF][START_REF] Martin | Searching for the bacterial effector: The example of the multi-skilled commensal bacterium Faecalibacterium prausnitzii[END_REF] . According to the latest phylogenetic analysis [START_REF] Sakamoto | Genome-based, phenotypic and chemotaxonomic classification of Faecalibacterium strains: Proposal of three novel species Faecalibacterium duncaniae sp. nov., Faecalibacterium hattorii sp. nov. and Faecalibacterium gallinarum sp. nov[END_REF] , the genus Faecalibacterium is composed of six species, of which prausnitzii is the best known for its effects on human health. The most extensively studied strain of F. prausnitzii, A2-165, has been recently reclassified and placed into a new species, duncaniae sp. nov. [START_REF] Sakamoto | Genome-based, phenotypic and chemotaxonomic classification of Faecalibacterium strains: Proposal of three novel species Faecalibacterium duncaniae sp. nov., Faecalibacterium hattorii sp. nov. and Faecalibacterium gallinarum sp. nov[END_REF] . Interest in Faecalibacterium has increased over the last decade, mostly in response to the pioneering study of Sokol et al. reporting a depletion of F. duncaniae A2-165 in Crohn's disease patients [START_REF] Sokol | Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients[END_REF] . Since this report, many studies have confirmed reduced abundances of Faecalibacterium in patients with inflammatory bowel disease and metabolic diseases [START_REF] Sokol | Low counts of Faecalibacterium prausnitzii in colitis microbiota[END_REF][START_REF] Tilg | Microbiota and diabetes: An evolving relationship[END_REF] , which has led to consider members of this genus into candidates for the development of diagnostic, prognostic, preventive or therapeutic approaches [START_REF] Langella | Editorial: Next-generation probiotics: From commensal bacteria to novel drugs and food supplements[END_REF] .

In the healthy human colon, Faecalibacterium are among the main bacteria responsible for the consumption of acetate and the production of butyrate. Butyrate is the preferred energy source for colonocytes and has anti-inflammatory properties that are generally considered to be beneficial to intestinal health [START_REF] Pryde | The microbiology of butyrate formation in the human colon[END_REF][START_REF] Louis | Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine[END_REF] . Recently, we demonstrated that dact3, an host gene linked to the Wnt/JNK pathway, mediates these F. prausnitzii antiinflammatory effects [START_REF] Lenoir | Butyrate mediates anti-inflammatory effects of Faecalibacterium prausnitzii in intestinal epithelial cells through Dact3[END_REF] . In addition, several peptides originating from a single 15-kDa protein (Microbial Antiinflammatory Molecule, MAM) have been identified in the supernatant of F. duncaniae A2-165 cultures [START_REF] Quevrain | The presence of the anti-inflammatory protein MAM, from Faecalibacterium prausnitzii, in the intestinal ecosystem[END_REF][START_REF] Quevrain | Identification of an anti-inflammatory protein from Faecalibacterium prausnitzii, a commensal bacterium deficient in Crohn's disease[END_REF][START_REF] Auger | Intraspecific diversity of microbial anti-inflammatory molecule (MAM) from Faecalibacterium prausnitzii[END_REF] , and these have been shown to alleviate chemically induced colitis in mice [START_REF] Martin | The commensal bacterium Faecalibacterium prausnitzii is protective in DNBS-induced chronic moderate and severe colitis models[END_REF][START_REF] Martin | Faecalibacterium prausnitzii prevents physiological damages in a chronic low-grade inflammation murine model[END_REF] . The key enzyme for butyrate production is butyryl-CoA:acetate CoA-transferase. It generates butyrate and acetyl-CoA from extracellular acetate and intracellular butyryl-CoA 2, [START_REF] Duncan | Contribution of acetate to butyrate formation by human faecal bacteria[END_REF][START_REF] Charrier | A novel class of CoA-transferase involved in short-chain fatty acid metabolism in butyrate-producing human colonic bacteria[END_REF][START_REF] D'hoe | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community[END_REF] . In addition to generating butyrate, this process also promotes growth, thus explaining the growth-stimulating effects of culture supplementation with a high amount of acetate (33-50 mM) [START_REF] Duncan | Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb[END_REF][START_REF] D'hoe | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community[END_REF][START_REF] Lopez-Siles | Cultured representatives of two major phylogroups of human colonic Faecalibacterium prausnitzii can utilize pectin, uronic acids, and host-derived substrates for growth[END_REF] . In co-culture models, acetate cross-feeding between Faecalibacterium and acetate-producing bacteria such as Bifidobacteria adolescentis [START_REF] Rios-Covian | Enhanced butyrate formation by crossfeeding between Faecalibacterium prausnitzii and Bifidobacterium adolescentis[END_REF] or Blautia hydrogenotrophica [START_REF] D'hoe | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community[END_REF] has been observed to enhance butyrate formation. A positive correlation between acetate consumption and butyrate production was also established in vivo between F. duncaniae A2-165 and Bacteroides thetaiotaomicron [START_REF] Wrzosek | Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii influence the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent[END_REF] .

In the human gut, acetate is the most abundant short-chain fatty acid largely generated by the bacterial fermentation of dietary fibers. Its concentration fluctuates depending on various parameters, including gut transit time, diet, age, health status, and microbiota composition [START_REF] Macfarlane | Regulation of short-chain fatty acid production[END_REF][START_REF] Miquel | Ecology and metabolism of the beneficial intestinal commensal bacterium Faecalibacterium prausnitzii[END_REF][START_REF] Martin | Functional characterization of novel Faecalibacterium prausnitzii strains isolated from healthy volunteers: A step forward in the use of F. prausnitzii as a next-generation probiotic[END_REF] . To cope with such changes, Faecalibacterium have presumably developed regulatory systems that sense and respond to acetate levels. These adaptive strategies would necessarily involve a well-coordinated gene expression network that takes into account both the physiological state of the bacteria (latency, exponential, stationary phases) and the environmental conditions (availability of acetate and other nutrients, physicochemical signals such as oxygen tension, pH, temperature). Although several recent studies have investigated the transcriptome of F. duncaniae [START_REF] D'hoe | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community[END_REF][START_REF] Lebas | Metabolic response of Faecalibacterium prausnitzii to cell-free supernatants from lactic acid bacteria[END_REF][START_REF] Kang | Functional dissection of the phosphotransferase system provides insight into the prevalence of Faecalibacterium prausnitzii in the host intestinal environment[END_REF] , none has examined the effects of acetate across growth phases. In light of its proposed vital role in intestinal health, this information is critical for understanding the metabolism of Faecalibacterium and how this might affect human health.

Here, we investigated the effect of acetate on temporal changes in the transcriptome of F. duncaniae A2-165 cultures using RNA sequencing. Next, we characterized the regulation of two feoB genes-which encode wellknown ferrous iron transporter-in response to the availability of acetate and ferrous sulfate. Finally, using an novel integrated approach, we searched for and identified FeoB peptides specific to the A2-165 strain in the healthy human fecal metaproteome. The general workflow of our study can be found as Supplementary Fig. S5 online.

Results

Experimental design for acetate-dependent transcriptome analysis

Acetate consumption is the main driver of butyrate production by genus Faecalibacterium, as shown in Fig. 1A. To gain insight into the effect of acetate on the transcriptome of F. duncaniae A2-165, two sets of cultures were established in media that contained low (3 mM) or high (23 mM) concentrations of acetate (see "Methods" section). The resulting growth kinetics are shown in Fig. 1B. In both acetate conditions, there was no difference in growth kinetics over the first 7 h, and the stationary growth phase was reached after 9 h of culture in both treatments. In the early stationary phase, the biomass in high-acetate conditions (Sa) was about 1.5-fold higher than in low-acetate conditions (S) (2.30 ± 0.13 OD 600 vs. 1.50 ± 0.18 OD 600 , N = 4, p < 0.05). Moreover, the growth rate was 1.25-fold higher in high-acetate conditions (Fig. 1C), suggesting that the general metabolism of F. duncaniae A2-165 was highly active in these cultures. Indeed, the generation time was reduced by about 25 min in this group compared to that of low-acetate cultures (1.67 h vs. 2.08 h). In high-and low-acetate conditions, we quantified butyrate production and acetate consumption in both the late exponential growth phase (Ea and E, respectively) and the early stationary growth phase (Sa and S, respectively) (Fig. 1D). In both acetate conditions, butyrate production was significantly higher in the early stationary phase than in the late exponential phase. Moreover, in the late exponential phase (7 h of growth) there was no difference between acetate conditions in either butyrate production or acetate consumption. In contrast, in the early stationary phase (10 h of growth), butyrate production and acetate consumption were significantly different between acetate conditions (butyrate: 11.94 mM ± 0.89 for Sa, 6.37 mM ± 1.07 for S, p < 0.01). Moreover, after 10 h of growth, almost all acetate had been consumed in the low-acetate cultures (-2.16 mM ± 0.38), whereas only one-third of the acetate had been consumed in the high-acetate cultures (-7.66 mM ± 0.58). The acetate limitation experienced in the low-acetate conditions strongly affected the growth of F. duncaniae A2-165 (Fig. 1B,C). We thus investigated the acetategrowth effect at the transcriptional level in both acetate-limited and acetate-saturated conditions using RNA-Seq. For this, gene expression profiles were analyzed at both E/Ea and S/Sa time points (Fig. 1B).

Overview of transcriptomes in low-and high-acetate conditions

The RNA-Seq datasets contained a total of 2882 genes out of the 3013 predicted in the RefSeq database (i.e., over 95%). Of these, 1159 genes were found to be differentially expressed (DE) (log 2 fold change (FC) ≥ |2| and FDR-adjusted p-value ≤ 0.01) between conditions. All DE genes are presented in Supplementary Tables S1-S4 online. Eight of these genes were differentially expressed in early exponential cultures, compared to 541 in the late stationary phase (339 and 202 transcripts up-and down-regulated, respectively, Fig. 1E), which is consistent with the different patterns of growth kinetics. This result clearly demonstrates that, under our experimental conditions, acetate concentration (3 vs. 23 mM) had little impact on transcriptomic profiles in F. duncaniae A2-165 for the first 7 h of growth (i.e., up to the late exponential growth phase), but had a significant impact when the cultures entered the stationary phase of growth. This prompted us to perform a detailed analysis of the adaptive changes that occur in the transcriptome in response to acetate availability between 7 and 10 h of growth. As shown in Fig. 1E, there was a large difference in the adaptive response between high-acetate (Sa/Ea, 118 DE genes) and low-acetate (S/E, 492 DE genes) conditions in this three-hour period. Specifically, we found that, under high-acetate conditions, only 67 and 51 genes were up-and downregulated, respectively, whereas under low-acetate conditions, 216 and 276 genes were up-and downregulated, respectively. When comparing the DE transcript lists in low-and high-acetate conditions (see Supplementary Fig. S6 online), it clearly appeared that the acetate-limiting condition triggered a larger adaptive transcriptional response at the onset of the stationary growth phase compared to the acetate-saturated conditions, in our growth model.

Using the COG and PATRIC databases, we classified DE genes into 12 functional categories (see Supplementary Table S5 online). As shown in Fig. 2A, for all transcriptomes (high-acetate, low-acetate, and early The number of (differentially expressed) DE genes for each comparison is presented in the form of a bar chart. Two-group comparisons were conducted between high-and low-acetate conditions in the late exponential phase (Ea vs. E) and early stationary phase (Sa vs. S). Additionally, two-group comparisons were performed between the early stationary and late exponential phases in high-acetate (Sa vs. Ea) and low-acetate (S vs. E) conditions. log 2 FC ≥ |2|, FDR-adjusted p-value ≤ 0.01. stationary), the largest category (27.2-58.8% of genes) was the superclass "Poorly characterized protein-genes", which included the categories "Hypothetical proteins" and "General function prediction". It is likely that these unknown DE genes contribute to the adaptive responses of F. duncaniae A2-165 as cells enter the stationary phase. In addition, clear differences between low-and high-acetate transcriptomes were observed with respect to the categories "Protein synthesis", "Energy metabolism", "Import system", "Defense system", "Stress response", and "Transcription and Post-transcriptional regulation" (Fig. 2A). Interestingly, in acetate-limiting conditions (S vs. E), the highest proportions of up-and downregulated genes were related to "Stress response" (9.3%, i.e., 20 DE genes) and "Protein synthesis" (27.9%, i.e., 77 DE genes) respectively, whereas in acetate-saturated conditions (Sa vs. Ea), the highest proportions of affected genes were related to "Import system" (13.4%, i.e., 9 upregulated genes, and 23.5%, i.e., 12 downregulated genes).

Overall, our transcriptome analysis strongly suggests that F. duncaniae A2-165 is able to tightly regulate the expression of metabolic and stress-response genes according to acetate levels when cells enter the stationary phase, in our growth conditions. Remarkably, in all comparative transcriptional analyses, the CG447_03795 gene encoding the MAM protein did not appear among the DE genes; the transcription of this gene was quite high and unchanged between acetate conditions as well as between the growth phases examined here (see Supplementary Fig. S7 online).

We analyzed in detail the categories with the highest gene count belonging to the TOP 3, in low-and highacetate transcriptomes (see Table S5 in Supplementary Information). These categories include 'Protein synthesis' and 'Stress response' in low acetate transcriptomes, while they encompass 'Import system' in high acetate transcriptomes. Differentially expressed transcriptional regulators may yield clues as to how the adaptive response is regulated. We concentrated on the 'Transcription and Post-transcriptional Regulation' category in low acetate growth conditions to associate putative transcriptional regulators with potential target genes.

A general stress response under acetate-limiting conditions

As depicted in Fig. 2B, we clearly observed significant differences in the transcriptional responses of F. duncaniae A2-165 under acetate-limiting condition compared with acetate-saturated condition. Interestingly, in low-acetate condition, we found a high number of downregulated transcripts in the "Protein synthesis" category (77 DE genes, log 2 FC range: 2-5, Table S3) that were not detected in high-acetate condition. These were mainly transcripts involved in translation machinery, such as translation initiation/elongation factors and aminoacyl-tRNA synthetases/transferases, but also included genes involved in ribosome biogenesis and/or stability. These findings likely indicated a major slowdown of translational processes under low-acetate growth conditions as F. duncaniae cells entered the stationary phase.

We also noted a drastic shift in the "Stress response" category (20 DE genes, Table S3) which again was not observed in high-acetate condition. Seven of these genes (log 2 FC range: 2.2-2.9) encoded chaperone proteins involved in protein remodeling, in the repair of proteins following stress damage, or even in the ubiquitin machinery and proteasome. The remaining 13 (log 2 FC range: 2.1-6.2) genes were associated with type II toxin/ antitoxin (TA) systems [START_REF] Harms | Toxins, targets, and triggers: An overview of toxin-antitoxin biology[END_REF] . More specifically, we observed the upregulation of four putative operons for RelE TA systems, one putative operon for a TA module in the Doc family, two genes encoding antitoxin proteins, and one gene encoding a toxin protein. Of these, the DinJ/YafQ system (CG447_14090/14095) was the most activated TA system (log 2 FC: 6.1-6.2). Overall, our data suggest that cells of F. duncaniae A2-165 in low-acetate condition experienced severe general stress upon entry to the early stationary growth phase.

Bacteria employ different transcriptional regulators and sigma transcription factors to respond to changing environments. In the low-acetate transcriptome examined here, we found a higher number of upregulated genes encoding transcriptional regulators and sigma transcription factors (18 DE genes, log 2 FC range: 2.1-5.5, see Supplementary Table S3 online) compared to high-acetate condition (4 DE genes, log 2 FC range: 3.0-5.0, see Supplementary Table S4 online). Moreover, in all bacteria studied thus far, the global regulator that mediates the general stress response is a specialized sigma factor [START_REF] Gottesman | Trouble is coming: Signaling pathways that regulate general stress responses in bacteria[END_REF] . In the low-acetate transcriptome, we specifically found five upregulated genes encoding sigma factors (CG447_02225/05485/06440/06875/08160, see Supplementary Table S3 online), while in high-acetate conditions there was only one, which was also upregulated in low-acetate conditions (CG447_02215, Tables S4-S5). It is thus possible that these five sigma factors could be involved in the general stress response described above when cells enter the stationary phase.

Deciphering import systems under high-and low-acetate conditions

Transcription of transporter genes is usually regulated in response to substrate availability [START_REF] Saier | A functional-phylogenetic system for the classification of transport proteins[END_REF] . As shown in Fig. 2B, we clearly observed two distinct import system transcriptomes of F. duncaniae A2-165, under acetate-limiting and saturated conditions. These findings likely indicated two major adaptation responses to substrate availability, according to acetate conditions. A large number of genes (46) belonging to the "Import system" category were found to be downregulated under low-acetate conditions (see Supplementary Table S3 online); this number was four-fold higher than under high-acetate conditions (see Supplementary Table S4 online). These were mainly transporter genes in the ABC superfamily (25 DE genes), in the sodium-dependent transporter family (5 DE genes), in the ECF subfamily (3 DE genes) and in the FeoB family (4 DE genes) (Supplementary Table S3 online, Fig. 2B). Within the ECF group, we noticed a reduction in gene expression related to B vitamins uptake (bioY gene, CG447_11745, involved in biotin import, log 2 FC -4.14; ribU gene, CG447_14300, log 2 FC -3.92, involved in riboflavine import). We noticed a considerable reduction in gene expression related to ferrous iron uptake (feoA 1 A 2 BC putative operon, CG447_12740-55, log 2 FC range: -4.9 to 5.9), and ferric iron uptake (fhu putative operon, CG447_03300-10, log 2 FC range: -6.1 to 8.0). This suggested that the expression of major systems of iron transport was severely impaired in low-acetate conditions. Conversely, we found that expression of the feoA 1 A 2 BC operon was upregulated under high-acetate condition (log 2 FC: 1.5-2.1, Fig. 2B). This was particularly marked in S5 in Supplementary file 2 and the total number of DE genes is shown below each pie-chart. The right part of the panel shows the representative color for each category. The category "Other biological processes" contained the metabolism subcategories "Amino acid", "Amino sugar", "Nucleotide", "Vitamin and Cofactor", "Lipid", and "Cell wall", as well as "Bacterial cell division processes". The "Energy metabolism" category corresponds to the conversion of carbon sources and acetate to ATP and the carbon skeleton and includes glycolysis and the butyrate pathway. See Tables S2-S4 in Supplementary file 2 for data on DE genes (gene ID, COG number, protein annotation, log 2 FC, padj value, category). Bold characters indicate category selection in this study. (B) Description of relevant functional categories and import system subclassification in high, low and early stationary acetate transcriptomes. ABC (ATP-binding cassette) transport family. Others: other transport system family, FeoB (Ferrous) iron transport system family. PTS: phosphoenol pyruvate transferase system family, ECF (Energy Coupling Factor) transport family. Arrows indicate "Import system" category selection and FeoB transport system selection in this study.

early stationary transcriptome, in which we observed an even higher fold-change in expression (log 2 FC: 4.5-5.9, Sa vs. S, Supplementary Table S2 online, Fig. 2B). Many studies have explored the role of the FeoB high affinity transporters in ferrous iron uptake in iron-poor environments [START_REF] Sestok | Toward a mechanistic understanding of Feo-mediated ferrous iron uptake[END_REF][START_REF] Lau | Bacterial ferrous iron transport: The Feo system[END_REF] . Our result suggests that in the early stationary phase in an acetate-saturated environment, ferrous iron is no longer abundant, and activation of the feoAABC system may allow F. duncaniae A2-165 cells to maintain iron homeostasis in these conditions.

Under high-acetate conditions, feoB is the most transcribed feo homolog

In order to confirm our hypothesis of limited iron availability in the high-acetate culture conditions, we analyzed feoB expression in the presence of excess ferrous sulfate (Fig. 3). Figure 3A illustrates ferrous iron uptake and iron homeostasis in F. duncaniae. As a control, we also analyzed gene expression in low-acetate conditions, as well as the expression of feoAB (CG447_08795, log 2 FC: -4.3, see Supplementary Table S4 online) and butCoA, which encodes the terminal enzyme required for butyrate production (Fig. 3A). A new set of F. duncaniae A2-165 cultures was prepared with high or low levels of acetate and with or without ferrous sulfate, and sampling was performed as previously described (i.e., in the late exponential phase, indicated by E, and the early stationary phase, indicated by S, Fig. 3B). Figure 3B presents the results regarding the expression ratios (S vs. E) of feoB, feoAB, and butCoA obtained under the different conditions. These clearly demonstrated that the feoB expression was significantly triggered (log 2 FC: 6.0) during the early stationary phase, only in the high-acetate condition, and in the absence of ferrous sulfate supplementation. Moreover, its expression was totally repressed in the presence of ferrous sulfate (log 2 FC: -2.0). Overall, the feoB regulation was dependent on the availability of an iron source in the medium, with strong activation and repression in the absence and presence of ferrous sulfate, respectively. For the feoAB gene, the expression ratios were similar in the absence or presence of an iron source In the FeoB systems that have been described to date, cytosolic proteins are required for ferrous iron acquisition but the exact mechanism is not yet known [START_REF] Sestok | Toward a mechanistic understanding of Feo-mediated ferrous iron uptake[END_REF] . The glycolysis pathway and Faecalibacterium's genus-specific butyrate production pathway (shown as butyrate cycle) are shown. Pyruvate is converted to acetyl-CoA by pyruvate:ferredoxin oxidoreductase (PFOR) and the energy generated during butyrate production is conserved through the buildup of a proton gradient via the activity of a membrane-associated NADH:ferredoxin oxidoreductase encoded by two putative rnf operons (rnfDEA, CG447_09840-830, rnfCDGEAB CG447_10905-930) [START_REF] Heinken | Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe[END_REF] . Ferredoxin proteins (orange color). See Tables S2-S4 in Supplementary file 2 for data on DE genes (gene ID, COG numbers, protein annotation, log 2 FC, padj value, category). (B) Effect of the addition of ferrous sulfate on the transcription of feoB, feoAB, and butCoA genes, quantified using RT-PCR. Growth kinetics of F. duncaniae strain A2-165 in the presence or absence of ferrous sulfate (50 µM) in high-acetate (23 mM acetate) and low-acetate (3 mM) growth conditions. Square: culture sampling at T6 (exponential (E) growth phase) and T10 (early stationary (S) growth phase) time points. Genetic organization of the putative feoA 1 A 2 BC operon is shown.

in both acetate growth conditions, indicating that the regulation of feoAB is independent of iron availability in our growth condition. For the butCoA gene, we observed a positive growth phase effect in both acetate and iron conditions with stronger activation in the high-acetate conditions (Fig. 3B). Overall, these results demonstrate that regulation of the expression of feoAABC and feoAB differs significantly and suggest that the FeoB and FeoAB systems of F. duncaniae A2-165 play nonredundant roles in ferrous iron acquisition.

FeoB peptides from strain A2-165 are found in abundance in a healthy human fecal metaproteome

We were interested in studying feoB expression in the human gut microbiome. For this, we analyzed a fecal metaproteomic dataset obtained from eight healthy individuals, which included 123,425 peptides from the envelope fraction of the gut microbiota (Fig. 4) [START_REF] Henry | Modern metaproteomics: A unique tool to characterize the active microbiome in health and diseases, and pave the road towards new biomarkers-example of Crohn's disease and ulcerative colitis flare-ups[END_REF] . The metaproteomics/transcriptomics data can be found in Supplementary Tables S6-S8 online. Among these peptides, 236 matched with 10 of the 42 transporter genes that we had found to be upregulated in high-acetate conditions. Remarkably, the second highest degree of protein coverage (43.6%, 51 peptides) was found for the FeoB transporter. Of those 51 peptides, 9 were specific to a single protein in the metaproteomic dataset 'a5.b59.a1' (see Supplementary Table S7-2 'CG447_12750 FeoB' and Supplementary Fig. S8 online), which was identified as FeoB of the A2-165 strain (K04759 in the KEGG orthology database). In addition, among the 573 identified proteins from A2-165 strain, FeoB belongs to the top 20 hits in term of spectra number (see Supplementary Table S8 online). On the other hand, FeoAB protein exhibited a fivefold lower number of spectra corresponding to the 284th position in the A2-165 proteins list (see Supplementary Table S8 online). Overall, this demonstrates that FeoB, but not FeoAB, from A2-165 is found in abundance in this healthy human fecal metaproteome [START_REF] Henry | Modern metaproteomics: A unique tool to characterize the active microbiome in health and diseases, and pave the road towards new biomarkers-example of Crohn's disease and ulcerative colitis flare-ups[END_REF] .

Discussion

Two early stationary lifestyles of F. duncaniae A2-165

Here, we investigated the adjustments in the bacterial transcriptome when cells of F. duncaniae A2-165 entered the stationary growth phase in low-and high-acetate conditions. To our knowledge, this is the first physiological study based on transcriptomic and metabolic analyses that focuses on the entry into the stationary growth phase of F. duncaniae and, moreover, of a bacterium belonging to the Faecalibacterium genus.

Given that Faecalibacterium is a strictly anaerobic bacterium, cultivation presents challenges [START_REF] Martin | Faecalibacterium: A bacterial genus with promising human health applications[END_REF] . We have limited options for monitoring the growth of F. duncaniae, which include a semi-defined medium ("Yeast, Casitone, Fatty acid" named YCFA medium of Duncan laboratory 2 ) with slow growth and low biomass, or rapid growth with high biomass in the rich complex BHIS medium. We opted for the latter method to enable accurate and precise tracking of stationary phase entry over a 12-14 h period.

Comparative analysis of the high-and low-acetate transcriptomes showed two different metabolic responses regarding the number of genes and their functions. Given that acetate is a major growth factor (i.e. major energy source) [START_REF] Heinken | Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe[END_REF] , this seems consistent. Because of the lack of relevant data from the literature with which to compare our results, we chose to focus on the strongest and clearest effects, i.e., high fold-changes in expression. In the future, it will be necessary to study (i) the functions carried by the weaker adjustments in the transcriptome (i.e. lower fold change), (ii) this adaptive response in continuous culturing using chemostats, (iii) this adaptive response in co-culture models with acetate-producing bacteria.

Our experimental design enabled the identification of a general stress response under low acetate growth conditions. A characteristic of the exponential-stationary transition is the induction of stress proteins adapted for general stress condition. The general stress response has been very well characterized in model bacteria such as Escherichia coli and Bacillus subtilis [START_REF] Hecker | Heat-shock and general stress response in Bacillus subtilis[END_REF] , but this protective adaptive response is not known in Faecalibacterium. Notably, a general stress response was observed only in low-acetate conditions; concomitantly with the general stress response, a negative regulation of protein synthesis genes and a positive regulation of genes encoding type II toxin/antitoxin modules were also observed. As the majority of type II toxins inhibit translation [START_REF] Harms | Toxins, targets, and triggers: An overview of toxin-antitoxin biology[END_REF] , we can hypothesize that the former observation may be the consequence of the latter. Sigma B is the sigma factor involved in the control of the general stress response [START_REF] Hecker | Heat-shock and general stress response in Bacillus subtilis[END_REF] in many bacteria including model bacteria and several anaerobic bacteria such as Clostridioides difficile [START_REF] Morvan | Responses of Clostridia to oxygen: From detoxification to adaptive strategies[END_REF] . Remarkably, the gene encoding Sigma B is not present in A2-165 genome. Our functional analysis led to a list of genes encoding Sigma factors, that could be involved in the control of this protective response in low-acetate conditions. To our knowledge, this study represents the first description of a general stress response, in the early stationary phase, in acetate-limiting conditions in Faecalibacterium.

FeoB transporters search strategy

In the second part of our study, we chose to study bacterial transporters of the Feo family because the transport function of ferrous iron and its regulation are well characterized [START_REF] Saier | A functional-phylogenetic system for the classification of transport proteins[END_REF][START_REF] Sestok | Toward a mechanistic understanding of Feo-mediated ferrous iron uptake[END_REF] . For this, we focused on the fecal metaproteome of healthy individuals, previously published [START_REF] Henry | Modern metaproteomics: A unique tool to characterize the active microbiome in health and diseases, and pave the road towards new biomarkers-example of Crohn's disease and ulcerative colitis flare-ups[END_REF] . This metaproteome was of interest in our study of the F. duncaniae A2-165 import systems because it targeted bacterial envelope proteins. We combined high-resolution mass spectrometry of fecal specimens with RNA-seq of F. duncaniae A2-165 pure culture. Our metaproteomic analysis shows a significant difference in abundance between FeoB and FeoAB, suggesting variations in the regulation of feoAABC and feoAB expression in the context of an healthy gut microbiome. In conclusion, our search strategy allows us to capture the major A2-165 Feo import systems, namely the FeoB transporter. In the future, this search strategy can be extended to investigate Feo transporters in other bacteria of the genus Faecalibacterium using the same metaproteomic dataset.

Iron homeostasis and butyrate production

In many environments, including the human gut, iron is a limiting nutrient for growth, and high-affinity uptake systems play a central role in ferrous iron homeostasis [START_REF] Pi | Ferrous iron efflux systems in bacteria[END_REF] . Maintenance of ferrous iron homeostasis is crucial for the production of butyrate [START_REF] Heinken | Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe[END_REF] because this process requires two iron-binding ferredoxins as illustrated in Fig. 3A. Here, we demonstrated that butCoA expression was strongly upregulated regardless the supplementation of cultures with ferrous sulfate. This result suggests that, in the early stationary growth phase in high-acetate conditions, mechanisms of ferrous iron homeostasis were well established in F. duncaniae A2-165.

Interestingly, together with upregulation of feoAABC, we also detected upregulation of a flavodoxin-encoding gene (see Supplementary Table S4 online). This is consistent with previous studies reporting that iron-free flavodoxin replaces iron-sulfur ferredoxin under iron-limited conditions [START_REF] Pi | Ferrous iron efflux systems in bacteria[END_REF][START_REF] Pisithkul | Metabolic remodeling during biofilm development of Bacillus subtilis[END_REF] . Because flavodoxin and ferredoxin both mediate electron transfer in redox processes, the use of flavodoxin could free up iron for utilization by other iron-dependent enzymes. In other word, flavodoxins are key players in maintenance of ferrous iron homeostasis in iron-limited environment [START_REF] Pi | Ferrous iron efflux systems in bacteria[END_REF][START_REF] Pisithkul | Metabolic remodeling during biofilm development of Bacillus subtilis[END_REF] . For example, in C. difficile, the production of flavodoxin is tied to iron homeostasis in iron-limited conditions [START_REF] Berges | Iron regulation in Clostridioides difficile[END_REF] . In addition, the switch to flavodoxin as electron transfer protein may have significant effects on the activity of numerous enzymes that use flavodoxin as a redox partner. For example, in B. subtilis, flavodoxin is the redox partner for the acyl lipid desaturase involved in fatty-acid desaturation [START_REF] Chazarreta-Cifre | Role of ferredoxin and flavodoxins in Bacillus subtilis fatty acid desaturation[END_REF] . To date, similar data are not available for Faecalibacterium, but the impact of flavodoxins on the activity of certain metabolic pathways, including butyrate pathway, as well as the link with iron availability, merits further investigation.

Methods

Strain used for experimental culture

This study used a stock of Faecalibacterium duncaniae A2-165 (DSM No. 17677, DSMZ collection, Braunschweig, Germany) originally isolated from human fecal stool by S. H. Duncan (University of Aberdeen, United Kingdom) [START_REF] Duncan | Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb[END_REF] and maintained by V. Robert, MICALIS Institute, INRAE, France.

Cultivation experiments of F. duncaniae

F. duncaniae A2-165 was grown under anaerobic conditions (anaerobic chamber: N 2 = 90%, CO 2 = 5%, and H 2 = 5%) at 37 °C in BHIS medium (also named LYBHI in our previous studies), which is brain heart infusion broth (BHI, 37 g/L, Difco) supplemented with yeast extract (5 g/L, Difco), cellobiose (1 mg/mL, Sigma), maltose (1 mg/mL, Sigma), and cysteine (0.5 mg/mL, Sigma) [START_REF] Martin | The commensal bacterium Faecalibacterium prausnitzii is protective in DNBS-induced chronic moderate and severe colitis models[END_REF] . The strain was thawed and grown from a 10% inoculation in 10 mL BHIS for 24 h at 37 °C, followed by a 1% inoculation in 10 mL BHIS for overnight growth (16-18 h). The experimental cultures were then created using 2% inoculation in 50 mL BHIS medium with (BHISAc) or without the addition of sodium-acetate solution (20 mM, Sigma [START_REF] Duncan | Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb[END_REF][START_REF] Heinken | Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe[END_REF] ) at the time of inoculation. Growth kinetics were monitored by measuring the OD 600 nm every hour. The low acetate condition (3 mM) corresponded to the basal amount of acetate that we measured in the BHIS growth medium. The high acetate condition (20 mM added to the medium, i.e. final concentration 23 mM), was based on the previous in vitro studies of Duncan et al. [START_REF] Duncan | Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb[END_REF] and Heinken et al. [START_REF] Heinken | Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe[END_REF] , as well as our own measurements of acetate concentration in human feces (median value 20 mM, see Table 1 of Martin et al. [START_REF] Martin | Functional characterization of novel Faecalibacterium prausnitzii strains isolated from healthy volunteers: A step forward in the use of F. prausnitzii as a next-generation probiotic[END_REF] ).

Addition of ferrous sulfate to F. duncaniae culture

A fresh solution of ferrous sulfate (FeSO 4 -7H 2 O, Sigma) was prepared with deionized water and filter-sterilized. The experimental cultures were created using 2% inoculations in 50 mL BHIS or BHISAc media. Ferrous sulfate (50 µM, Sigma) was added 3 h after inoculation.

Short-chain fatty acid (SCFA) production and consumption

Gas chromatography (7890B, Agilent Technologies) was used to identify the short-chain fatty acids present in culture supernatants. The SCFAs of interest in this study were acetate and butyrate. An internal standard of 2-ethylbutyrate was used to normalize the data in each run. Measurements of SCFA concentrations in the bacterial samples were normalized using the basal SCFA levels of BHISAc and BHIS media from the same experiment.

Collection of RNA samples

For both growth conditions, cells and culture supernatant were sampled in the late exponential growth phase (7 h after inoculation) and early stationary growth phase (10 h after inoculation) for RNA extraction (cells) and SCFA analysis (supernatant). At the times of sampling, dilutions were created of all cultures and plated on BHIS agar for quantification of colony-forming units (CFUs).

RNA extraction

The single-step RNA isolation method was used, with TRIzol reagent and the FastPrep-24™ 5G instrument. For RNA-Seq and RT-PCR analyses, 2 mL of each culture was harvested and centrifuged (30 s, 13,000 rpm) in the Freter chamber, and cell pellets were snap-frozen in liquid nitrogen. 1 mL of TRIzol reagent (phenol-based RNA extraction buffer, Ambion, ThermoFisher Scientific) and 0.4 g of glass beads (0.1 mm, Bühler, ThermoFisher Scientific) were added to the defrosted pellet, and cell lysis was performed with a FastPrep-24™ 5G instrument (MP Biomedicals) (speed 6, 40 s). RNA precipitation, washing, and solubilization was carried out following the TRIzol protocol. Residual DNA from the RNA preparations was enzymatically removed using TURBO DNA-free (Ambion, United Kingdom). RNA quality was assessed with the Agilent 6000 Nano kit using an Agilent 2100 bioanalyzer (Stratagene, Agilent Technologies, France); RIN values were in the 7.7-8.5 range. Total RNA was purified from three biological replicates for RNA-Seq experiments and for RT-qPCR analysis. Extracted RNA samples were stored in RNAase/DNAse-free water (Ambion, United Kingdom) at -80 °C.

Library construction and Illumina sequencing

Total RNA quality was assessed using an Agilent Bioanalyzer 2100 and the RNA 6000 Pico kit (Agilent Technologies). Directional RNA-Seq libraries were constructed using the TruSeq Stranded Total RNA library prep kit, with bacterial Ribo-Zero reagents (Illumina), following the manufacturer's instructions; 500 ng of total RNA were used (I2BC HTS platform, CNRS, Gif-sur-Yvettes, France). After the Ribo-Zero step, the samples were checked on the Agilent Bioanalyzer to verify rRNA depletion. The quality of the libraries was assessed on an Agilent Bioanalyzer 2100, using an Agilent High Sensitivity DNA Kit. Libraries were pooled in equimolar proportions and sequenced in a paired-end 2 × 75-pb run on an Illumina NextSeq500 instrument (I2BC HTS platform, CNRS, Gif-sur-Yvettes, France). Demultiplexing was performed with bcl2fastq2 v2.18.12. Adapters were trimmed with Cutadapt v1.15, and only reads longer than 10 pb were kept for further analysis.

Mapping and identification of differentially expressed genes

Reads were mapped on the genome of F. duncaniae strain A2-165 (GenBank: CP022479.1) with BWA 0.6.2-r126, and were counted using the subread feature of Counts v1.5.2. Analyses of differential expression were performed in R using DESeq2 (I2BC HTS platform, CNRS, Gif-sur-Yvettes, France). In total, 2900 genes-including 2819 protein-coding sequences, 63 tRNA genes, and 18 rRNA genes, were mapped. Only the first two groups were analyzed in this study, so that a total of 2882 genes were considered. These were further filtered to retain only ORFs that showed a four-fold change in expression (absolute value Log 2 FC > = 2) (up/down) between treatment conditions. RNA-Seq datasets can be found on the database Omics Dataverse under the DOI accession number BDNCT2 (https:// doi. org/ 10. 15454/ BDNCT2).

RT-PCR analysis

We generated cDNA from 1 μg of total RNA using the High Capacity cDNA Reverse Transcription kit (Fisher Scientific, France) and random hexamers. The quality of cDNA was checked with an Agilent 6000 Pico kit and an Agilent 2100 Bioanalyzer (Stratagene, Agilent Technologies, France). We carried out qPCR in duplicate, in a reaction volume of 20 μL containing 500 pg of cDNA, 15 μL of SYBR ® Green PCR Master Mix (Applied Biosystems, Courtaboeuf, France), and 300 nM of each gene-specific primer. The primers were designed with Primer Express ® (version 3.0). We generated standard curves for each set of primers, using serial dilutions (four dilutions) of cDNA obtained from a mix of total RNA collected in BHISAc and BHIS. Amplification was carried out with an ABI ® PRISM 7900 thermal cycler (Applied Biosystems), with the following thermal profile: 2 min at 50 °C, 10 min at 95 °C, and 40 cycles of 15 s at 95 °C and 60 s at 60 °C. The specificity of each PCR amplicon was checked by melting curve analysis. Here, the feoB (CG447_12750, F5′-tgatcttcaacctgctgtgc, R5′-gccacgatggtgaagaagtt), feoAB (CG447_08795, F5′-ataccgaagtcaccgacctg R5′-ctccatcagctgcatcgtta) and butCoA (CG447_01820, F5′actttgttctgggcgcatac, R5′-ggtcagtcccttcaggttca) primers used in this study. The efp gene (CG447_05125), encoding the translation elongation factor P, was used for normalization with the primers efpF (5-gttgagttccagcacgtgaa-3) and efpR (5-aaagcctgagggaactttgc-3). The relative change in gene expression was recorded as the ratio of normalized target concentrations and was calculated with the comparative ΔΔCt method [START_REF] Bustin | The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments[END_REF] . The mean values for three independent experiments are presented.

Protein sequence annotations, functional classification

Protein annotation data from the PATRIC database [START_REF] Wattam | the bacterial bioinformatics database and analysis resource[END_REF] (PATRIC genome ID 853.173) were used for functional classification. As the functional subsystem coverage in PATRIC was low (29%), EggNOG database was used for COG-based functional classifications using the COG system (https:// www. ncbi. nlm. nih. gov/ resea rch/ COG).

We created a simplified classification scheme with 12 categories; the largest metabolism classes (protein synthesis, energy, and import system) were retained while smaller metabolism classes (cell wall metabolism, lipid metabolism, amino acid metabolism, amino sugar metabolism, nucleotide metabolism, vitamin and cofactor metabolism) were merged into an "Other metabolism" category. The "Import system" and "Export system" classes encompassed all membrane transport systems involved in the uptake/export processes of nutrients, micronutrients, ions, and unknown compounds. "Stress response" category encompassed toxin/antitoxin systems and chaperones. The TC-BLAST tool (TCD database https:// www. tcdb. org/) was used for the determination of the number of TMS (putative TransMembrane Segment) and for the import system family assignment. To characterize gene similarity, homology, and gene context, NCBI BLAST was used, in particular for analysis of feo genes.

Fecal metaproteomics analysis

We conducted an analysis of 16 published available metaproteomes derived from the envelope fractions of fecal microbiota obtained from eight healthy donors without any family history of gastrointestinal disease and no medication use [START_REF] Henry | Modern metaproteomics: A unique tool to characterize the active microbiome in health and diseases, and pave the road towards new biomarkers-example of Crohn's disease and ulcerative colitis flare-ups[END_REF] . The details of the metaproteomic method has been described previously [START_REF] Henry | Modern metaproteomics: A unique tool to characterize the active microbiome in health and diseases, and pave the road towards new biomarkers-example of Crohn's disease and ulcerative colitis flare-ups[END_REF] . To note, a minimum of two distinct peptides identified across all samples in the dataset was set to validate a protein in order to exclude proteins of weak proof of presence.

Combined A2-165 transcriptomics and fecal metaproteomics analysis

Each of the 123,425 peptide sequences identified in the fecal metaproteomes was matched against each of the 42 query protein sequences identified in this RNA-seq analysis (see Supplementary Tables S6-S8 online) in the R environment.

Statistical analysis

Normally distributed data are presented as mean ± standard deviation (SD), skewed data as median with interquartile range (IQR), and categorical data as frequencies with proportions. T-tests for independent samples and one-way analysis of variance (ANOVA) (or Kruskal-Wallis when not normally distributed) were performed for continuous variables. Data were represented and analyzed with GraphPad Prism 8.

Figure 1 .

 1 Figure 1. Acetate growth effect and butyrate production in F. duncaniae A2-165 cultures. (A) Schematic view of the importance of acetate in the butyrate biosynthetic pathway. The production of butyrate is dependent on glycolysis and the butyrate cycle. The key enzyme for butyrate production is butyryl-CoA:acetate CoAtransferase (ButCoAT), which consumes extracellular acetate to produce butyrate and acetyl-CoA from butyryl-CoA. (B) Growth kinetics of F. duncaniae A2-165 under high-and low-acetate conditions. Growth kinetics are shown for bacteria cultured in BHIS medium with 23 mM acetate (high-acetate, orange color) or with 3 mM acetate (low-acetate, blue color). Arrows indicate time points of sampling for the RNA-Seq transcriptome analysis. Sampling was performed after 7 h (late exponential phase, E and Ea for low-and highacetate conditions, respectively) and 10 h (early stationary phase, S and Sa for low-and high-acetate conditions, respectively) of growth. N = 4, median with interquartile range (IQR) is shown. (C) Individual growth-rate measures in high/low-acetate conditions. N = 4, raw data, median with IQR are shown. (D) SCFA concentrations (expressed as molarity) of E/Ea and S/Sa culture supernatants. Butyrate production is presented as positive values while acetate consumption is presented as negative values. Acetate values were normalized with the acetate value of BHIS medium, which contains 3 mM of acetate. N = 4, median with IQR is shown. (E) Overview of RNA-Seq data.The number of (differentially expressed) DE genes for each comparison is presented in the form of a bar chart. Two-group comparisons were conducted between high-and low-acetate conditions in the late exponential phase (Ea vs. E) and early stationary phase (Sa vs. S). Additionally, two-group comparisons were performed between the early stationary and late exponential phases in high-acetate (Sa vs. Ea) and low-acetate (S vs. E) conditions. log 2 FC ≥ |2|, FDR-adjusted p-value ≤ 0.01.

A B 2 .

 2 Transcriptional responses of F. duncaniae A2-165 to acetate. (A) Pie charts of up-and downregulated genes showing the relative frequency (%) of each functional category. The number of genes in each category is shown in Table

Figure 3 .

 3 Figure 3. Expression analysis of feoB, feoAB and butCoA by RT-PCR. (A) Schematic representation of ferrous iron uptake, iron protein synthesis, glycolysis, and butyrate metabolism pathway. The FeoB membrane transporter, NFeoB domain with GTPase activity, and FeoA1, FeoA2, and FeoC cytosolic proteins are indicated.In the FeoB systems that have been described to date, cytosolic proteins are required for ferrous iron acquisition but the exact mechanism is not yet known[START_REF] Sestok | Toward a mechanistic understanding of Feo-mediated ferrous iron uptake[END_REF] . The glycolysis pathway and Faecalibacterium's genus-specific butyrate production pathway (shown as butyrate cycle) are shown. Pyruvate is converted to acetyl-CoA by pyruvate:ferredoxin oxidoreductase (PFOR) and the energy generated during butyrate production is conserved through the buildup of a proton gradient via the activity of a membrane-associated NADH:ferredoxin oxidoreductase encoded by two putative rnf operons (rnfDEA, CG447_09840-830, rnfCDGEAB CG447_10905-930)[START_REF] Heinken | Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe[END_REF] . Ferredoxin proteins (orange color). See Tables S2-S4 in Supplementary file 2 for data on DE genes (gene ID, COG numbers, protein annotation, log 2 FC, padj value, category). (B) Effect of the addition of ferrous sulfate on the transcription of feoB, feoAB, and butCoA genes, quantified using RT-PCR. Growth kinetics of F. duncaniae strain A2-165 in the presence or absence of ferrous sulfate (50 µM) in high-acetate (23 mM acetate) and low-acetate (3 mM) growth conditions. Square: culture sampling at T6 (exponential (E) growth phase) and T10 (early stationary (S) growth phase) time points. Genetic organization of the putative feoA 1 A 2 BC operon is shown.

Figure 4 .

 4 Figure 4. Workflow for the search for FeoB peptides in the healthy human gut metaproteome. RNA-Seq transcriptome of early stationary acetate cultures of F. duncaniae strain A2-165. (A) The general workflow employed for RNA-Seq in the current study: from identification of DE genes in the early stationary phase (Sa vs S comparison) to feoAABC operon selection. (B) Published human gut metaproteome. The general workflow employed in a published study of the gut metaproteome. The data were obtained from eight healthy subjects included in a study of intestinal bowel diseases 35 . (C) Integrating RNA-Seq and metaproteomic data. The general workflow employed to integrate RNA-Seq and metaproteomic data in the current study and the presentation of data for F. duncaniae A2-165.

Scientific Reports | (2024) 14:987 | https://doi.org/10.1038/s41598-023-51059-3

Scientific Reports | (2024) 14:987 | https://doi.org/10.1038/s41598-023-51059-3

Acknowledgements

We acknowledge the sequencing and bioinformatics expertise of the I2BC High-throughput sequencing facility. This work has benefited from the facilities and expertise of @BRIDGe (Université Paris-Saclay, INRAE,

Funding

This work was supported by the French funding agency "Agence Nationale de la Recherche" under Grant (ANR-16-CE29-0020); under Grant (BP-Acetate, Qualiment-Institut Carnot); and under Grant (ANR-10-INBS-09).

Data availability

The data that support the findings of this study are openly available in database Omics Dataverse at https:// doi. org/ 10. 15454/ BDNCT2 [DOI accession number BDNCT2]. All of the material is owned by the authors and/or no permissions are required.

Author contributions

E.H., S.L. and M.T. conceptualized, conceived, and designed the study; E.H., S.V., S.C., and Y.J. performed research; E.H., S.V., S.A., S.L., Y.J., C.J., C.H. analysed data; E.H., S.L., C.J., and M.T. wrote the original draft; E.H., S.L., M.T., C.J., S.V., P.L., H.S., C.H., L.B., S.A. revised the manuscript; E.H., L.B. and M.T., funding acquisition. All approved the submitted version of the manuscript.

Competing interests

The authors declare no competing interests.


domain: phys spi

text:
Tatiana E Itina

Mechanisms of laser-based synthesis and modifications of nanomaterials

Keywords: Laser, nanoparticles, synthesis, nanocomposite, vibrations, sintering, fragmentation, modeling, simulation

Lasers are known to be extremely versatile tools suitable both for the synthesis and modifications of numerous nanomaterials with unique and extremely interesting optical properties suitable for a wide range of applications in various fields ranging from optics and photonics to medical applications. Efficient control over these processes is still challenging and often requires numerical simulations because of the complex interplay of many physical and chemical processes involved that depend on the combination of both material properties and laser parameters. To simulate these processes, multi-physical modeling should be used including electromagnetic, thermal, mechanical, and chemical effects taking place at several time and space scales. Depending on the experimental conditions, nanoparticles can be formed, grow, aggregate, or on the contrary decay, so that a set of transient variations often take place, particularly when multipulse laser irradiation is applied. In the case of short and ultra-short laser pulses, strongly non-linear and time-dependent processes play a role involving not only ionization but also phase transitions, acoustic vibrations, shock waves, as well as void formation, and cavitation. If a considerable energy is released in a very short time, firstly aggregates decay, then nanoparticles are fragmented. Here, based on numerical calculations, the roles of several above-mentioned effects are analyzed. The performed simulations can be used for a better understanding of laser interactions with nanoobjects.

INTRODUCTION

A wide variety of recently developed laser systems from continuous wave (CW) to nanosecond, short (picosecond), and ultra-short (femtosecond) pulsed ones, have enabled the development of numerous laser applications in various fields ranging from optics and photonics to biology and medicine. [START_REF] Jr | Principles of Laser Materials Processing: Developments and Applications[END_REF] Among the main advantages of a typical laser treatment is the possibility to carefully choose laser parameters (energy, wavelength, pulse duration polarization, temporal and spatial pulse shape) for the required results. All these parameters affect the resulting material response. This is particularly true in the case of nanocomposite materials and nano-and meta-objects because effects such as electromagnetic field enhancement and plasmonic absorption enter into play. Lasers are also used to generate nanoparticles by laser ablation in liquids, gases, or in a vacuum. Additional laser irradiation can be used to sinter fragment nanoparticles, induce aggregation, melting, or coalescence, create Janus, core-shells, or alloy nanoparticles with unique conjugated properties, such as magneto-optical or chemical-plasmonic, etc. This opens ways for the fabrication of smart nanomaterials with combined properties reacting in a very particular way that can be subjected to several external forces or fields.

To better understand the mechanisms involved in laser-based synthesis and modifications of nanomaterials, computer simulations were used in addition to numerous experiments. Several numerical approaches were developed describing the involved multi-scale effects and ranging from ab initio methods, such as DFT and TD-DFT, molecular dynamics (quantum and classical), mesoscopic models, thermal models, thermo-mechanical and hydrodynamical models, etc [START_REF] Miloshevsky | Ultrafast laser matter interactions: modelling approaches, challenges, and prospects[END_REF] . By using such approaches, many mechanisms involved were described in detail ranging from optical parameter modifications, structural defects formation, other photo-thermal, photo-chemical, photo-mechanical effects that occur at relatively low laser energies, to much more violent ablative behavior involving material spallation, overheating, explosive boiling, cavitation, and/or dynamic fragmentation [START_REF] Povarnitsyn | Material decomposition mechanisms in femtosecond laser interactions with metals[END_REF] . Because of the collective nature of such effects and the rather large number of atoms or molecules involved, classical molecular dynamics and hydrodynamic approaches were found to describe these mechanisms quite correctly. However, only a very limited number of materials, mostly homogeneous, were considered. In reality, however, even in the initially homogeneous material, nano-defects are often generated as a result of multiple pulse irradiation. Additionally, nanoparticles are formed or either are suspended in the ambient gas or form colloids that can be transformed into nanocomposites with unique and adjustable properties. Furthermore, particles can be also ejected into a vacuum deposited on a distance substrate, or re-deposited back on the surface. Lasers can also induce their vibrations and lead to their complete or partial decomposition inducing nanobubbles' complexity. Many questions remain in the case of bi-metallic or complex nanoparticles, concerning not only their thermal stability but also the effects of laser on their shape, morphology, composition, optical and other properties.

SIMULATION DETAILS

Classical all-atom molecular dynamics [START_REF] Povarnitsyn | Molecular dynamics simulation of subpicosecond double-pulse laser ablation of metals[END_REF] is used that allows one to follow the detailed dynamics of nano-systems at different time scales based just on the interaction potentials, or force fields. All nanoparticles were firstly slightly heated above their melting and properly quenched for a sufficiently long time to form surface energy. Then such samples were subjected to much stronger heating during 20 ps well above melting and boiling points that was followed by a long cooling (up to several nanoseconds). The output of the calculations not only provides intriguing insights into the mechanisms involved but also allows one to describe non-equilibrium phase transitions and instabilities rather easily

RESULTS AND DISCUSSION

Nanoparticle oscillations upon laser heating

As soon as a nanoparticle has absorbed sufficient laser energy, it starts vibrating with frequency depending on its material and decreasing with increasing its size (Figure 1). This is actually the first observation that molecular dynamics simulation provides in agreement with several experiments performed. .

In addition to the so called "breathing mode", several acoustic vibrational modes are developed, as described by the classical Lamb model which remains valid down to the sizes of around 1 nm. At smaller sizes, corrections are required since system behaves differently, but because here studies the behavior of particles larger than several nanometers, this model remains applicable. Nanoparticles are known to be small objects and the role of surface increases when their size drops below a certain size in nanometric range, when the contribution of the surface potential energy in the total Gibbs energy overcomes the one of the volume or bilk potential energy

Nanoparticle fragmentation upon single pulsed laser heating

Upon of a nanoparticle, its surface experience instabilities. For clusters, Coulomb explosion model was often discussed [START_REF] Delfour | Mechanisms of ultrashort laser-induced fragmentation of metal nanoparticles in liquids: numerical insights[END_REF] .

For larger particles, however, effects can be similar to the ones observed in small liquid droplets and are characterized by well-known classical models like the ones based on instabilities (namely, Plateau-Rayleigh and/or Rayleigh -Taylor), multi-modal fragmentation, dynamic fragmentation, etc. [START_REF] Sazhin | Droplets and sprays[END_REF] To better understand nanoparticle response, elucidate mechanisms major and verify theoretical concepts, molecular simulations are carried out as a function of particle size and maximum temperature. The obtained results show that in fact such effects lead to the surface breakage facilitating nanoparticle deformation (Figure 2). In fact, the role of the surface is to confine the heat and to compensate expansion forces and mechanical stresses. As a result of the fast heating, surface tension drops down, and surface is destroyed. Typically, particle melting and evaporation start from the surface. At stronger heating, ejections of clusters and small junks can be observed. Further heating leads particle fragmentation due to a set of thermo-mechanical effects. [START_REF] Garrison | Limit of overheating and the threshold behavior in laser ablation[END_REF][START_REF] Itina | Decomposition of rapidly expanding liquid: Molecular dynamics study[END_REF] This happens if particle temperature approaches the thermodynamic critical one (Tc, rather than boiling point) known to define the limit of thermal stability. This criterion does not depend on particle size. However, a set of the accompanying effects, such as void formation, subnano-cavitation, dynamic fragmentation [START_REF] Grady | Mechanisms of dynamic fragmentation: Factors governing fragment size[END_REF] . depend on nanoparticle size, as well as nanoparticle's time to fracture (Figure 2), which rises with particle size and is proportional to ~N rp/Cs, where rp is particle radius and Cs is speed of sound in the particle material.

Multiple pulse irradiation

A series of simulations were performed where the ensemble of fragments formed upon single pulsed heating experienced fast heating again. The resulting effects look similar, even if the daughter particles are much smaller (Figure 3). If the concentrating of fragments is locally high, they can collide and sinter reforming novel nanoobjects. Thus, in the experiments, typically dynamic effects are observed as a function of the number of applied laser pulses involving aggregation and either desegregation or alternative melting. We note that here we neglect chemical effects, but they were considered recently in the presence of water. [START_REF] Jr | Principles of Laser Materials Processing: Developments and Applications[END_REF] Other commonly used solvents reduce oxidation and are therefore more interesting for future studies that are underway.

CONCLUSIONS

In this study, several questions have been addressed concernin nanoparticle behavior upon laser heating, and, namely, upon pulsed laser heating. The performed numerical atomistic modeling allow us to formulate the following conclusions:

-(i) The obtained results show how nanoparticles firstly start vibrating upon laser heating. The corresponding vibration frequencies depend on nanoparticle material and they decrease with size if it is larger than ~1 nm. Down to particle sizes of several nanometers the typical vibration modes are still well described by the classical Lamb model. These vibrations can be considerably enhanced in case of resonances.

-(ii) Small size of nanoparticles leads to the confinement of heat and stresses. Both surface energy and surface tension that help particle to keep its shape, drop dramatically with temperature upon heating, so that particle's surface start experiencing common instabilities (mostly, Plateau-Rayleigh and/or Rayleigh-Taylor) as well as structural change facilitating particle deformation.

-(iii) As a result of a sufficient pulsed heating not only atom by atom evaporation takes place, but also surface fragmentation if maximum particle temperature reaches the critical thermodynamic one, or the limit of its stability. Furthermore, thermo-mechanical effects, play a role for particles larger than 1-10 nm, when considerable stresses and strains are created in the particle. Then, sub-nano voids are formed and oscillate. Depending on particle size and affecting the time when particle starts to break up. This time rises almost linearly as ~N rp/Cs with time indicating several periods of stress or pressure waves passing toward the surface and back to center.

-(iv) In the case of multiple laser irradiation, modifications of nanoparticle can become dynamic at rather moderate energy since nanoparticles can be disintegrated or broken, but then aggregate and sinter again. As a result, preferential growth instead of fragmentation takes place. Above a certain rather high threshold, however, mostly breakage takes place.

AKNOWLEDGEMENTS

  [START_REF] Del Fatti | Acoustic vibration of metal films and nanoparticles[END_REF]

Figure 1 .

 1 Figure 1. (a)-Upper plots show typical time-evolution of Au nanoparticle with radius 30 aAu, t=20ps,50ps,1,6ns, Tmax= 8 kK; (b) Lambs vibration frequency (in THz) vs size for gold nanoparticle, where radius is normalized by unit cell length (aAu = 4.05 Å); (c) -Calculated time to decay (ps) for Au NP (red) and Al NP (blue) vs radius normalized by unit cell lengths.

Figure 2 .

 2 Figure 2. (a) Snapshort from a simulation for Au NP with initial radius of 30 aAu and when heating is above threshold (Tmax= 9500 K) at t=20, 50 and 100 ps, (aAu = 4.05 Å).

Figure 3 .

 3 Figure 3. Snapshot from multi-pulse irradiation of a nanoparticle showing fragment formation, interaction and new particle formation. The presented results are obtained for an alloy CoAu nanoparticle. (t=0, t=50 ps, t=1.6ns),

Computer support from CINES, France under the project "Modeling laser ultra-short interactions with surfaces and nano-objects "A0150814604 is gratefully acknowledged. The author is also thankful to many colleagues and collaborators working on laser experiments for numerous stimulating discussions.