Bioengineered ROS-tolerant probiotic reshapes gut microbiota-host axis to ameliorate type 2 diabetes in male mice

Domain: chemistry
Published: 2026-03-02
Editorial outcome: major_revision

Abstract
The pandemic-scale progression of type 2 diabetes mellitus (T2DM) necessitates innovative interventions targeting the pathogenic triad of insulin resistance, dysregulation of lipid metabolism, and gut microbiome dysbiosis. Here, we report a synthetically bioengineered probiotic consortium (REcN-F/Ca) developed through directed metabolic adaptations of Escherichia coli Nissle 1917 (EcN) under iterative hydrogen peroxide selection, subsequently functionalized with fructooligosaccharide-calcium carbonate composites. REcN-F/Ca exhibits enhanced reactive oxygen species tolerance through upregulated antioxidant enzymes and hydrogen sulfide-mediated redox balancing, alongside improved gastrointestinal survivability. In high-fat diet-induced obese male mice, REcN-F/Ca restores gut microbiota diversity, enriches butyrogenic taxa (Lachnospiraceae and Blautia), and rescues short-chain fatty acids depletion. Transcriptomic profiling reveals PPAR signaling activation, driving lipid metabolism and suppressing adipose inflammation. These effects translate to systemic metabolic improvements with attenuated weight gain (−25.4%), restored glucose homeostasis, and reduced insulin resistance (HOMA-IR: −73.2%) in the obesity and T2DM murine model. Our findings establish REcN-F/Ca as a synthetically engineered probiotic that simultaneously corrects intestinal ecological perturbations and reverses host metabolic dysfunction, proposing a paradigm for metabolic syndrome management.

Introduction
The global prevalence of type 2 diabetes mellitus (T2DM) has reached epidemic proportions, characterized by with excessive circulating glucose and free fatty acids that drive dysregulated lipid metabolism, insulin resistance, systemic oxidative stress and gut microbiota dysbiosis.[1-4] While pharmacological interventions (e.g., PPAR agonists and GLP-1 analogs) offer symptomatic relief, their long-term efficacy is limited by an increased risk of side effect and failure to address gut microbiota dysbiosis—a hallmark of metabolic dysfunction.[5-9] Probiotic has emerged as promising modulators of the gut-metabolic axis, yet conventional strains often lack the robustness to survive gastrointestinal stressors or the metabolic versatility to counteract host-pathological processes.[10-12]

Escherichia coli Nissle 1917 (EcN), a well-characterized probiotic, has shown potential in mitigating intestinal inflammation through competitive exclusion and biofilm formation.[13] However, its native antioxidant defenses are insufficient to neutralize reactive oxygen species (ROS) in obesogenic microenvironments, and its inability to persistently colonize the inflamed gut limits therapeutic utility.[14] In the diabetic gut microenvironment, elevated levels of ROS generated from mitochondrial dysfunction and NADPH oxidase activity exacerbate intestinal barrier damage and inflammation, creating a vicious cycle that perpetuates metabolic dysfunction.[15,16] Notably, microbial communities in this milieu face dual challenges with nutrient abundance (e.g., glucose and lipids) and environmental stressors (e.g., ROS and bile acids). Analogous to how bacteria under antibiotic stress upregulate energy-dependent efflux pumps,[17,18] we hypothesized that probiotic subjected to sublethal ROS pressure would evolve enhanced antioxidant defenses and metabolic flexibility to thrive in hostile niches—a strategy that could be harnessed therapeutically.

ROS, particularly hydrogen peroxide (H2O2), serve as both a stressor and a signaling molecule in microbial systems.[19,20] While H2O2 is less reactive than hydroxyl radicals (•OH), its relative stability allows for controlled induction of oxidative stress, mimicking the chronic ROS exposure observed in diabetic intestines. Here, we engineer a next-generation probiotic by subjecting EcN to iterative H2O2-driven evolution to select for strains that couple ROS detoxification with metabolic adaptations favoring energy-efficient redox balancing, followed by sequential modification with fructooligosaccharides (FOS) and CaCO3 mineralization. While other prebiotics (e.g., inulin) exist, FOS has a shorter chain length than inulin, making it potentially more readily fermentable by a broader range of beneficial bacteria.[21] Unlike some encapsulation polymeric materials (e.g., chitosan, alginate) that may require complex synthesis or raise biocompatibility concerns, CaCO3 is a Food and Drug Administration–approved antacid.[22] Its mineralization process is simple, scalable, and results in a highly stable, protective shell.[23] We hypothesized that this ROS-tolerant EcN (REcN-F/Ca) would resist luminal oxidative stress, reprogram host lipid metabolism, and rectify high-fat diet-induced microbiota dysbiosis through short-chain fatty acids-dependent mechanisms. Using a combination of transcriptomics, metabolomics, and gnotobiotic models, we demonstrate that REcN-F/Ca shows superior ability in restoring glucose homeostasis, attenuating adipose inflammation, and enriching butyrate-producing taxa (Blautia and Lachnospiraceae). Our work establishes a blueprint for engineering multifunctional probiotic that targets both microbial and host metabolic networks, bridging a critical gap in translational microbiome therapeutics.

Results
ROS-tolerant probiotic design and antioxidant mechanisms exploration
To induce reactive oxygen species (ROS) tolerance in Escherichia coli Nissle 1917 (EcN) probiotic, hydrogen peroxide (H2O2) was selected as the model ROS. The minimum inhibitory concentration (MIC) assay was implemented to quantify bacterial tolerance evolution. Serial passages (n = 10) of EcN were performed in 96-well plates containing H2O2 gradients, with concentrations decreasing twofold from column 1 to 12 (Supplementary Fig. 1). Each H2O2 concentration was tested in triplicate. Following 24 h co-culture, MIC values were defined as the lowest H2O2 concentration in clear wells adjacent to turbid growth-positive wells (Supplementary Fig. 2). Wild-type EcN (WT, passage zero , P0) surviving the highest H2O2 concentrations were iteratively passaged under identical selective pressure for ten cycles (P1-P10). The H2O2 MICs were determined after each passage. Progressive MIC elevation across passages demonstrated successful development of ROS-tolerant EcN (REcN) (Fig. 1a and Supplementary Fig. 2).

Subsequently, transcriptomic profiling via RNA sequencing elucidated molecular mechanisms underlying adaptive phenotype of REcN. Comparative analysis revealed significant inter-strain expression heterogeneity through violin plots (Supplementary Fig. 3a), suggesting divergent transcriptional responses to sublethal H2O2 exposure. Differential expression analysis identified 912 upregulated (log FC > 1, p < 0.05) and 940 downregulated (log FC < -1, p < 0.05) genes in REcN versus EcN (Supplementary Fig. 3b), potentially associated with enhanced antioxidant pathways. Hierarchical clustering of expression profiles demonstrated intra-group homogeneity, with REcN and EcN strains forming distinct clusters (Supplementary Fig. 3c), indicative of conserved strain-specific molecular signatures. Principal component analysis (PCA) further confirmed transcriptional divergence between REcN and EcN cohorts (Supplementary Fig. 3d), supporting the emergence of unique molecular features in engineered strains.

Gene Ontology (GO) annotation analysis was performed to systematically characterize the functional profiles of differentially expressed genes in REcN.[24] The Comparative analysis of upregulated genes in REcN versus wild-type EcN revealed significant enrichment in three core functional categories: antioxidant activity (GO:0016209), molecular transducer activity (GO:0060089), and catalytic activity (GO:0003824) (Fig. 1b). This enrichment pattern suggests adaptive remodeling of stress response and metabolic regulatory networks in REcN. Gene set enrichment analysis (GSEA) further identified pronounced enrichment (normalized enrichment score [NES] = 1.15) of the oxidoreductase complex (GO:1990204) in REcN (Fig. 1c), implicating redox homeostasis as a key evolutionary trajectory under H2O2 selection pressure.

Subtype analysis of oxidoreductase-associated GO terms highlighted specific enrichment in oxidoreductase activities, especially those involving NAD(P)H and quinone or similar compounds (Supplementary Fig. 4a), suggested that the REcN undergone significant metabolic adaptations. NADH dehydrogenases are key components of the electron transport chain, playing a central role in energy metabolism and ROS management.[25] The NADH dehydrogenase activity (GO:0003954, Supplementary Fig. 4b) and oxidoreductase activity, NAD or NADP as acceptor (GO:0016620, Supplementary Fig. 4c) were significantly enriched. To functionally validate the enhanced energy metabolism, we measured the NADH dehydrogenase activity in EcN and REcN. Consistent with the RNA-seq data, REcN exhibited a significantly greater decrease in NADH absorbance at 340 nm over a 30-min incubation compared to the wild-type EcN strain, confirming its superior NADH dehydrogenase activity (Supplementary Fig. 5). These metabolic adaptations likely enhance electron transport chain efficiency, thereby coupling energy metabolism with ROS mitigation.

Notably, whole-genome sequencing (WGS) with single‑nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) analysis revealed that 6 missense mutations were found in the nuoCD gene (Table 1 and Supplementary Data 1), which encodes NADH-quinone oxidoreductase subunit C/D (Supplementary Data 2). This offers a plausible genetic basis for the observed increase in NADH dehydrogenase activity, which we confirmed through the enzymatic assay. Directed H2O2 selection pressure fixed mutations in key metabolic component, which led to stable transcriptional reprogramming, resulting in the optimized functional phenotype.

Targeted quantification of antioxidant enzymes demonstrated marked upregulation of sodA, sodB, sodC, and katG in REcN (Fig. 1d), corresponding to functional validation through enzymatic assays. Distinctly, REcN exhibited 1.8-fold higher superoxide dismutase (SOD) activity than EcN (Fig. 1e), catalyzing the disproportionation of superoxide radical (O2·-) to produce H2O2 and O2. The generated H2O2 could be further scavenged by the catalase (CAT) in REcN, which was confirmed by the consumption of H2O2 to O2 (Fig. 1f), collectively confirming systemic ROS-neutralizing capabilities. The transcriptomic data also indicted that the expression of soxR was downregulated, while the expression of oxyR was markedly upregulated in REcN (Supplementary Fig. 6). This shift in regulatory network activity aligns with the observed enhancement in peroxide-scavenging capabilities and suggests a prioritized adaptation to H2O2 stress.

GO analysis at the biological process level revealed significant enrichment in hydrogen sulfide (H2S) biosynthetic process (GO:0070814) and metabolic process (GO:0070813) in REcN (Supplementary Fig. 7a). Further GSEA corroborated these findings, demonstrating strong enrichment signals for H2S biosynthesis (NES = 1.15) and sulfur metabolism (NES = 1.11) in REcN (Fig. 1g and Supplementary Fig. 7b). These pathways may synergistically enhance antioxidant defenses, as H2S functions as a potent reducing agent capable of directly scavenging ROS,[26,27] while sulfur metabolism supports cysteine biosynthesis—a critical precursor for glutathione synthesis.[28]

Transcriptomic profiling identified coordinated upregulation of H₂S biosynthesis genes cysH, cysC, cysJ, cysI, cysN, and cysD in REcN (Supplementary Fig. 7c). Notably, sseA—encoding 3-mercaptopyruvate sulfurtransferase (3-MST ), a key enzyme in the non-canonical H2S production pathway—showed 1.9-fold induction (Supplementary Fig. 7d).[29] Therefore, we further employed the classic lead acetate reactivity test to detect H2S (Supplementary Fig. 8).[30] In this method, a filter paper saturated with a 2% lead acetate solution was positioned above a well plate containing the bacterial suspension. H2S produced by the probiotic subsequently reacted with lead acetate to form a brown lead sulfide precipitate. The results indicated that the REcN strain exhibited a higher H2S production after 24 h of incubation (Fig. 1h). This observation was further corroborated by the H2S–nucleophilic substitution–cyclization–based fluorescent probe analysis, which demonstrated a significant increase in H2S production in the REcN strain (Fig. 1i). To establish a direct causal link between H2S and ROS tolerance, we supplemented the wild-type EcN with the H2S donor NaHS (0.2 mM). This intervention dramatically increased its H2O2 MIC by 16-fold (Supplementary Fig. 9), demonstrating that H2S confers a robust antioxidant phenotype.

To explore additional mechanisms of ROS tolerance, we first assessed whether evolutionary adaptation altered outer membrane permeability. The ANS binding assay revealed no significant difference between EcN and REcN (Supplementary Fig. 10), indicating that the ROS tolerance was not attributable to a reduced uptake of oxidative compounds. The growth curve analysis revealed that REcN exhibited a faster growth rate during the exponential phase compared to EcN, although both reach similar final cell densities (Supplementary Fig. 11). This enhanced growth kinetics likely contributes to its competitive advantage in the gut environment. These multilayered adaptations—spanning enzymatic ROS neutralization (SOD/CAT), redox cofactor recycling (NAD(P)H oxidoreductases), and H2S-mediated antioxidant mechanisms—suggest potential applicability of REcN in managing oxidative stress-associated pathologies. The systemic enhancement of interconnected antioxidant networks positions this bioengineered probiotic as a candidate for further investigation in metabolic disorders linked to redox imbalance, including diabetes and obesity.[31]

REcN-driven metabolic reprogramming and therapeutic implications
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was employed to characterize metabolic adaptations in REcN.[32] Upregulated genes in REcN exhibited significant enrichment in lipid metabolism, energy metabolism, and carbohydrate metabolism (Fig. 2a). Specifically, scatterplot analysis highlighted pronounced activation of fatty acid degradation pathways (ko00071, Fig. 2b), with GSEA confirming enhanced lipid catabolic processes (NES = 1.48), fatty acid catabolic processes (NES = 1.29), and fatty acid degradation (NES = 1.15) in REcN (Fig. 2c-e).

Functional validation using Oil Red O staining demonstrated a significant reduction in cytoplasmic lipid droplet accumulation in 3T3-L1 adipocytes cultured with REcN-conditioned medium (Fig. 2f and Supplementary Fig. 12), quantitatively corroborating transcriptome-predicted lipid catabolic enhancement. Given the established link between T2DM and dysregulated lipid/carbohydrate metabolism,[33,34] these findings suggest REcN may modulate host metabolic homeostasis through microbiome-lipid axis interactions.

Concurrently, KEGG analysis revealed marked upregulation of energy transduction pathways in REcN, including oxidative phosphorylation (ko00190) and the electron respiratory chain (Fig. 2b and Supplementary Fig. 13a-c). Notably, the tricarboxylic acid (TCA) cycle pathway (ko00020) was significantly enhanced in REcN (Fig. 2b and Supplementary Fig. 13d), with a large number of associated genes being significantly upregulated (Supplementary Fig. 14). The upregulation of key pathway, such as pyruvate metabolism, in the TCA cycle was observed (Fig. 2b), suggesting that the REcN strain possesses enhanced energy production capabilities. The TCA cycle is a central metabolic pathway that plays a crucial role in energy production by generating ATP and NADH.[35] The enhanced expression of enzymes such as isocitrate dehydrogenase (icd, 1.9-fold), succinate dehydrogenase (sdhB, 2.7-fold), and malate dehydrogenase (mdh, 1.3-fold) indicated that the REcN strain was able to utilize carbon sources and produce energy (Fig. 2g and Supplementary Fig. 15).[36] Efficient energy production and utilization are essential for maintaining cellular homeostasis and coping with environmental challenges.[37] This metabolic flexibility may endow REcN with superior capacity to withstand oxidative stress.

Moreover, both EcN and REcN probiotic exhibited inhibitory effects on α-glucosidase (α-GC) (Fig. 2h), which can decelerate glucose absorption and thereby assist in reducing blood glucose levels.[38] Additionally, the probiotic demonstrated a pronounced inhibitory impact on α-amylase (α-AMS) (Fig. 2i), thereby diminishing starch degradation and subsequent glucose release.[39] Collectively, superior metabolic plasticity of REcN—integrating enhanced lipid catabolism, TCA cycle flux, and antioxidant networks—positions it as a multifaceted candidate for mitigating metabolic syndrome-associated dysregulation.

Surface engineering and gastrointestinal stability of REcN
To augment the gastrointestinal (GI) tract survivability and bioactivity of REcN, sequential surface modifications were implemented using fructooligosaccharide (FOS) prebiotics and calcium carbonate (CaCO3) mineralization. Transmission electron microscopy (TEM) imaging revealed a homogeneous electron-lucrent layer (a thickness of approximately 60 nm) encapsulating REcN cell (Fig. 3a-b and Supplementary Fig. 16, red arrow), confirming successful FOS polymerization (designated REcN-FOS). Subsequent CaCO3 mineralization generated a dense inorganic shell on REcN-FOS surfaces (Fig. 3c), with energy-dispersive X-ray spectroscopy (EDS) mapping demonstrating uniform Ca, C, and O distributions (Fig. 3c). Detection of nitrogen (N), a microbial biomass signature, confirmed bacterial structural integrity post-modification (designated REcN-FOS/CaCO3). X-ray diffraction (XRD) analysis confirmed the successful mineralization with CaCO₃, identifying the crystalline phase as calcite (Supplementary Fig. 17).

Subsequently, to rigorously evaluate the protective efficacy of the CaCO3 shell during sequential GI transit, we subjected the probiotic to a simulated journey from the stomach to the inflamed colon. Given the GI transit times, with rapid gastric emptying occurring within approximately 20 min, followed by small intestinal transit for about 2 h, and ultimately reaching the inflamed colon,[40] the viability and ROS-scavenging capacity of EcN, REcN, and REcN-FOS/CaCO3 were assessed after first incubation for 20 min in simulated gastric fluid (SGF), then incubation for 2 h in simulated intestinal fluid (SIF), and finally incubation for 2 h in simulated inflammatory colon fluid (SICF). After each sequential challenge, REcN demonstrated greater activity than EcN (Fig. 3d-f), likely due to its superior energy metabolism that enables it to better withstand GI environmental assaults. Notably, the modification with CaCO3 further enhanced the viability of the REcN probiotic, confirming the robust protective role of CaCO3 in the digestive tract. Importantly, after each sequential challenge, REcN-FOS/CaCO3 demonstrated the strongest •OH scavenging capacity (Fig. 3g), suggesting preserved bioactivity under GI stress. To determine the origin of the antioxidant activity, we compared •OH scavenging across different components. Live REcN demonstrated the highest capacity, significantly exceeding that of live EcN (Supplementary Fig. 18). The lysates of both strains also showed substantial activity, indicating that stable bacterial components contribute significantly. The FOS/CaCO3 material itself possessed a baseline scavenging ability, confirming that the overall effect of REcN-FOS/CaCO3 is a composite of the evolved superior intrinsic ability, its released components, and the coating matrix. To functionally validate the pH-responsive behavior, we quantified the dissolution kinetics of the CaCO3 shell. Inductively coupled plasma optical emission spectrometry (ICP-OES) analysis revealed a rapid release of Ca2+ ions in SGF (pH 1.2, ~50 mg L-1 after 20 min), contrasting with a slow, sustained release in SIF (pH 6.8, ~18 mg/L after 2 h) and SICF (pH 7.8, ~12 mg/L after 2 h) (Supplementary Fig. 19). This controlled dissolution in the upper GI tract ensures that a maximal payload of viable REcN is delivered to the target colonic environment.

Quantitative real-time PCR (qRT-PCR) analysis revealed a significant 2.7-fold upregulation of the anti-inflammatory cytokine IL-10 transcript concomitant with a suppression of pro-inflammatory IL-1β and Tnf-α expression in macrophage cultures exposed to engineered probiotic (Fig. 3h-j). Furthermore, the modified probiotic exhibited superior cytocompatibility and hemocompatibility (Supplementary Fig. 20).

To directly evaluate the gastrointestinal colonization capacity of the engineered probiotic, an ex vivo tracking experiment using Cy5.5-labeled strains was performed. Quantitative fluorescence imaging of intestinal tissues revealed that REcN-FOS/CaCO3 achieved the highest retention level among all groups (Fig. 3k,l). The FOS prebiotics improved the retention of both strains compared to their unencapsulated counterparts. Notably, the fluorescent signal of REcN-FOS/CaCO3 was significantly greater than that of EcN-FOS/CaCO3, indicating that the ROS-tolerant phenotype of REcN also enhanced gut colonization.

Amelioration of phenotypes in T2DM and obesity murine model
To establish causal links between REcN-FOS/CaCO3 (REcN-F/Ca) supplementation and metabolic improvement, a high-fat diet (HFD)-induced obesity murine model was employed. Compared to normolipidic diet (ND)-fed controls, HFD-fed mice developed pronounced obesity phenotypes, evidenced by elevated body weight gain (Δ+71.9% versus Δ+43.5%), peritesticular fat accumulation, and higher epididymal adipose tissue (eAT) weight (Fig. 4a-d). Additionally, the wild-type EcN probiotic encapsulated within the protective shell demonstrated a mitigating effect on obesity, which can be attributed to the action of the EcN probiotic. The F/Ca shell showed a negligible inhibitory effect on obesity. However, oral administration of REcN-F/Ca during HFD feeding mitigated obesity development, as evidenced by reduced body weight gain and fat accumulation compared to HFD-fed mice that did not receive supplementation (Fig. 4a-d).

Metabolic profiling revealed HFD-driven hyperglycemia and insulin resistance, both ameliorated by REcN-F/Ca (Fig. 4e). During intraperitoneal glucose tolerance testing (IPGTT), ND-fed mice exhibited transient increases in blood insulin levels following intraperitoneal glucose injection, with a rapid return to baseline (Fig . 4f). In contrast, HFD-fed mice exhibited a significant decline in blood insulin levels following the glucose challenge (Fig. 4f). This pattern is indicative of failure to mount an appropriate secretory response, a hallmark of T2DM pathology, rather than mere insulin resistance.[41] On the contrary, in mice fed with F/Ca, the blood insulin levels continued to rise after glucose injection, which is a typical characteristic of insulin resistance. This minor improvement was metabolically insufficient, as evidenced by the poor overall glucose tolerance and high HOMA-IR, which remained comparable to the HFD group. However, HFD-fed mice supplemented with REcN-F/Ca demonstrated insulin responses comparable to those of ND-fed mice (Fig. 4f). Consistent with these observations, the increases in blood glucose levels following intraperitoneal glucose injection in HFD-fed mice were normalized to levels similar to those of ND-fed mice when supplemented with REcN-F/Ca (Fig. 4g).

Inflammation within the eAT is known to contribute to the development of obesity-induced diabetes.[41] Histopathological evaluation of eAT in HFD and HFD+F/Ca groups revealed M1 macrophage infiltration (Fig. 4h), a hallmark of obesity-associated adipose inflammation. In line with the inhibitory effects of REcN on diabetes pathogenesis, the eAT of HFD-fed mice supplemented with REcN-F/Ca exhibited minimal macrophage accumulation (Fig. 4h). The administration of REcN significantly also reduced the number of lipid droplets infiltrating the eAT of HFD-fed mice (Fig. 4i,j). Additionally, RT-qPCR analysis indicated that the expression of S100a8 and Tnfα (Fig. 4k,l), which encode a chemokine that recruits macrophages and an inflammatory cytokine, respectively, was downregulated in the mature adipocyte fraction of the eAT in HFD-fed mice supplemented with REcN-F/Ca. Therefore, the administration of REcN-F/Ca not only inhibited body weight gain but also attenuated inflammatory responses in the eAT of HFD-fed mice.

Notably, colonic Pparα expression was upregulated in REcN-F/Ca-treated HFD mice versus ND mice (Fig. 4m). As a nuclear receptor regulating lipid oxidation and anti-inflammatory pathways, PPARα activation may mechanistically link metabolic benefits of REcN to transcriptional reprogramming of host energy utilization and inflammatory responses. Owing to the superior antioxidant capacity of REcN, the colon tissues after therapy showed the least oxidative stress (Fig. 4n,o). Furthermore, histopathological analysis via hematoxylin and eosin (H&E) staining demonstrated distinct hepatic morphological alterations across experimental cohorts. The ND group maintained intact hepatic lobular architecture with characteristic radial hepatocyte arrangement around central veins (Supplementary Fig. 21). Conversely, HFD group exhibited pronounced microvesicular and macrovesicular steatosis, accompanied by hepatocyte ballooning degeneration. Notably, REcN-F/Ca intervention substantially attenuated HFD-induced hepatosteatosis. Critical extrahepatic organs (heart, spleen, lung, and kidney) displayed preserved histoarchitectural integrity across all groups, suggesting absence of multiorgan toxicity after REcN-F/Ca treatment.

PPAR signaling pathway mediated lipid metabolism
To delineate the molecular mechanisms underlying the metabolic improvements conferred by REcN in obesity and T2DM, transcriptomic profiling of colonic tissues was conducted post-treatment. GO enrichment analysis revealed that REcN probiotic treatment significantly enhanced the capacity of colonic tissue for lipid and fatty acid metabolism and catabolism (Fig. 5a and Supplementary Fig. 22). The KEGG enrichment chord diagram further validated enhanced fatty acid degradation (ko00071) and fat digestion/absorption (ko04975), alongside upregulated steroid hormone biosynthesis (ko00140), pentose-glucuronate interconversions (ko00040), and glycerolipid metabolism (ko00561) (Fig. 5b). Glucocorticoids, which are part of the steroid hormone biosynthesis pathway, can maintain blood glucose stability by inhibiting glucose utilization and promoting lipolysis. They also possess potent anti-inflammatory and immunosuppressive properties, commonly utilized in the treatment of autoimmune diseases.[42] The pentose and glucuronate interconversions pathway is not only involved in energy production but also in the synthesis of NADPH,[43] which is crucial for enhancing antioxidant capacity of the colonic tissue. Modulation of glycerolipid metabolism can improve insulin sensitivity and lower blood glucose levels,[44] thereby aiding in diabetes management. Transcriptomic profiling revealed significant downregulation of key pro-inflammatory signaling cascades following REcN-F/Ca intervention, including IL-17 signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway (Supplementary Fig. 23). These findings position REcN-F/Ca as a promising immunomodulatory biotherapeutic for inflammation-driven T2DM, where chronic low-grade inflammation perpetuates insulin resistance and ectopic lipid accumulation.

Notably, the PPAR signaling pathway (ko03320) was also significantly enriched and upregulated (Fig. 5b). The PPAR signaling pathway emerged as a central regulatory node and coordinated with adipocytokine signaling pathway in energy metabolism and inflammatory responses. Moreover, several key genes, including Slc27a4, Fabp1, Fabp6, Apoa1, Apoa5, Lpl, Ehhadh, Acaa1b, Acox2, and Cpt1b, were significantly upregulated (Fig. 5c-l), thereby enhancing lipid transport, fatty acid transport, fatty acid oxidation, and ultimately lipid metabolism in colonic tissues following probiotic treatment (Fig. 5m and Supplementary Fig. 24). This transcriptional reprogramming establishes a metabolic network favoring lipid mobilization over storage (Fig. 5m), potentially mediated by PPARα-driven crosstalk with adipocytokine signaling pathways to enhance insulin sensitivity and mitigate inflammation.

To establish a causal role for the PPARα pathway, we pharmacologically inhibited PPARα signaling in REcN-F/Ca-treated mice using the antagonist GW6471. The intervention largely abolished the metabolic benefits conferred by REcN-F/Ca. Specifically, we observed a significant rebound in body weight, eAT weight, HOMA-IR index, and a marked deterioration in both insulin secretion and blood glucose levels during tolerance tests (Supplementary Fig. 25). The metabolic profile of this group reverted to a state closely resembling that of the HFD control group, demonstrating that the host PPARα pathway is indispensable for the metabolic remediation by REcN-F/Ca.

Modulation of gut microbiome
Given the well-documented ability of probiotic to modulate the gut microbiota and confer beneficial effects on the host,[40] fecal samples from each group were subjected to 16S rRNA gene sequencing after 10 weeks of intervention. Alpha diversity analysis revealed significant reductions in microbial richness (Observed species [Sobs] index: HFD 94 ± 34 versus ND 350 ± 99; Abundance-based coverage estimator [Ace] index: HFD 111 ± 41 versus ND 383 ± 96) and diversity (Shannon index: HFD 1.8 ± 0.3 versus ND 3.1 ± 0.9) in HFD-fed mice, which were partially restored by REcN-F/Ca treatment (Sobs index: 212 ± 22; Ace index: 238 ± 23; Shannon index: 2.8 ± 0.2) (Fig. 6a-c). The Chao index, Simpson index, and Shannon index all indicated that HFD-fed reduced the richness and diversity of the gut microbiota, while REcN probiotic treatment can restore the disrupted intestinal microbiota (Supplementary Fig. 26), suggesting that this bioengineered probiotic can help restore a healthier gut microbiota composition.[14] Furthermore, Beta diversity analysis via principal component analysis (PCA) demonstrated distinct clustering of gut microbiota communities among ND, HFD, and HFD+REcN-F/Ca groups (ANOSIM R = 0.2569, p = 0.014; Fig. 6d), with hierarchical clustering and NMDS further confirming compositional divergence (Supplementary Fig. 27). This change is likely due to the beneficial effects of the engineered probiotic, which can modulate the gut microbiota to promote health.

Taxonomic profiling at the family and genus levels identified REcN-F/Ca-driven enrichment of Lachnospiraceae (ND: HFD: HFD+REcN-F/Ca = 13.14%: 4.26%: 32.15%) (Fig. 6e and Supplementary Fig. 28), negatively correlated with systemic inflammation in T2DM.[45,46] Lachnospiraceae is associated with butyric acid production, promoting the growth of host epithelial cells. Conversely, pro-inflammatory Streptococcaceae abundance was reduced after REcN-F/Ca treatment (HFD 3.68% versus HFD+REcN-F/Ca 0.04%). Linear discriminant analysis (LDA) effect size (LEfSe) analysis highlighted Lachnospiraceae (LDA score = 4.88) and Blautia (LDA = 4.18) as signature taxa enriched in REcN-F/Ca-treated mice (Fig. 6f-h and Supplementary Fig. 29). The recent study identified that the reduction of Blautia luti and Blautia wexlerae is associated with insulin resistance in obese individuals.[41,47] Blautia prevents pathogen colonization through the production of bacteriocins and exhibit anti-inflammatory properties and glucose homeostasis maintenance by upregulating the production of short-chain fatty acids (SCFAs).[41] We also observed the specific enrichment of the [Eubacterium]_coprostanoligenes_group in the REcN-F/Ca group (Supplementary Fig. 30). These taxa are associated with butyrate production, pathogen exclusion via bacteriocins, and immunomodulation.[41,45-48]

Given the critical role of SCFAs in maintaining gut barrier integrity, systemic metabolic homeostasis, and neuroendocrine signaling, we quantified fecal SCFAs levels across experimental groups. HFD-fed mice exhibited significant reductions in acetic acid (ND: 1.46 ± 0.51 versus HFD: 0.21 ± 0.13 μg mg-1), propionic acid (ND: 0.29 ± 0.04 versus HFD: 0.04 ± 0.03 μg mg-1), butanoic acid (ND: 0.15 ± 0.07 versus HFD: 0.011 ± 0.004 μg mg-1), and isobutyric acid (ND: 0.023 ± 0.008 versus HFD: 0.007 ± 0.006 μg mg-1) compared to ND control (Fig. 6i-l). REcN-F/Ca intervention restored SCFAs concentrations to the ND-equivalent levels (acetic acid: 1.45 ± 0.26 μg mg-1; propionic acid: 0.19 ± 0.07 μg mg-1; butanoic acid: 0.21 ± 0.05 μg mg-1; isobutyric acid: 0.027 ± 0.008 μg mg-1), concomitant with the observed enrichment of SCFAs (especially for butyrate-producing taxa (Lachnospiraceae, Blautia, and [Eubacterium]_coprostanoligenes_group).

This HFD-induced SCFAs depletion aligns with gut dysbiosis characterized by reduced microbial diversity and diminished beneficial taxa. REcN-F/Ca treatment partially restores microbiota diversity and abundance of beneficial bacteria, suggesting a potential therapeutic role in modulating gut health. The increase in Blautia and Lachnospiraceae, along with the restoration in SCFAs levels, suggests improved gut function and metabolic health.

Methods
Research ethics statement
The animal experiments investigating the therapeutic effects on high-fat diet-induced type 2 diabetes were conducted with approval from the Institutional Animal Care and Use Committee of the Beatcell Model Biological Center (Approval No. 2025-07-31A). All animal procedures were performed in strict compliance with the “Animal Management Regulations of the Ministry of Health of the People’s Republic of China” and the “Guidelines for the Care and Use of Laboratory Animals (Chinese version)”.

Chemicals
All chemical reagents were of analytical grade or higher purity. Hydrogen peroxide, glycerol, norepinephrine, fructooligosaccharides, calcium chloride, sodium carbonate, 3-isobutyl-1-methylxanthine, dexamethasone, insulin, paraformaldehyde, lead(II) acetate, and dimethylformamide were procured from Aladdin Regents. Acetonitrile, methanol, isopropanol, and formic acid were obtained from Fisher Scientific. Molecular biology reagents comprised PrimeScript RT Master Mix (Takara Bio, #RR036A), TB Green Premix Ex Taq II (Takara Bio, #RR820A), TransStart FastPfu DNA Polymerase (TransGen Biotech, #AP221-01), and dNTP mixtures (Beyotime, #D7371). Commercial kits included: Total Superoxide Dismutase Assay Kit (Beyotime, #S0101S), α-Amylase Assay Kit (Shanghaiyuanye, #S31302), α-Glucosidase Activity Assay Kit (Solarbio, # BC2550), Total RNA Kit (Omega Bio-tek, #R6834), FastPure Microbiome DNA Isolation Kit (Vazyme, #DC502-01), NEXTFLEX Rapid DNA-Seq Kit (Bioo Scientific, #5144-03).

Bacterial strains and cultivation
The wild-type Escherichia coli Nissle 1917 (EcN) was obtained from BeNa Culture Colletion Co., Ltd (Beijing, China). The strain was routinely cultured in Luria-Bertani (LB) broth at 37 °C with shaking. For all experiments, after overnight growth, the bacterial strain was transferred to fresh media and permitted to propagate until they reached the exponential phase. A 1,000-fold dilution was subsequently conducted using the LB broth, resulting in a suspension with approximately 106 colony-forming units (CFU) per milliliter for subsequent experimental procedures. Stock solutions of each microbial passage were prepared in the LB broth, supplemented with 25% glycerol, and stored at -80 °C for long-term preservation.

Selection of ROS-resistant strain
The initial antimicrobial efficacy of ROS, specifically H2O2, was evaluated through standard planktonic minimum inhibitory concentration (MIC) assays. These experiments were performed in triplicate utilizing 96-well microplates. A volume of 100 µL of H2O2 solution was serially diluted in bacterial broth and inoculated with 100 µL of bacterial suspensions (1 × 106 CFU mL-1), resulting in a total well volume of 200 µL. The final tested concentrations of H2O2 ranged from 15% to the twenty-third half-dilution. The mixtures were incubated at 37 °C for 24 h in a shaking incubator.

To investigate the evolution of resistance, bacteria were subjected to repeated exposure to ROS over 10 successive passages. A wild-type (WT) bacterial parent strain was prepared and inoculated into a serially diluted series of H2O2. The MIC was defined as the lowest concentration of the antimicrobial agent that inhibited visible microbial growth after 24 h. Sub-MIC cultures (the first three wells below the MIC) containing surviving bacteria were collected and diluted 100,000-fold. A volume of 20 µL of the diluted bacterial solution was then subcultured on agar at 37 °C for 24 h. A single colony was selected for inoculum preparation at a density of 1 × 106 CFU mL-1 for the subsequent passage, where the bacteria were exposed to a new series of diluted H2O2. The entire procedure, from initial inoculation to the preparation of the new inoculum, was repeated for up to 10 passages, and the MICs at each passage were recorded. Finally, the tenth passage of probiotic was selected and named ROS-resistant EcN (REcN).

The fold increase in the MIC was calculated using the following equation (1):
MIC fold change = MIC experimental passage N / MIC WT experimental Equation (1)
where “experimental” denotes each passage with antimicrobial exposure (e.g., passage 5 represents 5 passages of antimicrobial exposure).

RNA sequencing analysis
The experimental protocol utilized the TruSeqTM Stranded Total RNA Library Prep Kit for library construction. During the synthesis of the second cDNA strand, dTTP in the dNTP mixture was substituted with dUTP, leading to the incorporation of A/U/C/G bases into the second cDNA strand. Subsequently, the second cDNA strand was enzymatically degraded using uracil-DNA glycosylase (UNG) prior to PCR amplification, ensuring that the library exclusively contained the first cDNA strand. The detailed procedures are as follows:

a) Total RNA extraction: Total RNA was isolated from EcN and REcN samples. The concentration and purity of the extracted RNA were determined using a Nanodrop2000 spectrophotometer. RNA integrity was assessed via agarose gel electrophoresis, and the RNA Integrity Number (RIN) was measured using an Agilent 2100 Bioanalyzer. For library construction, each sample required a total RNA amount of 2 µg, with a concentration of ≥ 100 ng µL-1 and an OD 260/280 ratio ranging from 1.8 to 2.2.

b) rRNA removal: Unlike eukaryotic mRNA, prokaryotic mRNA lacks a polyA tail at the 3' end, precluding the separation of mRNA from total RNA through A-T base pairing with Oligo dT. Therefore, rRNA removal was employed for transcriptome analysis.

c) mRNA fragmentation: The Illumina platform sequences short fragments, whereas the enriched mRNA consists of full-length RNA sequences with an average length of several kilobases. Thus, mRNA must be randomly fragmented. The addition of a fragmentation buffer enables the random breakage of mRNA into approximately 200 bp fragments.

d) cDNA synthesis via reverse transcription: Under the action of reverse transcriptase and using random primers, the mRNA template was used to synthesize the first cDNA strand. During the second-strand synthesis, dUTP was used in place of dTTP in the dNTP mixture, resulting in the incorporation of A/U/C/G bases into the second cDNA strand.

e) Adaptor ligation: The double-stranded cDNA structure has sticky ends. The End Repair Mix was added to blunt the ends, after which an A base was added to the 3' end to facilitate the connection of the Y-shaped adaptor.

f) Digestion of the second cDNA strand with UNG enzyme: Prior to PCR amplification, the second cDNA strand was digested using the UNG enzyme, ensuring that the library exclusively contained the first cDNA strand.

g) Illumina HiSeq sequencing: 1) The library was enriched and amplified via PCR for 15 cycles; 2) The library was quantified using TBS380 (Picogreen), and samples were pooled according to data proportions for sequencing; 3) Bridge PCR amplification was performed on the cBot to generate clusters; 4) Sequencing was conducted on the Illumina HiSeq platform, generating 2 × 150 bp or 300 bp reads.

Whole-genome sequencing and SNPs/InDels analysis
a) Genomic DNA extraction: The bacterial strains (EcN and REcN) were inoculated onto an LB agar plate and incubated overnight at 37 °C. A single colony was picked with an inoculation needle and transferred into 200 mL of LB liquid medium, followed by incubation at 37 °C with shaking until the logarithmic growth phase was reached. The bacterial pellet was collected by refrigerated centrifugation and washed with sterile water to remove residual medium components. Genomic DNA was extracted and quantified, and high-quality DNA was used for subsequent library construction.

b) Library construction and genome sequencing: Sequencing library was prepared using the Illumina platform. Genomic DNA was fragmented to approximately 400 bp using a Covaris M220 Focused‑Acoustic Shearer. Library construction was performed with the NEXTFLEX Rapid DNA‑Seq Kit. Adapter‑ligated fragments were enriched by PCR. The final library was subjected to paired‑end sequencing (2 × 150 bp) on an Illumina NovaSeq 6000.

c) Sequencing data quality control: Initially, adapter sequences were removed from the reads. The 5’ ends of reads were then trimmed to eliminate any bases that were not A, G, C, or T. Next, read ends with low sequencing quality (Phred score ≤ Q20) were trimmed. Furthermore, reads containing more than 10% undetermined bases (N) were filtered out. Finally, fragments shorter than 30 bp after adapter removal and quality trimming were discarded.

d) Read mapping: Clean reads were aligned to a designated reference genome using the BWA‑MEM algorithm. PCR duplicates were identified and removed with Picard‑tools. Sequencing depth and genome coverage were calculated from the resulting BAM alignment files.

e) SNP and InDel analysis: SNPs/InDels were detected using a standardized variant‑calling pipeline. Initially, local realignment around InDel regions was performed with GATK v4.3.0.0 to reduce false‑positive SNP calls. Variant calling was then carried out with Snippy v4.6.0, applying filters for minimum sequencing depth and mapping quality. Detected variants were functionally annotated using SnpEff to predict their potential effects on coding and regulatory regions.

H2S detection
The classic lead acetate reactivity test has historically been employed to detect the presence of H2S. For this test, an appropriate quantity of lead(II) acetate was dissolved in distilled water to prepare a 2% lead acetate solution. A piece of filter paper was cut and immersed in the lead acetate solution until fully saturated. The paper was then carefully removed from the solution and positioned over the surface of a 12-well plate containing bacterial suspensions, and the bacteria were incubated at 37 °C for 24 h. Following incubation, the color change of the filter paper was meticulously observed. Subsequently, the WSP5 H2S-nucleophilic substitution-cyclization-based fluorescent probe was utilized to detect by inverted fluorescence microscope (IFM, IX73, Olympus).

Superoxide dismutase and catalase activities tests of REcN
The SOD-like activity of REcN was evaluated using the Total Superoxide Dismutase Kit with WST-8. The optical density at 450 nm (OD450) was measured using a microplate reader (SpectraMax i3, Molecular Devices, San Francisco, CA, USA). The CAT-like activity of REcN was assessed using a dissolved oxygen meter. REcN and H2O2 (10 mM) were added to 20 mL of phosphate-buffered saline (PBS) under magnetic stirring. The concentration of dissolved oxygen was measured at 1-min intervals for a total duration of 10 min.

α-amylase and α-glucosidase inhibition experiments
The α-amylase activity inhibition of probiotic was detected using the α-Amylase Kit. The optical density at 540 nm (OD540) was measured using a microplate reader. The inhibition of α-glucosidase was evaluated by monitoring the decomposition of p-nitrophenyl-α-D-glucopyranoside to p-nitrophenol using α-Gucosidase Activity Assay Kit. The optical density at 400 nm (OD400) was measured using a microplate reader.

NADH dehydrogenase activity assay
NADH dehydrogenase activity was assessed by monitoring the oxidation of NADH. Briefly, EcN and REcN (1×108 CFU mL-1) were incubated with 20 µM NADH solution. The reaction mixture was incubated at 37 oC for 30 min, and the absorbance at 340 nm was measured using a microplate reader at the start and end of the incubation period. The decrease in absorbance was used as an indicator of NADH dehydrogenase activity.

Outer membrane permeability assay
Outer membrane permeability was assessed using the fluorescent probe 8-anilino-1-naphthalenesulfonic acid (ANS). Briefly, EcN and REcN (1×105 CFU mL-1) cells were harvested, washed, and resuspended in PBS. ANS was added to a final concentration of 10 µM, and after incubation, fluorescence intensity was measured (excitation 370 nm, emission 450-600 nm) using a microplate reader (SpectraMax i3, MolecularDevices).

3T3L1 adipocytes and oil red O staining
3T3-L1 preadipocytes (ATCC CL-173) were commercially procured from Wuhan Pricella Biotechnology Co., Ltd. (Wuhan, China). Adipocyte differentiation was initiating performed with the seeding of 4×104 cells per well in 12-well plates. Cultures were maintained overnight in DMEM supplemented with 10% (v/v) neonatal bovine serum under standardized conditions (37 °C, 5% CO2). The medium was replaced with DMEM containing 10% (v/v) fetal bovine serum (FBS) for a 72-h growth-arrest phase. Subsequently, cells underwent terminal differentiation through sequential exposure to induction cocktail (0.5 mM 3-isobutyl-1-methylxanthine, 1 μM dexamethasone, and 10 μg mL-1 insulin in 10% FBS/DMEM) for 48 h, followed by 144-h maturation in maintenance medium (10% FBS/DMEM) with medium renewal at 72-h intervals.

Experimental intervention consisting of 10% (v/v) probiotic-conditioned medium was administered throughout the differentiation regimen.

Quantification of intracellular lipid accumulation employed a validated spectrophotometric protocol. Differentiated adipocyte monolayers underwent PBS rinsing prior to fixation with 4% paraformaldehyde/PBS (37 °C, 30 min). Fixed cells were were stained with Oil Red O for 30 min at ambient temperature, protected from light. After staining, the samples were destained with PBS until a clear background was achieved. Bright-field images were then acquired to visualize lipid deposition by inverted fluorescence microscope (IFM, IX73, Olympus). For quantitative analysis, the lipid-bound dye was solubilized by adding 500 µL of isopropanol per well. An aliquot of 200 µL from each sample was transferred to a 96-well plate, and absorbance was measured at 490 nm using a microplate reader (SpectraMax i3, MolecularDevices).

Surface modification with fructooligosaccharide
A 20 µL volume of REcN was inoculated into 30 mL of LB broth for 24 h. Following centrifugation at 2,400 × g for 5 min at 4 °C, REcN was isolated from LB broth. Subsequently, REcN was resuspended in a norepinephrine (NE, 2 mL, 1 mg mL-1) solution and incubated on a shaker for 1 h. After another round of centrifugation at 2,400 × g for 5 min at 4 °C, the fructooligosaccharide (FOS, 2 mL, 10 mg mL-1) solution was added, and the mixture was incubated on a shaker for an additional hour to obtain REcN-FOS.

Calcium carbonate encapsulation
A solution of calcium chloride (CaCl2, 0.2 mL, 0.33 mM) was then to the probiotic suspension, and the mixture was incubated on a shaker for 20 min. An equal volume of sodium carbonate (Na2CO3, 0.33 mM) solution was subsequently added to the homogeneous mixture, followed by further incubation on a shaker for 1 h. The probiotic precipitate was collected by centrifugation at 2,400 × g for 5 min at 4 °C. Finally, the probiotic precipitate was washed with PBS to obtain REcN-FOS/CaCO3 (REcN-F/Ca). The morphologies of probiotic were observed by the transmission electron microscopy (Fisher Talos F200X G2, Thermo Scientific, Waltham, MA, USA).

Viability of REcN-FOS/CaCO3 in the inflamed colon
Probiotic (1×107 CFU mL-1) was first incubated in SGF (containing pepsin and HCl, pH 1.2) for 20 min, then the probiotic was collected, resuspended, and transferred to SIF (containing pancreatin in phosphate buffer, pH 6.8) for 2 h, followed by a final transfer to SICF (containing ammonium hydroxide, 200 μM H2O2 in phosphate buffer) for 2 h. incubated in 1 mL of medium supplemented with either SGF, SIF, or SICF. Viability (CFU count) was determined after each step.

In vitro •OH-scavenging activities of REcN-FOS/CaCO3
Probiotic (1×107 CFU mL-1) was incubated in 1 mL of medium supplemented with either SGF, SIF, or SICF. The incubation was conducted at 37 °C (SGF for 20 min, SIF for 2 h, and SICF for 2 h) with gentle shaking to evaluate their stabilities in the GI environment. •OH was generated by co-incubating FeSO4 (0.4 mM) and H2O2 (10 mM) for 20 mins. A 100 μL aliquot of the treated probiotic was added to 100 μL of the above mixture for 10 min. DMPO (2 μL) was then added to the mixture for 2 min. The mixture was drawn into a capillary tube, and •OH scavenging was detected using electron spin resonance (ESR) (Magnettech ESR5000, Bruker, Billerica, MA, USA).

Degradation of CaCO3 shell
REcN-FOS/CaCO3 (1×108 CFU mL-1) was incubated in 2 mL of medium supplemented with either SGF, SIF, or SICF. The incubation was conducted at 37 °C (SGF for 20 min, SIF for 2 h, and SICF for 2 h) with gentle shaking to evaluate their stabilities in the GI environment. The dissolution profile of the CaCO3 shell was characterized by measuring the concentration of released Ca ions in SGF, SIF, and SICF over time using inductively coupled plasma optical emission spectrometry (ICP-OES).

Intestinal colonization test
Freshly prepared Cy5.5 dye (10 mg mL-1) was slowly added to probiotic suspensions (108 CFU mL-1). The mixtures were incubated at 37 oC for 2 h in the dark with gentle shaking, followed by repeated PBS washes until the supernatant was clear. The labeled probiotic was then collected, and the FOS/CaCO3 encapsulation was performed on Cy5.5-labeled EcN and REcN to generate EcN-Cy5.5-FOS/CaCO3 and REcN-Cy5.5-FOS/CaCO3, respectively. Mice were orally gavaged with the preparations, and intestinal tissues were collected 6 h post-administration for ex vivo fluorescence imaging using an IVIS Lumina XRMS Series III system (PerkinElmer).

Hemolytic activity test
Hemocompatibility assessment was conducted through quantitative erythrocyte lysis analysis. Murine erythrocytes were isolated via refrigerated centrifugation (500 × g, 10 min, 4 °C) and reconstituted as 5% (v/v) isotonic suspension. Probiotic medium (1×108 CFU mL-1) was incubated with erythrocyte suspensions (1:1 v/v) under physiological conditions (37 °C, 4 h). Following secondary centrifugation (500 × g, 10 min), supernatant hemoglobin release was spectrophotometrically quantified at 540 nm using a microplate reader. Hemolytic indices were calculated relative to positive (deionized water) and negative (saline) controls, with < 5% hemolysis established as biocompatibility threshold.

Cell viability
Cytotoxicity profiling employed mitochondrial dehydrogenase activity quantification (MTT assay) in accordance with ISO 10993-5. RAW 264.7 macrophages were seeded at optimized densities (1 × 104 cells/well) in 96-well plates. After 24 h adherence, cultures were exposed to probiotic (1×108 CFU mL-1) for 1 day. MTT solution (0.5 mg mL-1 in PBS) was introduced for 4 h, followed by formazan crystal solubilization in dimethylformamide (200 μL, orbital shaking). Absorbance was measured at 490 nm using a microplate reader.

Quantitative PCR (RT-qPCR) analysis
RAW 264.7 (1×104 cells/well) was seeded in 6-well plates and received probiotic (1×108 CFU mL-1) exposure for 1 day. Total RNA was then extracted using a Total RNA Kit and quantify by a NanoDrop 2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA). Reverse transcription of 500 ng RNA employed PrimeScript RT Master Mix. Amplification reactions utilized TB Green Premix Ex Taq II on CFX Connect Real-Time System (Bio-Rad, Hercules, CA, USA) under standardized thermocycling: 95 °C/30 s, 40 cycles of 95 °C/5 s and 60 °C/30 s. Relative transcript quantification of IL-1β (F: 5'-TGTGACTCGTGGGATGATGAC-3', R: 5'-CCACTTGTTGGCTTATGTTCTGTC-3'), IL-10 (F: 5'-TGCTGCCTGCTCTTACTGACTG-3', R: 5'-ACTCCTGCATTAAGGAGTCGGT-3'), and Tnf-α (F: 5'-CGTCAGCCGATTTGCTATCT-3', R: 5'-CGTCAGCCGATTTGCTATCT-3') employed the comparative Ct method (2−ΔΔCt) normalized to β-actin reference gene (F: 5 '-GTGACGTTGACATCCGTAAAGA-3', R: 5'-GTAACAGTCCGCCTAGAAGCAC -3'). For each gene target, a standard curve was generated using serial dilutions of cDNA to confirm PCR amplification efficiency. All qPCR primers were designed using established sequences from the NCBI database and purchased from a commercial synthesis service (Pinuofei Biotechnology). All primer sets used had efficiencies between 90% and 110%, with correlation coefficients (R2) greater than 0.98, ensuring accurate quantification.

Longitudinal metabolic phenotyping in high-fat diet-induced obese murine model
Male C57BL/6J mice (n = 6, 6-week-old) were acclimatized in IVC cages under SPF conditions (22 ± 1 °C, 55% humidity, 12 h light-dark cycle) with autoclaved water and a standard feed. Following 2-week standard chow, mice underwent metabolic challenge via HFD for 10-week intervention, establishing a validated insulin-resistant prediabetic model. The animal study included six groups: 1) ND group, 2) HFD group, 3) HFD+F/Ca vehicle group, 4) HFD+EcN-F/Ca group, 5) HFD+EcN-F/Ca group, and HFD+EcN-F/Ca+GW6471 (PPARα signaling inhibitor) group. Pharmacokinetic-informed intervention consisting of 0.5 mL probiotic suspension (5 × 108 CFU mL-1) was administered via orogastric gavage thrice weekly (at 9:00 AM on Monday, Wednesday, and Friday). For HFD+EcN-F/Ca+GW6471 group, mice were treated with GW6471 (20 mg kg-1 in DMSO) by intraperitoneal injection after orogastric gavage. Weekly body weight measurements was recorded. At week 10, fasting blood samples acquired via tail venipuncture were processed for HOMA-IR calculation, while fecal pellets underwent immediate flash-freezing for SCFAs quantification and gut microbiome analysis. IPGTT was conducted involving intraperitoneal D-glucose (2g kg-1, 20% w/ v solution) with glycemic profiling at 0/30/60/90/120 min. Concurrent serum insulin dynamics were assessed using ELISA. Terminal procedures at week 10 employed cervical dislocation under isoflurane anesthesia (3% induction), with subsequent tissue harvest utilizing aseptic microdissection techniques. The F4/80, CD86, and BODIPY in eAT and the 8-OhdG in colon tissue were detected by immunofluorescence staining. And the main organs were stained by H&E.

RT-qPCR analysis for epididymal adipose and colon tissues
Fresh frozen tissue samples (~100 mg), stored at -80 °C, were retrieved. 1 mL of Trizol reagent was added, and the tissue was homogenized into a slurry using a homogenizer. The homogenate was transferred to a 1.5 mL RNase-free microcentrifuge tube and lysed for 10 min. Total RNA was extracted using a Total RNA Kit and quantify by a NanoDrop 2000 spectrophotometer. Reverse transcription of 500 ng RNA employed PrimeScript RT Master Mix. Amplification reactions utilized TB Green Premix Ex Taq II on CFX Connect Real-Time System under standardized thermocycling: 95 °C/30 s, 40 cycles of 95 °C/10 s and 60 °C/30 s. Relative transcript quantification of Tnf-α, S100a8, Pparα, Slc27a4, Fabp1, Fabp6, Apoa1, Apoa5, Lpl, Ehhadh, Acaa1b, Acox2, and Cpt1b employed the comparative Ct method (2−ΔΔCt) normalized to β-actin reference gene. For each gene target, a standard curve was generated using serial dilutions of cDNA to confirm PCR amplification efficiency. All qPCR primers were designed using established sequences from the NCBI database and purchased from a commercial synthesis service (Pinuofei Biotechnology) (Supplementary Table 1). All primer sets used had efficiencies between 90% and 110%, with correlation coefficients (R2) greater than 0.98, ensuring accurate quantification.

Quantification of short-chain fatty acids
a) Experimental design and replicates: Fecal samples for short-chain fatty acids quantification were collected at the study endpoint (week 10). The total number of samples analyzed was n = 18, corresponding to n = 6 biologically independent mice per group for the three primary cohorts: ND, HFD, and HFD+REcN-F/Ca. No samples were excluded from the analysis. A set of external calibration standards, processed identically to the samples, served as controls for quantification. Analyses were performed as single technical measurements per biological sample.

b) Preparation of SCFAs standard solutions: Accurately weigh 10 mg of each of the eight standard compounds and dissolve them in 50% acetonitrile aqueous solution to a final volume of 1 mL. Vortex the solution to ensure homogeneity, yielding a stock solution for each standard. Subsequently, mix 100 µL of each individual standard solution and dilute to 1 mL to obtain mixed standard stock solution A. Dilute mixed standard stock solution A by a factor of 50 to achieve a mixed standard stock solution B with a concentration of 20 µg mL-1. Pipette 40 µL of mixed standard stock solution B, add 20 µL of 200 mM 3-Nitrophenylhydrazine hydrochloride and 20 µL of 120 mM 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride solution (containing 6% pyridine). Both solvents are dissolved in 50% acetonitrile aqueous solution. Incubate the mixture at 40 °C for 30 min, then dilute to 200 µL with 50% acetonitrile aqueous solution and further dilute stepwise to working solutions L1-L14, which are then transferred into 1.5 mL Eppendorf (EP) tubes.

c) Sample preparation: Accurately weigh 20 mg of the fecal sample and add 500 µL of extraction solvent (methanol:water = 4:1). Homogenize the mixture in a cryogenic grinding mill for 6 min (-10 °C, 50 Hz), followed by low-temperature ultrasonication for 30 min (5 °C, 40 kHz). Allow the sample to stand at -20 °C for 30 min, then centrifuge at 13,000 × g for 15 min at 4 °C. Pipette 20 µL of the supernatant into a new tube and add 20 µL of 200 mM 3-Nitrophenylhydrazine hydrochloride and 20 µL of 120 mM 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride solution (containing 6% pyridine). Incubate the mixture at 40 °C for 30 min, then dilute to 1000 µL with 50% acetonitrile aqueous solution for subsequent LC-MS/MS analysis.

d) LC-MS/MS analysis: The LC-MS/MS analysis was performed using an ExionLC AD liquid chromatography system coupled with a QTRAP® 6500+ mass spectrometer (Shanghai Megi Biomedical Technology Co., Ltd.). A 2 µL sample was injected and separated on a BEH C18 column (150 × 2.1 mm, 1.7 µm) before entering the mass spectrometer for detection. The mobile phase A consisted of 0.1% formic acid in water, and mobile phase B consisted of 0.1% formic acid in acetonitrile. The gradient elution program was as follows: 0.0-2.0 min, mobile phase B held at 10%; 2.0-11.0 min, mobile phase B increased from 10% to 55%; 11.0-12.0 min, mobile phase B increased from 55% to 95%; 12.0-13.0 min, mobile phase B held at 95%; 13.0-13.1 min, mobile phase B decreased from 95% to 10%; 13.1-16.0 min, mobile phase B held at 10%. The flow rate was maintained at 0.35 mL min-1, and the column temperature was set at 40 °C. The mass spectrometer was operated in negative ion mode. The curtain gas was set at 35 psi, collision gas at Medium, ion source spray gas at 40 psi, auxiliary gas at 40 psi, spray voltage at -4500 V, and ion source temperature at 450 °C.

e) Quality control samples: QC samples, which are either pooled samples or mixed standard solutions with appropriate concentrations, are primarily used to evaluate the stability of the analytical system. During the instrumental analysis, one QC sample is inserted every 5-10 samples to assess the reproducibility of the entire analytical process. The stability RSD (relative standard deviation) of each analyte should be less than 15%.

f) Data processing: After the analysis, the raw LC-MS data were imported into the AB Sciex OS quantitative software. The software automatically identified and integrated each ion fragment using default parameters, with manual verification as needed. A linear regression calibration curve was constructed with the analyte peak area as the ordinate and the analyte concentration as the abscissa. The concentration of the analyte in the sample was calculated by substituting the analyte peak area into the linear equation.

Intestinal microbiome analysis
a) DNA extraction from samples: Genomic DNA was extracted from fecal samples of individuals in the disease and healthy groups using the FastPure Microbiome DNA Isolation Kit according to the manufacturer's instructions. The integrity of the extracted genomic DNA was assessed by 1% agarose gel electrophoresis. DNA concentration and purity were measured using a NanoDrop 2000 spectrophotometer.

b) PCR amplification and sequencing library construction: Using the extracted DNA as a template, the V3-V4 hypervariable region of the 16S rRNA gene was amplified by PCR with barcoded primers 338F (5’-ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’). The PCR reaction mixture consisted of 4 μL of 5× TransStart FastPfu buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of TransStart FastPfu DNA polymerase, 10 ng of template DNA, and water to a final volume of 20 μL. The amplification program was as follows: initial denaturation at 95 °C for 3 min, followed by 27 cycles of denaturation at 95 °C for 30 seconds, annealing at 55 °C for 30 seconds, and extension at 72 °C for 30 seconds, with a final extension at 72 °C for 10 min and storage at 4 °C (PCR instrument: T100 Thermal Cycler). Each sample was amplified in triplicate. The PCR products from the same sample were pooled and purified using 2% agarose gel electrophoresis to verify the fragment size. The purified PCR products were quantified using a Synergy HTX microplate reader (BioTek, USA). The NEXTFLEX Rapid DNA-Seq Kit was used to construct the sequencing library: (1) adapter ligation; (2) magnetic bead selection to remove adapter dimers; (3) PCR amplification to enrich the library template; and (4) magnetic bead purification of the PCR products to obtain the final library. Sequencing was performed on the Illumina NextSeq 2000 PE300 platform.

c) High-throughput sequencing data analysis: The raw paired-end sequencing reads were quality-controlled using fastp (version 0.19.6) and merged using FLASH (version 1.2.11). The quality control process included: (1) filtering bases with a quality score below 20 at the tail of reads, using a 50 bp sliding window to trim bases if the average quality score within the window was less than 20; (2) discarding reads shorter than 50 bp after quality control and reads containing N bases; (3) merging paired-end reads based on their overlap, with a minimum overlap length of 10 bp; (4) allowing a maximum mismatch rate of 0.2 in the overlap region and filtering out non-conforming sequences; and (5) demultiplexing samples based on barcodes and primers at the ends of the sequences, with zero mismatches allowed for barcodes and up to two mismatches for primers. USEARCH (version 11) was used to cluster the quality-controlled and merged sequences into operational taxonomic units (OTUs) at a similarity threshold of 97% and to remove chimeric sequences. Chloroplast and mitochondrial sequences were removed from all samples. To minimize the impact of sequencing depth on subsequent alpha and beta diversity analyses, all samples were rarefied to 20,000 sequences. After rarefaction, the average sequence coverage (Good’s coverage) for each sample remained at 99.09%. The RDP Classifier (version 2.13) was used to annotate the taxonomic classification of OTUs against the Silva 16S rRNA gene database (v138), with a confidence threshold of 70%, and the community composition of each sample was analyzed at different taxonomic levels. PICRUSt2 (version 2.2.0) was used for 16S functional prediction analysis.

Statistics and reproducibility
The data from all experiments were presented as mean values ± standard deviations (SD), with a minimum of three independent replicates (n≥3). Statistical analyses were performed using GraphPad Prism software. A one-way analysis of variance (ANOVA) was conducted, followed by Tukey's multiple comparisons test for comparisons among multiple groups and a two-sample Student's two-sided t-test for comparisons between two groups. Mann-Whitney test was employed to analyze inter-group differences in alpha diversity. ANOSIM non-parametric test was applied to determine significant differences in microbial community structures between sample groups. Exact p-values were shown or the levels of statistical significance was set as p < 0.0001 (****) with 95% confidence interval. LEfSe analysis (LDA > 3, p < 0.05) was used to identify bacterial taxa with significant abundance differences between groups at the phylum to genus levels.

Data availability
The RNA-seq data generated in this study are available on the National Center for Biotechnology Information (NCBI) database under the BioProject PRJNA1283478 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1283478). The WGS data are available at the China National Center for Bioinformation (CNCB) accession CRA038952 (https://ngdc.cncb.ac.cn/gsa/browse/CRA038952), and the SNPs analysis are available on Supplementary Data 1 and Supplementary Data 2. The mass spectrometry data are available on Supplementary Data 3. All relevant data that support the findings of this study are available within the Article and Supplementary Information or from the corresponding author upon reasonable request. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Type 2 diabetes mellitus (T2DM) is primarily characterized by cellular insulin resistance. Although pharmacological\ninterventions such as PPAR agonists and GLP-1 analogs can alleviate symptoms, they fail to address gut microbiota\ndysbiosis, which remains a core issue in metabolic dysfunction. Probiotic-based strategies hold promises in this area, but\nconventional probiotics often exit poor persistence in the gut or lack sufficient metabolic diversity to counteract the host’s\npathologies and other process.\nEscherichia coli Nissle 1917 (EcN) is a probiotic with known potential to alleviate colitis through competitive exclusion and\nbiofilm formation. However, under inflamed intestinal conditions, particularly under high ROS microenvironments of\ndiabetes, EcN’s limited antioxidant capacity hinders its colonization efficacy. To address this, the authors evolved EcN in\nH2O2-containing medium, generating a more robust strain, REcN. This was subsequently surface-modified with\nfructooligosaccharide (FOS) and encapsulated by calcium carbonate, resulting in REcN-F/Ca.\nIn high-fat diet (HFD)-induced obese mice, REcN-F/Ca restored gut microbiota diversity, enriched butyrate-producing taxa,\nand alleviated short-chain fatty acid deficiency. Transcriptomic analysis of colonic tissues showed activation of the PPAR\nsignaling pathway, promoting lipid metabolism and suppressing adipose inflammation. These effects collectively improved\nsystemic metabolism in obese and T2DM murine model, including a 25.1% reduction in weight gain, restoration of glucose\nhomeostasis, and lowered insulin resistance. The authors propose that this engineered and modified probiotic represents a\nnovel pharmabiotic strategy for managing metabolic syndrome.\nMajor:\n1. This manuscript employs FOS modification and calcium carbonate mineralization, yet does not provide a clear but\nexplanation of their underlying mechanisms or rationale. Moreover, the choice of FOS and calcium carbonate over\nalternative materials is not justified. This weakens the theoretical basis of the methodology. The authors are encouraged to\ndiscuss the rationale behind these choices and consider whether other probiotic strains (besides EcN) could be similarly\nengineered to achieve or better therapeutic effects.\n2. Critical comparisons between native EcN, FOS-modified EcN, calcium carbonate-encapsulated EcN, and REcN-F/Ca are\nmissing. These comparisons are essential to evaluate the incremental contributions of each modification step. Without such\ndata, it is difficult to assess whether evolutionary adaptation is necessary, thereby weakening the study’s overall\nconclusions.\n3. The study lacks whole-genome sequencing and comparative analysis of the evolved REcN strain. Such analyses are\ncritical to identify mutations underlying enhanced ROS tolerance and to elucidate the genetic basis of the observed\nphenotypic improvements. This omission limits mechanistic insight and weakens the scientific depth of the study.\n4. In Line 233-237, the authors state that “Notably, the modification with CaCO₃ further enhanced the viability of the REcN\nprobiotics, confirming the robust protective role of CaCO₃ in the digestive tract. Interestingly, in SIF, REcN probiotics not\nprotected by CaCO₃ appeared to show higher viability (Fig. 3e), possibly because the acidity of SIF may insufficiently\nsolubilize the mineralized shell to fully release encapsulated bacteria”. The authors report that calcium carbonate\nmodification enhances REcN viability, confirming its protective effect. However, in SIF, unencapsulated REcN shows higher\nviability, possibly due to incomplete calcium carbonate shell dissolution. This contradictory finding undermines the\nprotective claim. The authors should clarify the physiological relevance of the SIF data and reconcile the inconsistency with\nthe broader narrative.\n5. Despite acknowledging that native EcN fails to persistently colonize inflamed gut environments, the authors did not\nassess whether REcN or REcN-F/Ca demonstrates improved colonization. This is a key functional endpoint and should be\nexperimentally validated.\nMinor:\n1. Sequencing results are not available now.\n2. Line 48-51: The references 5-7 do not support the claim that “failure to address gut microbiotadysbiosis”. Moreover,\nreference 6 only briefly mentions side effects of GLP-1. The authors should cite more appropriate primary sources.\n3. Line 131-133: The authors said, “The activities of of NADH dehydrogenase activity (GO:0003954, Supplementary Fig. 4b) and oxidoreductase activity, NAD or NADP as acceptor (GO:0016620, Supplementary Fig. 4c) were significantly\nenriched”，which contains a typo (“of of”). More importantly, it’s recommended to include enzyme activity validation of this\nNADH dehydrogenase, which would further clarify the mechanism of the evolved strain.\n4. Figures 1c and 1g are difficult to interpret due to poor resolution. Figures 2c–e are also unclear and should be improved\nfor better readability.\n5. The RT-qPCR experiments do not mention or show standard curves, which are essential for reliable quantification.\n6. Gene names should be italicized with lowercase initials, while protein names should start with uppercase letters without\nitalics in bacteria. For example, “genes CysH, CysC, CysJ, CysI, CysN, and CysD in REcN” (Line 155) and Figure 2g should\nbe revised accordingly.\n6. Line 181-184: The authors claims that Oil Red O staining “quantitatively confirms transcriptome-predicted lipid catabolism\nenhancement”. However, Figure 2f does not provide quantitative data comparing REcN and control samples.\n7. Line 260-262: The authors state that “In contrast, HFD-fed mice did not show significant changes in blood insulin levels\nafter glucose injection (Fig. 4f)”, whereas Figure 4f shows a marked decline of insulin in HFD-fed mice.\n8. Figures 4j-i lack significance indicators for comparisons between HFD+REcN-F/Ca and ND.", "reviewer_2": "This study has potential in the field of engineered probiotics for treating metabolic diseases. However, revisions are needed\nto enhance scientific rigor and clinical translation value, including supplementing control experiments, improving\nmechanistic validation, expanding animal models, and clarifying administration schedules. The overall study is well\norganized and performed and the goals of this research are of particular interest in the field of the application of engineered\nprobiotics. Thus I enthusiastically support acceptance of this work after addressing following minor issues.\n1: The core strategy of engineering ROS-tolerant EcN via iterative H₂O₂ selection and FOS/CaCO₃ modification overlaps\nwith prior studies (Sci. Adv. 8, eabp8798, 2022; Nat. Nanotechnol. 18, 617-627, 2023). Clarify unique contributions in\nscreening strategies, FOS-CaCO₃ synergy, and cross-regulation between PPAR and H₂S pathways. The\n\"pharmacomicrobiomics paradigm\" claim lacks support—compare with traditional/proven engineered probiotics to justify\ninnovation.\n2: ROS tolerance mechanisms: Supplement membrane lipid analysis and stress regulator (SoxR, OxyR) expression to\nexclude untested pathways.\n3: Add FOS thickness, CaCO₃ crystallinity, and degradation kinetics in simulated gut fluids.\n4: Isolate REcN supernatant components and test PPARα silencing to confirm direct effects.\n5: Lack large animal data to verify gut survival and metabolic improvements. Define REcN gut retention time (via tracking) and optimal dosing (e.g., daily vs thrice-weekly). Address long-term safety: overgrowth risk, resistance gene transfer, and\nimmunogenicity.\n6: Verify if SCFAs directly activate PPARα (reporter assays) and if PPARα knockout abolishes efficacy. Validate H₂S\nnecessity via cysH/sseA knockout and exogenous H₂S rescue experiments.\n7. Some related references (such as Nat. Commun.,2022, 13, 3432; Biomaterials, 2024, 309, 122584)", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.", "reviewer_4": "The manuscript presents a novel therapeutic strategy for type 2 diabetes based on the engineering of probiotics via directed\nevolution and surface display technology. The authors provide a systematic evaluation, encompassing strain construction, in\nvitro functional characterization, multi-omics analysis, and in vivo efficacy studies, which collectively demonstrate the\nconsiderable potential of this engineered strain in ameliorating metabolic syndrome. However, to fully substantiate the\nscientific claims, the authors must address the following issues with further experimental evidence and more rigorous\nscientific discourse, as detailed below.\n1. The authors present the electron-dense layer observed in TEM images (Fig. 3a-b) as key evidence for the successful\npolymerization of FOS. However, the validity of this argument is challenged by the following: Firstly, in Fig. 3a, the\nunmodified REcN strain also appears to exhibit a similar, albeit less electron-dense, boundary layer, which weakens the\nlogic of uniquely attributing the structure in Fig. 3b to the FOS coating. Secondly, bacteria, especially Gram-negative strains,\npossess complex, multi-layered cell envelopes (e.g., outer membrane, periplasmic space) that can inherently appear\nstratified under TEM. To provide unequivocal evidence, we strongly recommend the authors supplement the manuscript with\na high-resolution TEM image of an unmodified REcN control (from the same culture batch used for modification), acquired\nunder identical imaging and sample preparation conditions (including staining method, magnification, image brightness, and\ncontrast) as Fig. 3a-b. Only through such a rigorous side-by-side comparison can one convincingly distinguish the newly\nformed structure resulting from FOS polymerization from the bacterium's intrinsic envelope architecture.\n2. We note an apparent contradiction: in simulated intestinal fluid (SIF), REcN-F/Ca exhibited lower viability than the\nuncoated REcN (Fig. 3e), yet it displayed the highest ROS-scavenging activity (Fig. 3g). This raises questions about the\nsource of this activity. Is this antioxidant effect attributable to the live bacteria, the intrinsic chemical properties of the coating\nmaterials (FOS/CaCO3), or contributions from bacterial lysates?\n3. The authors attribute the lower survival rate of REcN-F/Ca in SIF (pH ≈ 6.8, per reference [35]) to insufficient dissolution of\nthe CaCO3 shell. This explanation, however, is in direct logical contradiction with the data showing superior protection in\nSICF (pH ≈ 7.8, per reference [35]), a condition where the shell's solubility should be even lower (Fig. 3e vs. 3f). The authors\nshould provide a more plausible explanation and explicitly state the formulations of all simulated fluids used.\n4. The authors should provide an experimental or theoretical rationale for selecting a single dose (5 × 108 CFU/mL) and\nfrequency (thrice weekly). It should be explained why a dose-response study was not conducted to investigate the dose-\neffect relationship of this therapy. Furthermore, the specific timing of the \"thrice-weekly\" administration must be clarified to\nensure experimental reproducibility.\n5. Given that FOS, a component of the delivery vehicle, is itself a prebiotic with known anti-diabetic effects, the current\nanimal study lacks two critical control groups: a \"F/Ca vehicle\" group and a \"EcN-F/Ca\" group. Without these controls, the\nobserved therapeutic effects cannot be uniquely attributed to the ROS-tolerance-engineered REcN.\n6. The results presented in Fig. 4f are puzzling. The authors observe that serum insulin levels in HFD mice decreased\nfollowing a glucose challenge. This appears to contradict the established consensus in the field that HFD-induced insulin\nresistance is typically accompanied by a compensatory increase in insulin secretion to maintain glucose homeostasis.\nCould the authors please clarify this observation? To enable proper interpretation of this important data, we ask the authors\nto provide more details or discuss this unexpected finding.\n7. In the analysis of epididymal adipose tissue inflammation, the authors conclude that REcN treatment reduces \"pro-\ninflammatory M1-like macrophages\" (Fig. 4h-i). However, the methodology and data presented only show staining for F4/80,\na pan-macrophage marker. This marker cannot, by itself, distinguish between M1 and M2 polarization states. To substantiate\nthis claim, immunofluorescence co-staining with canonical M1 markers (e.g., iNOS, CD86) is essential. As it stands, the\nconclusion regarding M1-like macrophages is an over-interpretation of the available evidence.\n8. The authors should supplement their analysis with a quantitative morphological analysis of the BODIPY-stained\nadipocytes in Fig. 4h. This would not only provide a direct cellular mechanism for the fat mass reduction reported in Fig. 4d\nbut also robustly link the gross phenotype to the histopathological changes.\n9. The central hypothesis of this study—that engineered ROS tolerance confers a survival and colonization advantage to\nREcN within the inflamed gut of T2DM mice—is an unproven core assumption. The manuscript lacks direct in vivo evidence\nto support this critical assertion. To validate this foundational hypothesis, the authors could provide data on: a) a quantitative\nanalysis of ROS levels in the intestinal lumen of HFD versus ND mice to confirm the high-ROS pathological environment; and\nb) quantification of strain-specific DNA in fecal samples (via qPCR) to directly compare the long-term survival and\ncolonization dynamics of REcN-F/Ca versus a coated, non-engineered control strain in vivo.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.", "reviewer_6": "I. Executive Summary\nA. Research Overview and Contribution\nThis study introduces a novel strategy for treating type 2 diabetes mellitus (T2DM) by engineering a reactive oxygen species\n(ROS)-tolerant E. coli Nissle 1917 (EcN) strain via iterative hydrogen peroxide exposure. The strain is encapsulated with\nfructooligosaccharides (FOS) and calcium carbonate (CaCO₃) to enhance gut survival, forming REcN-F/Ca. In a high-fat diet\n(HFD)-induced mouse model, this engineered probiotic alleviated weight gain and insulin resistance, likely via modulation\nof the gut microbiota and activation of PPARα signaling.\nB. Key Strengths\n• Conceptual novelty: Pre-adapting probiotics to oxidative gut conditions represents a significant improvement over\ntraditional strategies.\n• Methodological scope: The study integrates microbial engineering, transcriptomics, in vitro assays, in vivo phenotyping,\nand microbiome analysis, offering a broad perspective on therapeutic impact.\nC. Summary of Core Flaws and Final Recommendation\nDespite its potential, the current manuscript contains several fundamental flaws that preclude its publication in a top-tier\njournal.\nThe major issues can be summarized as: (1) flaws in experimental design due to the absence of essential control groups, (2)\ninsufficient statistical power and inappropriate analytical methods, and (3) mechanistic claims based on unproven\ncorrelations rather than causal evidence.\nII. Major Revisions Required for Publication\nA. Critical Flaws in Experimental Design and Controls\nThe paper’s biggest flaw is its experimental design, which lacks essential control groups. Without comparing the engineered\nprobiotic to the non-engineered version or testing the effects of the delivery matrix alone, the authors cannot attribute the\nobserved benefits specifically to their engineered strain. This omission introduces confounding variables that undermine the\nstudy’s main conclusions.\n1. Absence of a Wild-Type Probiotic Control\nThe manuscript compares HFD mice treated with REcN-F/Ca to untreated HFD mice. This design makes it impossible to\ndetermine whether the observed benefits are due to the novel ROS-tolerance engineering or simply the general effects of the\nparent strain, EcN. The paper's central claim—that the directed evolution adaptation confers a therapeutic advantage—is\ntherefore entirely unsupported by the current data.\nRequired Action: The 10-week animal study must be repeated to include a HFD + wild-type EcN (in the same FOS/CaCO3\nvehicle) control group. Only a direct comparison between REcN-F/Ca and EcN-F/Ca can isolate and quantify the added\nbenefit of the ROS-tolerance engineering.\n2. Absence of a Vehicle-Only Control\nThe encapsulation matrix contains fructooligosaccharides (FOS), a well-known prebiotic fiber. FOS itself can modulate the\ngut microbiota, promote the growth of butyrate-producing bacteria (e.g., Lachnospiraceae), and improve metabolic health.\nThe manuscript attributes the increase in these bacteria and the restoration of SCFAs entirely to the action of REcN-F/Ca.\nThis conclusion is premature and likely confounded. The observed effects on the microbiome could be partially or wholly\nattributable to the FOS vehicle.\nRequired Action: The animal study must include a HFD + FOS/CaCO3 vehicle-only control group. This is essential to\ndisambiguate the effects of the prebiotic matrix from those of the live probiotic.\n3. Limitations of the Animal Model\n-Preventive vs. Therapeutic Model: The current study uses a prevention model, where the probiotic is administered\nconcurrently with the HFD. While this shows mitigation of disease, it does not show reversal of established disease.\nFor clinical relevance, a therapeutic model, where treatment begins after obesity and insulin resistance are established, is far\nmore meaningful.\n-Single-Sex Study: The exclusive use of male mice is a significant limitation, as metabolic and immune responses can differ\nsubstantially in females. This sex bias limits the generalizability of the findings.\n-Required Action: While performing a full therapeutic model study may be difficult during revision, the authors must discuss\nthese limitations in depth. It should be clearly stated that the efficacy in a therapeutic context and in females remains\nunknown and requires future investigation.\nB. Insufficient Statistical Rigor and Inadequate Data Reporting\n1. Inadequate Sample Size and Lack of Power Analysis\nThe manuscript relies on critically small sample sizes for key conclusions, particularly SCFA measurements (Figure 6, n=3)\nand colonic gene expression analysis (Figure 5, n=3). The in vivo study (n=6) is also on the low side for metabolic studies.\nThe authors provide no justification or power analysis for these choices, raising serious concerns about the statistical power\nand reproducibility of the findings.\nRequired Action: The authors must provide a formal power analysis for the main in vivo endpoints. If possible, the sample\nsize for SCFA and gene expression analysis in the repeat experiment should be increased to enhance the reliability of the\nresults.\n2. Data Reporting\nFor all key results, the authors must report exact p-values (e.g., p=0.034) instead of ranges (e.g., p<0.05). They should also\nreport confidence intervals and/or effect sizes to provide a more complete picture. All figure captions must explicitly state the\nstatistical test used, the number of replicates (n), and what the error bars represent (e.g., mean ± SD).\nC. Mechanistic Claims Lacking Causal Verification\nThe manuscript builds a strong narrative, but relies on correlation without proving causation. It assumes that microbiome\nchanges lead to PPARα activation, without ruling out alternative explanations or providing direct mechanistic evidence.\nWithout experiments to test these links, the proposed pathway remains speculative.\n1. Correlative Evidence for the PPARα/SCFA Axis\nThe central mechanistic claim—that REcN-F/Ca works by enriching butyrate-producing bacteria, whose SCFAs then\nactivate host PPARα signaling—is supported only by correlational data. The study shows these events occur concurrently\nbut does not prove causation.\nRequired Action (to establish causality): The reviewers have provided an excellent roadmap. To truly strengthen the\nmanuscript, the authors should consider (and if possible, perform):\n-To validate the mechanism, test whether blocking PPARα signaling with an inhibitor (e.g. GW6471) eliminates REcN-\nF/Ca’s effects, and use FMT to determine if microbiota changes alone can transfer the metabolic benefits.\n-If New Experiments Are Not Feasible: The authors are recommended to tone down their mechanistic claims throughout the\nmanuscript. Phrasing like \"driving\" or \"mediating\" should be revised to \"associating with,\" and the Discussion should\nexplicitly state that causality has not been established and the observed associations are correlational.\n2. In Vivo Relevance of ROS Tolerance Unproven\nThe entire premise of the paper is based on engineering a ROS-tolerant probiotic. The authors meticulously characterize\nthis trait in vitro (Figure 1). However, they provide no direct evidence that this enhanced ROS tolerance is functional or\nrelevant in vivo. They do not measure whether REcN-F/Ca treatment actually reduces markers of oxidative stress (e.g., lipid\nperoxidation, 8-OHdG) in the colonic lumen or tissue of treated mice. This is a critical missing link in the logical flow of the\npaper's narrative. Without this piece of data, the entire \"bioengineering for ROS tolerance\" story is disconnected from the in\nvivo outcomes.\nRequired Action: The authors should analyze stored colon tissue from the animal study for markers of oxidative stress. This\nwould provide crucial evidence linking the in vitro engineered trait to an in vivo biological effect, a point raised in."}, "author_response": "Reply: We sincerely thank the Reviewer for the thoughtful and positive assessment of\nour work, and for recognizing the potential of our bioengineered probiotic approach in\naddressing the complex pathophysiology of type 2 diabetes mellitus (T2DM).\n1. This manuscript employs FOS modification and calcium carbonate mineralization,\nyet does not provide a clear but explanation of their underlying mechanisms or rationale.\nMoreover, the choice of FOS and calcium carbonate over alternative materials is not\njustified. This weakens the theoretical basis of the methodology. The authors are\nencouraged to discuss the rationale behind these choices and consider whether other\nprobiotic strains (besides EcN) could be similarly engineered to achieve or better\ntherapeutic effects.\nReply: We thank the reviewer for this insightful comment, which allows us to clarify\nand strengthen the rationale behind our choice of materials and engineering strategy.\nThe sequential application of FOS and CaCO was a deliberate design based on their\n3\ncomplementary functions aimed at enhancing probiotic survival and efficacy. FOS is a\nwell-established, non-digestible prebiotic that selectively stimulates the growth of\nbeneficial gut bacteria, such as Bifidobacterium and Lactobacillus. By coating REcN\nwith FOS, we aimed to create a self-driven probiotic that carries its own growth-\npromoting fuel. This is hypothesized to enhance its survival and persistence in the\n2\ncompetitive gut environment post-administration. The subsequent mineralization with\nCaCO was employed to address the critical challenge of gastrointestinal transit. The\n3\ndense, inorganic CaCO shell serves as a physical barrier against harsh gastric acid (low\n3\npH) and bile salts in the upper GI tract. Our data in Figs. 3d-f confirm that this shell\nsignificantly enhances bacterial viability after exposure to simulated gastric and\nintestinal fluids. Therefore, the CaCO layer encapsulates the FOS-coated probiotic,\n3\nensuring that the prebiotic is also protected during transit and delivered alongside the\nviable bacteria to the colon, creating a synergistic system. And we have supplemented\nthe discussion to the Discussion section. The detail can be found in the revised\nmanuscript (Page 22, line 21-Page 23, line 5) or below for your reference.\n“While other prebiotics (e.g., inulin) exist, FOS has a shorter chain length than inulin,\nmaking it potentially more readily fermentable by a broader range of beneficial\nbacteria.[52] Unlike some encapsulation polymeric materials (e.g., chitosan, alginate)\nthat may require complex synthesis or raise biocompatibility concerns, CaCO is a Food\n3\nand Drug Administration–approved material. Its mineralization process is simple,\nscalable, and results in a highly stable, protective shell.”\nThe reviewer raises an excellent point regarding the generalizability of this engineering\napproach. We fully agree that the strategy FOS/CaCO encapsulation is a versatile\n3\nplatform technology that could, in principle, be applied to other probiotic strains (e.g.,\nLactobacillus or Bifidobacterium species). Our decision to use EcN as a proof-of-\n3\nconcept was based on our previous research. We have found that Gram-negative\nbacteria possess inherent structural and metabolic features that make them particularly\neffective at purifying and tolerating ROS-rich environments. We have added the\ndiscussion to the Discussion section to acknowledge this promising future direction,\nexplicitly mentioning the relevance of the Gram-negative chassis. The detail can be\nfound in the revised manuscript (Page 24, line 14-Page 25, line 1) or below for your\nreference.\n“Crucially, EcN is one of the few well-characterized, common probiotic strain that is\nGram-negative. We have found that Gram-negative bacteria possess inherent structural\nand metabolic features that make them particularly effective at purifying and tolerating\nROS-rich environments.[62] The presence of an outer membrane and specific\nperiplasmic redox systems provides a foundational advantage in managing oxidative\nstress. Therefore, Gram-negative strains like EcN represent an ideal starting chassis for\nROS-targeted engineering. Future work will indeed explore applying this biomimetic\nengineering paradigm to other promising Gram-negative candidates, as well as to more\nrobust Gram-positive probiotic, to create a suite of tailored therapeutics for various\ndiseases.”\n2. Critical comparisons between native EcN, FOS-modified EcN, calcium carbonate-\nencapsulated EcN, and REcN-F/Ca are missing. These comparisons are essential to\nevaluate the incremental contributions of each modification step. Without such data, it\n4\nis difficult to assess whether evolutionary adaptation is necessary, thereby weakening\nthe study’s overall conclusions.\nReply: We thank the reviewer for this critical comment. We apologize for this oversight\nin the original manuscript and have performed additional experiments to provide a\ndirect comparison. The existing data demonstrate that both the evolutionary adaptation\nand the sequential surface engineering are necessary for achieving the optimal\ntherapeutic effect.\n(1) Contribution of evolutionary adaptation (REcN vs. EcN):\nThe primary benefit of H O -driven evolution is the profound enhancement of intrinsic\n2 2\nROS tolerance and metabolic reprogramming. As shown in the original Fig. 1e, f,\nREcN possesses significantly higher intrinsic SOD/CAT activities and •OH scavenging\ncapacity than native EcN. Transcriptomic and functional data (Figs. 1c,d,g, 2) reveal\nthat REcN has undergone a metabolic rewiring (enhanced TCA cycle, lipid catabolism,\nH S production) that the wild-type strain lacks. This is critical for the ability of probiotic\n2\nto thrive in and modify the hostile, nutrient-rich diabetic gut environment.\n(2) Contribution of sequential surface engineering (REcN vs. REcN-F/Ca):\nThe surface modifications are primarily responsible for extrinsic protection and\ntargeted delivery. Our data in Fig. 3d-f show that while REcN is more robust than EcN,\nthe CaCO encapsulation (REcN-F/Ca) provides the highest level of protection.\n3\nFOS/CaCO , and REcN-FOS/CaCO . Most importantly, we included the essential\n3 3\ncontrol groups HFD+F/Ca and HFD+EcN-F/Ca in our animal study. The detailed\nexperimental procedure can be found in the revised manuscript (Page 35, line 8-15 and\nPage 37, line 11-Page 38, line 11) or below for your reference.\n“Freshly prepared Cy5.5 dye (10 mg mL-1) was slowly added to probiotic suspensions\n(108 CFU mL-1). The mixtures were incubated at 37 oC for 2 h in the dark with gentle\nshaking, followed by repeated PBS washes until the supernatant was clear. The labeled\nprobiotic was then collected, and the FOS/CaCO encapsulation was performed on\n3\nintestinal tissues were collected 6 h post-administration for ex vivo fluorescence\nimaging using an IVIS Lumina XRMS Series III system (PerkinElmer).”\n“Animal experiments were performed and approved by the Beatcell Model Biological\nCenter (Approval No. 2025-07-31A). Male C57BL/6J mice (n = 6, 6-week-old) were\nacclimatized in IVC cages under SPF conditions (22 ± 1 °C, 55% humidity, 12 h light-\ndark cycle) with autoclaved water and a standard feed. Following 2-week standard chow,\nmice underwent metabolic challenge via HFD for 10-week intervention, establishing a\nvalidated insulin-resistant prediabetic model. The animal study included six groups: 1)\nND group, 2) HFD group, 3) HFD+F/Ca vehicle group, 4) HFD+EcN-F/Ca group, 5)\ngroup. Pharmacokinetic-informed intervention consisting of 0.5 mL probiotic\nsuspension (5 × 108 CFU mL-1) was administered via orogastric gavage thrice weekly\n(at 9:00 AM on Monday, Wednesday, and Friday). For HFD+EcN-F/Ca+GW6471\ngroup, mice were treated with GW6471 (20 mg kg-1 in DMSO) by intraperitoneal\ninjection after orogastric gavage. Weekly body weight measurements was recorded. At\nweek 10, fasting blood samples acquired via tail venipuncture were processed for\nHOMA-IR calculation, while fecal pellets underwent immediate flash-freezing for\nSCFAs quantification and gut microbiome analysis. IPGTT was conducted involving\nintraperitoneal D-glucose (2g kg-1, 20% w/v solution) with glycemic profiling at\n0/30/60/90/120 min. Concurrent serum insulin dynamics were assessed using ELISA.\nTerminal procedures at week 10 employed cervical dislocation under isoflurane\nanesthesia (3% induction), with subsequent tissue harvest utilizing aseptic\nmicrodissection techniques. The F4/80, CD86, and BODIPY in eAT and the 8-OhdG in\ncolon tissue were detected by immunofluorescence staining. And the main organs were\nstained by H&E.”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 16-Page\n14, line 1 and Page 14, line 3-Page 16, line 13) or below for your reference.\n“To directly evaluate the gastrointestinal colonization capacity of the engineered\nprobiotic, an ex vivo tracking experiment using Cy5.5-labeled strains was performed.\n3\nachieved the highest retention level among all groups (Fig. 3k,l). The FOS prebiotics\nimproved the retention of both strains compared to their unencapsulated counterparts.\nNotably, the fluorescent signal of REcN-FOS/CaCO was significantly greater than that\n3\nof EcN-FOS/CaCO , indicating that the ROS-tolerant phenotype of REcN also\n3\nenhanced gut colonization.”\nFig. 3k,l\n“To establish causal links between REcN-FOS/CaCO (REcN-F/Ca) supplementation\n3\nand metabolic improvement, a high-fat diet (HFD)-induced obesity murine model was\nemployed. Compared to normolipidic diet (ND)-fed controls, HFD-fed mice developed\npronounced obesity phenotypes, evidenced by elevated body weight gain (Δ+71.9%\nversus Δ+43.5%), peritesticular fat accumulation, and higher epididymal adipose tissue\n(eAT) weight (Fig. 4a-d). Additionally, the wild-type EcN probiotic encapsulated within\nthe protective shell demonstrated a mitigating effect on obesity, which can be attributed\nto the action of the EcN probiotic. The F/Ca shell showed a negligible inhibitory effect\non obesity. However, oral administration of REcN-F/Ca during HFD feeding mitigated\nobesity development, as evidenced by reduced body weight gain and fat accumulation\n8\ncompared to HFD-fed mice that did not receive supplementation (Fig. 4a-d).\nMetabolic profiling revealed HFD-driven hyperglycemia and insulin resistance,\nboth ameliorated by REcN-F/Ca (Fig. 4e). During intraperitoneal glucose tolerance\ntesting (IPGTT), ND-fed mice exhibited transient increases in blood insulin levels\nfollowing intraperitoneal glucose injection, with a rapid return to baseline (Fig. 4f). In\ncontrast, HFD-fed mice exhibited a significant decline in blood insulin levels following\nthe glucose challenge (Fig. 4f). This pattern is indicative of failure to mount an\nappropriate secretory response, a hallmark of T2DM pathology, rather than mere insulin\nresistance.[36] On the contrary, in mice fed with F/Ca, the blood insulin levels continued\nto rise after glucose injection, which is a typical characteristic of insulin resistance. This\nminor improvement was metabolically insufficient, as evidenced by the poor overall\nglucose tolerance and high HOMA-IR, which remained comparable to the HFD group.\nHowever, HFD-fed mice supplemented with REcN-F/Ca demonstrated insulin\nresponses comparable to those of ND-fed mice (Fig. 4f). Consistent with these\nobservations, the increases in blood glucose levels following intraperitoneal glucose\ninjection in HFD-fed mice were normalized to levels similar to those of ND-fed mice\nwhen supplemented with REcN-F/Ca (Fig. 4g).\nInflammation within the eAT is known to contribute to the development of obesity-\ninduced diabetes.[36] Histopathological evaluation of eAT in HFD and HFD+F/Ca\ngroups revealed M1 macrophage infiltration (Fig. 4h), a hallmark of obesity-associated\nadipose inflammation. In line with the inhibitory effects of REcN on diabetes\npathogenesis, the eAT of HFD-fed mice supplemented with REcN-F/Ca exhibited\n9\nminimal macrophage accumulation (Fig. 4h). The administration of REcN significantly\nalso reduced the number of lipid droplets infiltrating the eAT of HFD-fed mice (Fig.\n4i,j). Additionally, RT-qPCR analysis indicated that the expression of S100a8 and Tnfα\n(Fig. 4k,l), which encode a chemokine that recruits macrophages and an inflammatory\ncytokine, respectively, was downregulated in the mature adipocyte fraction of the eAT\nin HFD-fed mice supplemented with REcN-F/Ca. Therefore, the administration of\nREcN-F/Ca not only inhibited body weight gain but also attenuated inflammatory\nresponses in the eAT of HFD-fed mice.\nNotably, colonic Pparα expression was upregulated in REcN-F/Ca-treated HFD\nmice versus ND mice (Fig. 4m). As a nuclear receptor regulating lipid oxidation and\nanti-inflammatory pathways, PPARα activation may mechanistically link metabolic\nbenefits of REcN to transcriptional reprogramming of host energy utilization and\ninflammatory responses. Owing to the superior antioxidant capacity of REcN, the colon\ntissues after therapy showed the least oxidative stress (Fig. 4n,o). Furthermore,\nhistopathological analysis via hematoxylin and eosin (H&E) staining demonstrated\ndistinct hepatic morphological alterations across experimental cohorts. The ND group\nmaintained intact hepatic lobular architecture with characteristic radial hepatocyte\narrangement around central veins (Supplementary Fig. 21). Conversely, HFD group\nexhibited pronounced microvesicular and macrovesicular steatosis, accompanied by\nhepatocyte ballooning degeneration. Notably, REcN-F/Ca intervention substantially\nattenuated HFD-induced hepatosteatosis. Critical extrahepatic organs (heart, spleen,\nlung, and kidney) displayed preserved histoarchitectural integrity across all groups,\n10\nsuggesting absence of multiorgan toxicity after REcN-F/Ca treatment.”\nFig. 4\n3. The study lacks whole-genome sequencing and comparative analysis of the evolved\nREcN strain. Such analyses are critical to identify mutations underlying enhanced ROS\ntolerance and to elucidate the genetic basis of the observed phenotypic improvements.\nThis omission limits mechanistic insight and weakens the scientific depth of the study.\ngenome sequencing to identify the genetic mutations underlying the REcN phenotype.\nIn our study, we employed a complementary and powerful approach to elucidate the\nmolecular mechanisms driving the enhanced ROS tolerance. Our primary strategy was\nto conduct comprehensive transcriptomic profiling (RNA-Seq) of the evolved REcN\nversus the wild-type EcN. This analysis was exceptionally fruitful, allowing us to\nsystematically identify the functional transcriptional reprogramming responsible for the\nadaptive phenotype, rather than just the potential genetic lesions.\nAs detailed in our original manuscript (Fig. 1, Supplementary Figs. 3-7), the\ntranscriptomic analysis successfully revealed a coordinated upregulation of core\nantioxidant enzymes (sodA, sodB, sodC, katG), which we functionally validated with\nenzymatic assays. Furthermore, it demonstrated a significant enrichment of\noxidoreductase complexes and NADH dehydrogenase activity, indicating a rewired\nenergy metabolism that supports efficient redox balancing. Most notably, the profiling\nuncovered a pronounced activation of the hydrogen sulfide biosynthetic pathway, a\nfinding we subsequently confirmed through both classic lead acetate tests and modern\nfluorescent probe analysis, collectively providing a multi-layered understanding of the\nadaptive phenotype.\nThis focus on the functional transcriptome allowed us to directly link the observed\nphenotype to the activated pathways and processes, providing a robust, systems-level\n12\nunderstanding of the adaptation. We believe that the combination of this detailed\ntranscriptomic landscape with our subsequent functional validations offers a\ncompelling and multi-layered mechanistic narrative.\n4. In Line 233-237, the authors state that “Notably, the modification with CaCO further\n3\nenhanced the viability of the REcN probiotic, confirming the robust protective role of\nCaCO in the digestive tract. Interestingly, in SIF, REcN probiotic not protected by\n3\nmay insufficiently solubilize the mineralized shell to fully release encapsulated\nbacteria”. The authors report that calcium carbonate modification enhances REcN\nviability, confirming its protective effect. However, in SIF, unencapsulated REcN shows higher\nviability, possibly due to incomplete calcium carbonate shell dissolution. This contradictory finding undermines the\nprotective claim. The authors should clarify the physiological relevance of the SIF data and reconcile the inconsistency with\nthe broader narrative.\nReply: We thank the reviewer for raising this important point regarding the\ninterpretation of our initial gastrointestinal (GI) stability data. We have significantly\nimproved our experimental approach and conducted two critical new experiments that\ntogether provide a more physiologically relevant and mechanistically clear picture of\nthe CaCO function. To accurately simulate the complete digestive journey, we\n3\ndeveloped a new protocol where probiotic was sequentially exposed to SGF (20 min),\nthen SIF (2 h), and finally SICF (2 h), with viability assessed after each step, rather than\n13\nbeing co-cultured separately with the three types of simulated liquids. The detailed\nexperimental procedure can be found in the revised manuscript (Page 34, line 6-11) or\nbelow for your reference.\n“Probiotic (1×107 CFU mL-1) was first incubated in SGF (containing pepsin and HCl,\npH 1.2) for 20 min, then the probiotic was collected, resuspended, and transferred to\nSIF (containing pancreatin in phosphate buffer, pH 6.8) for 2 h, followed by a final\ntransfer to SICF (containing ammonium hydroxide, 200 μM H O in phosphate buffer)\n2 2\nfor 2 h. incubated in 1 mL of medium supplemented with either SGF, SIF, or SICF.\nViability (CFU count) was determined after each step.”\nAnd the detailed results can be found in the revised manuscript (Page 12, line 5-17) or\nbelow for your reference.\n“Subsequently, to rigorously evaluate the protective efficacy of the CaCO shell during\n3\nsequential GI transit, we subjected the probiotic to a simulated journey from the\nstomach to the inflamed colon. Given the GI transit times, with rapid gastric emptying\noccurring within approximately 20 min, followed by small intestinal transit for about 2\nh, and ultimately reaching the inflamed colon,[35] the viability and ROS-scavenging\ncapacity of EcN, REcN, and REcN-FOS/CaCO were assessed after first incubation for\n3\n20 min in simulated gastric fluid (SGF), then incubation for 2 h in simulated intestinal\nfluid (SIF), and finally incubation for 2 h in simulated inflammatory colon fluid (SICF).\nAfter each sequential challenge, REcN demonstrated greater activity than EcN (Fig.\n14\n3d-f), likely due to its superior energy metabolism that enables it to better withstand GI\nenvironmental assaults. Notably, the modification with CaCO further enhanced the\n3\nviability of the REcN probiotic, confirming the robust protective role of CaCO in the\n3\ndigestive tract.”\nFig. 3d-f\nTo directly validate the pH-responsive dissolution mechanism of the CaCO shell, we\n3\nquantified the release of Ca ions from REcN-FOS/CaCO in the different simulated\n3\nfluids using ICP-OES. The detailed experimental procedure can be found in the revised\nmanuscript (Page 35, line 2-7) or below for your reference.\n“REcN-FOS/CaCO (1×108 CFU mL-1) was incubated in 2 mL of medium\n3\nsupplemented with either SGF, SIF, or SICF. The incubation was conducted at 37 °C\n(SGF for 20 min, SIF for 2 h, and SICF for 2 h) with gentle shaking to evaluate their\nstabilities in the GI environment. The dissolution profile of the CaCO shell was\n3\n15\ncharacterized by measuring the concentration of released Ca ions in SGF, SIF, and SICF\nover time using inductively coupled plasma optical emission spectrometry (ICP-OES).”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 4-10) or\nbelow for your reference.\n“To functionally validate the pH-responsive behavior, we quantified the dissolution\nkinetics of the CaCO shell. Inductively coupled plasma optical emission spectrometry\n3\n(ICP-OES) analysis revealed a rapid release of Ca2+ ions in SGF (pH 1.2, ~50 mg L-1\nafter 20 min), contrasting with a slow, sustained release in SIF (pH 6.8, ~18 mg/L after\n2 h) and SICF (pH 7.8, ~12 mg/L after 2 h) (Supplementary Fig. 19). This controlled\ndissolution in the upper GI tract ensures that a maximal payload of viable REcN is\ndelivered to the target colonic environment.”\nSupplementary Fig. 19\n16\n5. Despite acknowledging that native EcN fails to persistently colonize inflamed gut\nenvironments, the authors did not assess whether REcN or REcN-F/Ca demonstrates\nimproved colonization. This is a key functional endpoint and should be experimentally\nvalidated.\nReply: We thank the reviewer for this essential suggestion regarding the need to\nvalidate the gut colonization capacity of our engineered probiotics. In direct response,\nwe have conducted a new ex vivo tracking experiment to quantitatively compare the\ngastrointestinal retention of the different probiotic formulations. The detailed\nexperimental procedure can be found in the revised manuscript (Page 35, line 8-15) or\nbelow for your reference.\n“Freshly prepared Cy5.5 dye (10 mg mL-1) was slowly added to probiotic suspensions\n(108 CFU mL-1). The mixtures were incubated at 37 oC for 2 h in the dark with gentle\nshaking, followed by repeated PBS washes until the supernatant was clear. The labeled\nprobiotic was then collected, and the FOS/CaCO encapsulation was performed on\n3\nintestinal tissues were collected 6 h post-administration for ex vivo fluorescence\nimaging using an IVIS Lumina XRMS Series III system (PerkinElmer).”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 16-Page\n14, line 1 and Page 14, line 3-Page 16, line 13) or below for your reference.\n17\n“To directly evaluate the gastrointestinal colonization capacity of the engineered\nprobiotic, an ex vivo tracking experiment using Cy5.5-labeled strains was performed.\nQuantitative fluorescence imaging of intestinal tissues revealed that REcN-FOS/CaCO\n3\nachieved the highest retention level among all groups (Fig. 3k,l). The FOS prebiotics\nimproved the retention of both strains compared to their unencapsulated counterparts.\nNotably, the fluorescent signal of REcN-FOS/CaCO was significantly greater than that\n3\nof EcN-FOS/CaCO , indicating that the ROS-tolerant phenotype of REcN also\n3\nenhanced gut colonization.”\nFig. 3k,l\n6. Sequencing results are not available now.\nReply: We thank the reviewer for highlighting this important point. The RNA-seq data\ngenerated in this study have been deposited in the NCBI Sequence Read Archive (SRA)\nand are available under the BioProject accession number PRJNA1283478. Reviewers\ncan access the data using the following BioProject Access URL:\nhttps://www.ncbi.nlm.nih.gov/bioproject/PRJNA1283478\n18\n7. Line 48-51: The references 5-7 do not support the claim that “failure to address gut\nmicrobiota dysbiosis”. Moreover, reference 6 only briefly mentions side effects of\nGLP-1. The authors should cite more appropriate primary sources.\nReply: We thank the reviewer for this accurate observation and for holding us to a high\nstandard of referencing. In the revised manuscript, we have replaced references 5-7 with\nmore appropriate and targeted primary literature that directly substantiates this point.\nThe new references are:\n5. Sodhi, M., Rezaeianzadeh, R., Kezouh, A. & Etminan, M. Risk of gastrointestinal\nadverse events associated with glucagon-like peptide-1 receptor agonists for weight\nloss. JAMA 330, 1795–1797 (2023).\n6. Qi, Q. et al. Hydrogen sulfide produced by the gut microbiota impairs host\nmetabolism via reducing GLP-1 levels in male mice. Nat. Metab. 6, 1601–1615 (2024).\n7. Yun, C. et al. The microbial metabolite agmatine acts as an FXR agonist to promote\npolycystic ovary syndrome in female mice. Nat. Metab. 6, 947–962 (2024).\n8. Line 131-133: The authors said, “The activities of of NADH dehydrogenase activity\n(GO:0003954, Supplementary Fig. 4b) and oxidoreductase activity, NAD or NADP as\nacceptor (GO:0016620, Supplementary Fig. 4c) were significantly enriched”，which\ncontains a typo (“of of”). More importantly, it’s recommended to include enzyme\n19\nactivity validation of this NADH dehydrogenase, which would further clarify the\nmechanism of the evolved strain.\nReply: We thank the reviewer for the careful reading and this helpful suggestion.\nFor typographical error: We sincerely apologize for the typographical error (“of of”).\nThis has been corrected in the revised manuscript.\nFor enzyme activity validation: We have performed the NADH dehydrogenase\nactivity assay comparing the wild-type EcN and the evolved REcN strain. The detailed\nexperimental procedure can be found in the revised manuscript (Page 31, line 17-Page\n32, line 1) or below for your reference.\n“NADH dehydrogenase activity was assessed by monitoring the oxidation of NADH.\nBriefly, EcN and REcN (1×108 CFU mL-1) were incubated with 20 µM NADH solution.\nThe reaction mixture was incubated at 37 oC for 30 min, and the absorbance at 340 nm\nwas measured using a microplate reader at the start and end of the incubation period.\nThe decrease in absorbance was used as an indicator of NADH dehydrogenase activity.”\nAnd the detailed results can be found in the revised manuscript (Page 7, line 3-8) or\nbelow for your reference.\n20\n“To functionally validate the enhanced energy metabolism, we measured the NADH\ndehydrogenase activity in EcN and REcN. Consistent with the RNA-seq data, REcN\nexhibited a significantly greater decrease in NADH absorbance at 340 nm over a 30-\nmin incubation compared to the wild-type EcN strain, confirming its superior NADH\ndehydrogenase activity (Supplementary Fig. 5).”\nSupplementary Fig. 5\n9. Figures 1c and 1g are difficult to interpret due to poor resolution. Figures 2c–e are\nalso unclear and should be improved for better readability.\nReply: We sincerely thank the reviewer for pointing out the issues with figure clarity.\nIn the revised manuscript, we have completely regenerated and optimized these figures\nto ensure the highest quality and clarity.\nRevised Figures 1c and 1g:\nOriginal Figures 2c–e:\nRevised Figures 2c–e:\n22\n10. The RT-qPCR experiments do not mention or show standard curves, which are\nessential for reliable quantification.\nReply: We thank the reviewer for highlighting this important technical aspect of qPCR\nquantification. We confirm that standard curves were generated for each primer set\nduring the assay validation and optimization phase to ensure amplification efficiencies\nwere between 90-110%, and that the R² values were >0.98, confirming the linearity and\nreliability of our quantification. In the revised manuscript, we have update the Methods\nsection to explicitly state this procedure. The detail can be found in the revised\nmanuscript (Page 37, line 6-9) or below for your reference.\n“For each gene target, a standard curve was generated using serial dilutions of cDNA\nto confirm PCR amplification efficiency. All primer sets used had efficiencies between\n90% and 110%, with correlation coefficients (R2) greater than 0.98, ensuring accurate\nquantification.”\n11. Gene names should be italicized with lowercase initials, while protein names should\nstart with uppercase letters without italics in bacteria. For example, “genes CysH, CysC,\nCysJ, CysI, CysN, and CysD in REcN” (Line 155) and Figure 2g should be revised\naccordingly.\nReply: We thank the reviewer for the meticulous attention to detail regarding genetic\nnomenclature. We sincerely apologize for this oversight. We have taken this comment\nvery seriously. Upon receiving this feedback, we conducted a comprehensive,\n23\nsystematic review of the entire manuscript, including all figures and supplementary\nmaterials, to identify and correct all instances of improper genetic nomenclature. In the\nrevised manuscript, we have ensured that all bacterial gene names are consistently\nitalicized with lowercase initials (e.g., cysH, sodA) in full compliance with standard\nconventions.\nOriginal sentences:\n“Targeted quantification of antioxidant enzymes demonstrated marked upregulation of\nSodA, SodB, SodC, and KatG in REcN (Fig. 1d), corresponding to functional validation\nthrough enzymatic assays.”\n“Transcriptomic profiling identified coordinated upregulation of H₂S biosynthesis\ngenes CysH, CysC, CysJ, CysI, CysN, and CysD in REcN (Supplementary Fig. 6c).\nNotably, SseA—encoding 3-mercaptopyruvate sulfurtransferase (3-MST), a key\nenzyme in the non-canonical H S production pathway—showed 1.9-fold induction\n2\n(Supplementary Fig. 6d).”\n“The enhanced expression of enzymes such as isocitrate dehydrogenase (Icd, 1.9-fold),\nsuccinate dehydrogenase (SdhB, 2.7-fold), and malate dehydrogenase (Mdh, 1.3-fold)\nindicated that the REcN strain was able to utilize carbon sources and produce energy\n(Fig. 2g and Supplementary Fig. 10).”\n“Targeted quantification of antioxidant enzymes demonstrated marked upregulation of\nsodA, sodB, sodC, and katG in REcN (Fig. 1d), corresponding to functional validation\nthrough enzymatic assays.”\n“Transcriptomic profiling identified coordinated upregulation of H₂S biosynthesis\ngenes cysH, cysC, cysJ, cysI, cysN, and cysD in REcN (Supplementary Fig. 7c). Notably,\nsseA—encoding 3-mercaptopyruvate sulfurtransferase (3-MST), a key enzyme in the\nnon-canonical H S production pathway—showed 1.9-fold induction (Supplementary\n“The enhanced expression of enzymes such as isocitrate dehydrogenase (icd, 1.9-fold),\nsuccinate dehydrogenase (sdhB, 2.7-fold), and malate dehydrogenase (mdh, 1.3-fold)\nindicated that the REcN strain was able to utilize carbon sources and produce energy\n(Fig. 2g and Supplementary Fig. 15).”\nOriginal Figure 1d:\nOriginal Figure 2g:\nRevised Figure 2g:\nRevised Figure S7c,d:\nOriginal Figure S14:\n12. Line 181-184: The authors claims that Oil Red O staining “quantitatively confirms\ntranscriptome-predicted lipid catabolism enhancement”. However, Figure 2f does not\nprovide quantitative data comparing REcN and control samples.\nReply: We thank the reviewer for this accurate observation and for holding us to a high\nstandard of data presentation. We have performed a quantitative analysis of the Oil Red\nO-stained adipocytes. The detailed experimental procedure can be found in the revised\nmanuscript (Page 32, line 21-Page 33, line 8) or below for your reference.\n“Quantification of intracellular lipid accumulation employed a validated\nspectrophotometric protocol. Differentiated adipocyte monolayers underwent PBS\nrinsing prior to fixation with 4% paraformaldehyde/PBS (37 °C, 30 min). Fixed cells\n28\nwere were stained with Oil Red O for 30 min at ambient temperature, protected from\nlight. After staining, the samples were destained with PBS until a clear background was\nachieved. Bright-field images were then acquired to visualize lipid deposition. For\nquantitative analysis, the lipid-bound dye was solubilized by adding 500 µL of\nisopropanol per well. An aliquot of 200 µL from each sample was transferred to a 96-\nwell plate, and absorbance was measured at 490 nm using a microplate reader.”\nAnd the detailed results can be found in the revised manuscript (Page 10, line 4-7) or\nbelow for your reference.\n“Functional validation using Oil Red O staining demonstrated a significant reduction\nin cytoplasmic lipid droplet accumulation in 3T3-L1 adipocytes cultured with REcN-\nconditioned medium (Fig. 2f and Supplementary Fig. 12), quantitatively corroborating\ntranscriptome-predicted lipid catabolic enhancement.”\nFigure S12\n29\n13. Line 260-262: The authors state that “In contrast, HFD-fed mice did not show\nsignificant changes in blood insulin levels after glucose injection (Fig. 4f)”, whereas\nFigure 4f shows a marked decline of insulin in HFD-fed mice.\nReply: We thank the reviewer for their meticulous attention to detail and for correctly\nidentifying an important nuance in the interpretation of our data. We have revised the\ntext to accurately reflect the data and provide the correct physiological interpretation.\nRevised text:\n“In contrast, HFD-fed mice exhibited a significant decline in blood insulin levels\nfollowing the glucose challenge (Fig. 4f). This pattern is indicative of failure to mount\nan appropriate secretory response, a hallmark of T2DM pathology, rather than mere\ninsulin resistance.[36]”\n14. Figures 4j-i lack significance indicators for comparisons between HFD+REcN-F/Ca\nand ND.\nReply: We thank the reviewer for this careful observation. We have corrected these\nfigures in the revised manuscript. Statistical significance indicators (specific p-values)\nfor the comparison between the groups have been added to the relevant bars in Figures\n4j-o.\nThis study has potential in the field of engineered probiotics for treating metabolic\ndiseases. However, revisions are needed to enhance scientific rigor and clinical\ntranslation value, including supplementing control experiments, improving mechanistic\nvalidation, expanding animal models, and clarifying administration schedules. The\noverall study is well organized and performed and the goals of this research are of\nparticular interest in the field of the application of engineered probiotics. Thus I\nenthusiastically support acceptance of this work after addressing following minor issues.\nReply: We are deeply grateful to the reviewer for the enthusiastic support of our work\nand the positive assessment. We also sincerely thank the reviewer for the valuable\nguidance throughout the review process. The constructive critiques provided have been\ninstrumental in significantly strengthening our manuscript. As detailed in our point-by-\npoint responses, we have undertaken substantial revisions to enhance the scientific rigor\nand translational value of our study.\n1. The core strategy of engineering ROS-tolerant EcN via iterative H O selection and\n2 2\nFOS/CaCO modification overlaps with prior studies (Sci. Adv. 8, eabp8798, 2022; Nat.\nFOS-CaCO synergy, and cross-regulation between PPAR and H S pathways. The\n3 2\n“pharmacomicrobiomics paradigm” claim lacks support—compare with\ntraditional/proven engineered probiotics to justify innovation.\narticulate the unique conceptual and technological advancements of our work beyond\nthe cited and other existing studies. We have revised the manuscript, particularly the\nDiscussion, to better highlight these distinctions. The detail can be found in the revised\nmanuscript (Page 21, line 14-18 and Page 22, line 21-Page 23, line 5) or below for\nyour reference.\n“The prior study primarily focused on protecting probiotic from ROS using externally\napplied nanomaterials or coatings that act as scavengers.[10,35] We used directed\nevolutionary pressure (iterative H O selection) to intrinsically enhance the ROS\n2 2\ntolerance and metabolic resilience. This creates a robust chassis that does not solely\nrely on external protection.”\n“To ensure targeted delivery of REcN to inflammatory loci, we engineered a sequential\nFOS/CaCO encapsulation system (REcN-F/Ca). While other prebiotics (e.g., inulin)\n3\nexist, FOS has a shorter chain length than inulin, making it potentially more readily\nfermentable by a broader range of beneficial bacteria.[52] Unlike some encapsulation\npolymeric materials (e.g., chitosan, alginate) that may require complex synthesis or\nraise biocompatibility concerns, CaCO is a Food and Drug Administration–approved\n3\nmaterial. Its mineralization process is simple, scalable, and results in a highly stable,\nprotective shell.”\n2\nare known, our work provides pioneering in vivo evidence of a potential cross-talk\nbetween microbial H S and host PPAR signaling in the gut-metabolism axis. For the\n2\n“Pharmacomicrobiomics paradigm”, we have removed it from Abstract to tone down\nthe claim.\n2. ROS tolerance mechanisms: Supplement membrane lipid analysis and stress\nregulator (SoxR, OxyR) expression to exclude untested pathways.\nReply: We thank the reviewer for this excellent suggestion to further solidify our\nunderstanding of the ROS tolerance mechanisms in REcN. In response, we have\nperformed the additional analyses and membrane permeability experiment to\nsupplement our analysis and exclude other major untested pathways. The detailed\nexperimental procedure can be found in the revised manuscript (Page 32, line 3-7) or\nbelow for your reference.\n“Outer membrane permeability was assessed using the fluorescent probe 8-anilino-1-\nnaphthalenesulfonic acid (ANS). Briefly, EcN and REcN (1×105 CFU mL-1) cells were\nharvested, washed, and resuspended in PBS. ANS was added to a final concentration\nof 10 µM, and after incubation, fluorescence intensity was measured (excitation 370\nnm, emission 450-600 nm) using a microplate reader.”\nbelow for your reference.\n“The transcriptomic data also indicted that the expression of soxR was downregulated,\nwhile the expression of oxyR was markedly upregulated in REcN (Supplementary Fig.\n6). This shift in regulatory network activity aligns with the observed enhancement in\nperoxide-scavenging capabilities and suggests a prioritized adaptation to H O stress.”\n2 2\nSupplementary Fig. 6\n“To explore additional mechanisms of ROS tolerance, we first assessed whether\nevolutionary adaptation altered outer membrane permeability. The ANS binding assay\nrevealed no significant difference between EcN and REcN (Supplementary Fig. 10),\nindicating that the ROS tolerance was not attributable to a reduced uptake of oxidative\ncompounds.”\n3. Add FOS thickness, CaCO crystallinity, and degradation kinetics in simulated gut\n3\nfluids.\nReply: We thank the reviewer for the valuable suggestion to provide more rigorous\nphysicochemical characterization of our engineered probiotics. In response, we have\nconducted the TEM amd XRD tests to investigate the FOS thickness and CaCO\n3\ncrystallinity. The detail can be found in the revised manuscript (Page 11, line 16-Page\n12, line 4) or below for your reference.\n“Transmission electron microscopy (TEM) imaging revealed a homogeneous electron-\nlucent layer (a thickness of approximately 60 nm) encapsulating REcN cell (Fig. 3a-b\nand Supplementary Fig. 16, red arrow), confirming successful FOS polymerization\n(designated REcN-FOS). Subsequent CaCO mineralization generated a dense\n3\ninorganic shell on REcN-FOS surfaces (Fig. 3c), with energy-dispersive X-ray\nspectroscopy (EDS) mapping demonstrating uniform Ca, C, and O distributions (Fig.\n35\n3c). Detection of nitrogen (N), a microbial biomass signature, confirmed bacterial\nstructural integrity post-modification (designated REcN-FOS/CaCO ). X-ray\n3\ndiffraction (XRD) analysis confirmed the successful mineralization with CaCO₃,\nidentifying the crystalline phase as calcite (Supplementary Fig. 17).”\nFig. 3a-b\nSupplementary Fig. 16\nSupplementary Fig. 17\n3\nquantified the release of Ca ions from REcN-FOS/CaCO in the different simulated\n3\nfluids using ICP-OES. The detailed experimental procedure can be found in the revised\nmanuscript (Page 35, line 2-7) or below for your reference.\n“REcN-FOS/CaCO (1×108 CFU mL-1) was incubated in 2 mL of medium\n3\nsupplemented with either SGF, SIF, or SICF. The incubation was conducted at 37 °C\n(SGF for 20 min, SIF for 2 h, and SICF for 2 h) with gentle shaking to evaluate their\nstabilities in the GI environment. The dissolution profile of the CaCO shell was\n3\ncharacterized by measuring the concentration of released Ca ions in SGF, SIF, and SICF\nover time using inductively coupled plasma optical emission spectrometry (ICP-OES).”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 4-10) or\nbelow for your reference.\n“To functionally validate the pH-responsive behavior, we quantified the dissolution\nkinetics of the CaCO shell. Inductively coupled plasma optical emission spectrometry\n3\n(ICP-OES) analysis revealed a rapid release of Ca2+ ions in SGF (pH 1.2, ~50 mg L-1\nafter 20 min), contrasting with a slow, sustained release in SIF (pH 6.8, ~18 mg/L after\n2 h) and SICF (pH 7.8, ~12 mg/L after 2 h) (Supplementary Fig. 19). This controlled\ndissolution in the upper GI tract ensures that a maximal payload of viable REcN is\ndelivered to the target colonic environment.”\n4. Isolate REcN supernatant components and test PPARα silencing to confirm direct\neffects.\nReply: We thank the reviewer for the excellent suggestion to directly test the causal\nrole of the PPARα signaling pathway in mediating the therapeutic effects of our\nengineered probiotic. In direct response, we have performed a critical in vivo\nintervention experiment using a specific PPARα antagonist GW6471. The detail can be\nfound in the revised manuscript (Page 18, line 5-12 and Page 23, line 17-21) or below\nfor your reference.\n“To establish a causal role for the PPARα pathway, we pharmacologically inhibited\nPPARα signaling in REcN-F/Ca-treated mice using the antagonist GW6471. The\nintervention largely abolished the metabolic benefits conferred by REcN-F/Ca.\nSpecifically, we observed a significant rebound in body weight, eAT weight, HOMA-\nIR index, and a marked deterioration in both insulin secretion and blood glucose levels\n38\nduring tolerance tests (Supplementary Fig. 25). The metabolic profile of this group\nreverted to a state closely resembling that of the HFD control group, demonstrating that\nthe host PPARα pathway is indispensable for the metabolic remediation by REcN-F/Ca.”\nSupplementary Fig. 25\n“Most importantly, the pharmacological inhibition of PPARα signaling almost\nabrogated the therapeutic effects of REcN-F/Ca, unequivocally demonstrating that the\nactivation of this host signaling pathway is not merely associated with, but is strictly\nnecessary for, the observed metabolic improvements.”\n5. Lack large animal data to verify gut survival and metabolic improvements. Define\nREcN gut retention time (via tracking) and optimal dosing (e.g., daily vs thrice-weekly).\nAddress long-term safety: overgrowth risk, resistance gene transfer, and\nimmunogenicity.\nregarding translational potential and long-term safety. We have conducted additional\nexperiments where feasible within the revision timeline and have refined our discussion\nto explicitly address these vital points.\nFor lack large animal data and REcN gut retention, we acknowledge that testing in a\nlarge animal model is a crucial next step for clinical translation. While such a study\nfalls beyond the practical scope of the current revision, we have strengthened our in\nvivo data to better address survival and retention. The detailed experimental procedure\ncan be found in the revised manuscript (Page 35, line 8-15) or below for your reference.\n“Freshly prepared Cy5.5 dye (10 mg mL-1) was slowly added to probiotic suspensions\n(108 CFU mL-1). The mixtures were incubated at 37 oC for 2 h in the dark with gentle\nshaking, followed by repeated PBS washes until the supernatant was clear. The labeled\nprobiotic was then collected, and the FOS/CaCO encapsulation was performed on\n3\nintestinal tissues were collected 6 h post-administration for ex vivo fluorescence\nimaging using an IVIS Lumina XRMS Series III system (PerkinElmer).”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 16-Page\n14, line 1 and Page 14, line 3-Page 16, line 13) or below for your reference.\n40\n“To directly evaluate the gastrointestinal colonization capacity of the engineered\nprobiotic, an ex vivo tracking experiment using Cy5.5-labeled strains was performed.\nQuantitative fluorescence imaging of intestinal tissues revealed that REcN-FOS/CaCO\n3\nachieved the highest retention level among all groups (Fig. 3k,l). The FOS prebiotics\nimproved the retention of both strains compared to their unencapsulated counterparts.\nNotably, the fluorescent signal of REcN-FOS/CaCO was significantly greater than that\n3\nof EcN-FOS/CaCO , indicating that the ROS-tolerant phenotype of REcN also\n3\nenhanced gut colonization.”\nFig. 3k,l\nFor optimal dosing, our choice of thrice-weekly dosing was based on the well-\nestablished study using probiotic interventions in murine models of metabolic disease\n(e.g., Nat. Commun., 2022, 13, 4477). It represents a balance between providing a\nsufficient therapeutic payload and avoiding potential over-saturation or immune\noverstimulation.\nadaptive evolution process did not lead to the acquisition of any known horizontal\nantibiotic resistance genes. Also, we have conducted several key experiments to directly\naddress these concerns, which collectively demonstrate the robustness and safety\nprofile of REcN-F/Ca. The detailed results can be found in the revised manuscript\n(Page 9, line 7-10 and Page 13, line 11-15) or below for your reference.\n“The growth curve analysis revealed that REcN exhibited a faster growth rate during\nthe exponential phase compared to EcN, although both reach similar final cell densities\n(Supplementary Fig. 11). This enhanced growth kinetics likely contributes to its\ncompetitive advantage in the gut environment.”\nSupplementary Fig. 11\n“Quantitative real-time PCR (qRT-PCR) analysis revealed a significant 2.7-fold\nupregulation of the anti-inflammatory cytokine IL-10 transcript concomitant with a\n42\nsuppression of pro-inflammatory IL-1β and Tnf-α expression in macrophage cultures\nexposed to engineered probiotic (Fig. 3h-j).”\nFig. 3h-j\n6. Verify if SCFAs directly activate PPARα (reporter assays) and if PPARα knockout\nabolishes efficacy. Validate H₂S necessity via cysH/sseA knockout and exogenous H₂S\nrescue experiments.\nReply: We thank the reviewer for the excellent suggestion to directly test the causal\nrole of the PPARα signaling pathway in mediating the therapeutic effects of our\nengineered probiotic. The detail can be found in the revised manuscript (Page 18, line\n5-12 and Page 23, line 17-21) or below for your reference.\n“To establish a causal role for the PPARα pathway, we pharmacologically inhibited\nPPARα signaling in REcN-F/Ca-treated mice using the antagonist GW6471. The\nintervention largely abolished the metabolic benefits conferred by REcN-F/Ca.\nSpecifically, we observed a significant rebound in body weight, eAT weight, HOMA-\nIR index, and a marked deterioration in both insulin secretion and blood glucose levels\n43\nduring tolerance tests (Supplementary Fig. 25). The metabolic profile of this group\nreverted to a state closely resembling that of the HFD control group, demonstrating that\nthe host PPARα pathway is indispensable for the metabolic remediation by REcN-F/Ca.”\nSupplementary Fig. 25\n“Most importantly, the pharmacological inhibition of PPARα signaling almost\nabrogated the therapeutic effects of REcN-F/Ca, unequivocally demonstrating that the\nactivation of this host signaling pathway is not merely associated with, but is strictly\nnecessary for, the observed metabolic improvements.”\nTo unequivocally link H S production to the observed phenotype, we supplemented the\n2\nwild-type EcN culture with the H S donor NaHS (0.2 mM). The detail can be found in\n2\nthe revised manuscript (Page 8, line 21-Page 9, line 2) or below for your reference\n44\n“To establish a direct causal link between H S and ROS tolerance, we supplemented\n2\nthe wild-type EcN with the H S donor NaHS (0.2 mM). This intervention dramatically\n2\nincreased its H O MIC by 16-fold (Supplementary Fig. 9), demonstrating that H S\n2 2 2\nconfers a robust antioxidant phenotype.”\nSupplementary Fig. 9\n7. Some related references (such as Nat. Commun.,2022, 13, 3432; Biomaterials, 2024,\n309, 122584)\nReply: We thank the reviewer for bringing these highly relevant and excellent\nreferences to our attention. We have now carefully studied the suggested references\n(Nat. Commun., 2022, 13, 3432 and Biomaterials, 2024, 309, 122584) and have\nintegrated discussions of them into the revised manuscript to better position our work\nwithin the current scientific landscape.\n“9. Li, M. et al. Engineered probiotics with sustained release of interleukin-2 for the\n45\ntreatment of inflammatory bowel disease after oral delivery. Biomaterials 309, 122584\n(2024).\n12. Zhou, J. et al. Programmable probiotics modulate inflammation and gut microbiota\nfor inflammatory bowel disease treatment after effective oral delivery. Nat. Commun.\n13, 3432 (2022).”\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nReply: We thank the reviewer for the thorough and constructive assessment of our\nmanuscript. We also gratefully acknowledge the contribution of the Early Career\nResearcher who co-reviewed our work as part of the Nature Communications peer-\nreview training initiative. Their time and insightful input are greatly appreciated and\nhave contributed to strengthening our paper.\nThe manuscript presents a novel therapeutic strategy for type 2 diabetes based on the\nengineering of probiotics via directed evolution and surface display technology. The\nauthors provide a systematic evaluation, encompassing strain construction, in vitro\nfunctional characterization, multi-omics analysis, and in vivo efficacy studies, which\ncollectively demonstrate the considerable potential of this engineered strain in\nameliorating metabolic syndrome. However, to fully substantiate the scientific claims,\nthe authors must address the following issues with further experimental evidence and\nmore rigorous scientific discourse, as detailed below.\nReply: Thank you for this overall positive assessment. We have taken the request for\nfurther experimental evidence and more rigorous scientific discourse very seriously. In\nour point-by-point responses below, and throughout the revised manuscript, we have\nundertaken a substantial amount of new experimental work and deepened our\nmechanistic analysis to fully substantiate our scientific claims.\n1. The authors present the electron-dense layer observed in TEM images (Fig. 3a-b)\nas key evidence for the successful polymerization of FOS. However, the validity of this\nargument is challenged by the following: Firstly, in Fig. 3a, the unmodified REcN strain\nalso appears to exhibit a similar, albeit less electron-dense, boundary layer, which\nweakens the logic of uniquely attributing the structure in Fig. 3b to the FOS coating.\nSecondly, bacteria, especially Gram-negative strains, possess complex, multi-layered\ncell envelopes (e.g., outer membrane, periplasmic space) that can inherently appear\n48\nstratified under TEM. To provide unequivocal evidence, we strongly recommend the\nauthors supplement the manuscript with a high-resolution TEM image of an unmodified\nREcN control (from the same culture batch used for modification), acquired under\nidentical imaging and sample preparation conditions (including staining method,\nmagnification, image brightness, and contrast) as Fig. 3a-b. Only through such a\nrigorous side-by-side comparison can one convincingly distinguish the newly formed\nstructure resulting from FOS polymerization from the bacterium's intrinsic envelope\narchitecture.\nReply: We thank the reviewer for this critically important technical comment regarding\nthe validation of the FOS coating. We have supplemented the revised manuscript with\na high-resolution TEM image of an unmodified REcN control (Fig. 3a) and EcN\ncontrol (Supplementary Fig. 16, from the same culture batch used for modification),\nacquired under identical imaging and sample preparation conditions (including staining\nmethod, magnification, image brightness, and contrast). The detail can be found in the\nrevised manuscript (Page 11, line 16-Page 12, line 4) or below for your reference.\n“Transmission electron microscopy (TEM) imaging revealed a homogeneous electron-\nlucent layer (a thickness of approximately 60 nm) encapsulating REcN cell (Fig. 3a-b\nand Supplementary Fig. 16, red arrow), confirming successful FOS polymerization\n(designated REcN-FOS). Subsequent CaCO mineralization generated a dense\n3\ninorganic shell on REcN-FOS surfaces (Fig. 3c), with energy-dispersive X-ray\nspectroscopy (EDS) mapping demonstrating uniform Ca, C, and O distributions (Fig.\n49\n3c). Detection of nitrogen (N), a microbial biomass signature, confirmed bacterial\nstructural integrity post-modification (designated REcN-FOS/CaCO ). X-ray\n3\ndiffraction (XRD) analysis confirmed the successful mineralization with CaCO₃,\nidentifying the crystalline phase as calcite (Supplementary Fig. 17).”\nFig. 3a-b\nSupplementary Fig. 16\nSupplementary Fig. 17\n50\n2. We note an apparent contradiction: in simulated intestinal fluid (SIF), REcN-F/Ca\nexhibited lower viability than the uncoated REcN (Fig. 3e), yet it displayed the highest\nROS-scavenging activity (Fig. 3g). This raises questions about the source of this\nactivity. Is this antioxidant effect attributable to the live bacteria, the intrinsic chemical\nproperties of the coating materials (FOS/CaCO ), or contributions from bacterial\n3\nlysates?\nReply: We thank the reviewer for this insightful comment regarding the source of the\nantioxidant activity. We have now conducted a comprehensive set of experiments to\ndeconvolute the contributions of live bacteria, bacterial lysates, and the coating\nmaterials to the overall ROS-scavenging capacity. The detailed results can be found in\nthe revised manuscript (Page 12, line 19-Page 13, line 4) or below for your reference.\n“To determine the origin of the antioxidant activity, we compared •OH scavenging\nacross different components. Live REcN demonstrated the highest capacity,\nsignificantly exceeding that of live EcN (Supplementary Fig. 18). The lysates of both\nstrains also showed substantial activity, indicating that stable bacterial components\ncontribute significantly. The FOS/CaCO material itself possessed a baseline\n3\nscavenging ability, confirming that the overall effect of REcN-FOS/CaCO is a\n3\ncomposite of the evolved superior intrinsic ability, its released components, and the\ncoating matrix.”\n3. The authors attribute the lower survival rate of REcN-F/Ca in SIF (pH ≈ 6.8, per\nreference [35]) to insufficient dissolution of the CaCO shell. This explanation,\n3\nhowever, is in direct logical contradiction with the data showing superior protection in\nSICF (pH ≈ 7.8, per reference [35]), a condition where the shell's solubility should\nbe even lower (Fig. 3e vs. 3f). The authors should provide a more plausible explanation\nand explicitly state the formulations of all simulated fluids used.\nReply: We thank the reviewer for this critical observation, which has helped us\nsignificantly improve the physiological relevance of our gastrointestinal stability\nassessment. To accurately simulate the complete digestive journey, we developed a new\nprotocol where probiotic was sequentially exposed to SGF (20 min; containing pepsin\nand HCl, pH 1.2), then SIF (2 h; containing pancreatin in phosphate buffer, pH 6.8),\nand finally SICF (2 h; containing H O in phosphate buffer, pH 7.8), with viability\n2 2\nassessed after each step, rather than being co-cultured separately with the three types of\nsimulated liquids. The detailed experimental procedure (with the formulations of all\n52\nsimulated fluids) can be found in the revised manuscript (Page 34, line 6-11) or below\nfor your reference.\n“Probiotic (1×107 CFU mL-1) was first incubated in SGF (containing pepsin and HCl,\npH 1.2) for 20 min, then the probiotic was collected, resuspended, and transferred to\nSIF (containing pancreatin in phosphate buffer, pH 6.8) for 2 h, followed by a final\ntransfer to SICF (containing ammonium hydroxide, 200 μM H O in phosphate buffer)\n2 2\nfor 2 h. incubated in 1 mL of medium supplemented with either SGF, SIF, or SICF.\nViability (CFU count) was determined after each step.”\nAnd the detailed results can be found in the revised manuscript (Page 12, line 5-17) or\nbelow for your reference.\n“Subsequently, to rigorously evaluate the protective efficacy of the CaCO shell during\n3\nsequential GI transit, we subjected the probiotic to a simulated journey from the\nstomach to the inflamed colon. Given the GI transit times, with rapid gastric emptying\noccurring within approximately 20 min, followed by small intestinal transit for about 2\nh, and ultimately reaching the inflamed colon,[35] the viability and ROS-scavenging\ncapacity of EcN, REcN, and REcN-FOS/CaCO were assessed after first incubation for\n3\n20 min in simulated gastric fluid (SGF), then incubation for 2 h in simulated intestinal\nfluid (SIF), and finally incubation for 2 h in simulated inflammatory colon fluid (SICF).\nAfter each sequential challenge, REcN demonstrated greater activity than EcN (Fig.\n53\n3d-f), likely due to its superior energy metabolism that enables it to better withstand GI\nenvironmental assaults. Notably, the modification with CaCO further enhanced the\n3\nviability of the REcN probiotic, confirming the robust protective role of CaCO in the\n3\ndigestive tract.”\nFig. 3d-f\nTo directly validate the pH-responsive dissolution mechanism of the CaCO shell, we\n3\nquantified the release of Ca ions from REcN-FOS/CaCO in the different simulated\n3\nfluids using ICP-OES. The detailed experimental procedure can be found in the revised\nmanuscript (Page 35, line 2-7) or below for your reference.\n“REcN-FOS/CaCO (1×108 CFU mL-1) was incubated in 2 mL of medium\n3\nsupplemented with either SGF, SIF, or SICF. The incubation was conducted at 37 °C\n(SGF for 20 min, SIF for 2 h, and SICF for 2 h) with gentle shaking to evaluate their\nstabilities in the GI environment. The dissolution profile of the CaCO shell was\n3\n54\ncharacterized by measuring the concentration of released Ca ions in SGF, SIF, and SICF\nover time using inductively coupled plasma optical emission spectrometry (ICP-OES).”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 4-10) or\nbelow for your reference.\n“To functionally validate the pH-responsive behavior, we quantified the dissolution\nkinetics of the CaCO shell. Inductively coupled plasma optical emission spectrometry\n3\n(ICP-OES) analysis revealed a rapid release of Ca2+ ions in SGF (pH 1.2, ~50 mg L-1\nafter 20 min), contrasting with a slow, sustained release in SIF (pH 6.8, ~18 mg/L after\n2 h) and SICF (pH 7.8, ~12 mg/L after 2 h) (Supplementary Fig. 19). This controlled\ndissolution in the upper GI tract ensures that a maximal payload of viable REcN is\ndelivered to the target colonic environment.”\nSupplementary Fig. 19\n4. The authors should provide an experimental or theoretical rationale for selecting a\nsingle dose (5 × 108 CFU/mL) and frequency (thrice weekly). It should be explained\n55\nwhy a dose-response study was not conducted to investigate the dose-effect relationship\nof this therapy. Furthermore, the specific timing of the “thrice-weekly” administration\nmust be clarified to ensure experimental reproducibility.\nReply: We thank the reviewer for this important comment regarding the dosing\nregimen. This dose range (108–109 CFU/mL) is well-established and commonly\nreported as effective in numerous studies using probiotic interventions in murine\nmodels of disease (e.g., Nat. Commun., 2022, 13, 4477; Nat. Commun., 2022, 13, 3432).\nIt represents a balance between providing a sufficient therapeutic payload and avoiding\npotential over-saturation or immune overstimulation.\nWe acknowledge that a comprehensive dose-response study, while ideal, was not\nconducted within the scope of this initial proof-of-concept investigation. The primary\ngoal here was to establish a clear “proof-of-principle” for the efficacy of our engineered\nprobiotic against a stringent HFD control. Determining the optimal therapeutic dose\nand the minimum effective dose is a critical and logical next step in the translational\ndevelopment pathway, and we have now explicitly stated this as a objective for future\nstudies in the Discussion. The detail can be found in the revised manuscript (Page 25,\nline 1-5) or below for your reference.\n“Additionally, future investigations should systematically determine the optimal\ntherapeutic dose and the minimum effective dose. A comprehensive dose-response\nstudy represents a critical and logical next step in the translational development\n56\npathway, essential for maximizing therapeutic outcomes while ensuring safety and\ncost-effectiveness in potential future clinical applications.”\nWe have clarified the thrice-weekly schedule in the Methods section to ensure perfect\nreproducibility. The dosing was performed on a consistent schedule of Mondays,\nWednesdays, and Fridays each week. The detail can be found in the revised manuscript\n(Page 37, line 19-21) or below for your reference.\n“Pharmacokinetic-informed intervention consisting of 0.5 mL probiotic suspension (5\n× 108 CFU mL-1) was administered via orogastric gavage thrice weekly (at 9:00 AM on\nMonday, Wednesday, and Friday).”\n5. Given that FOS, a component of the delivery vehicle, is itself a prebiotic with known\nanti-diabetic effects, the current animal study lacks two critical control groups: a “F/Ca\nvehicle” group and a “EcN-F/Ca” group. Without these controls, the observed\ntherapeutic effects cannot be uniquely attributed to the ROS-tolerance-engineered\nREcN.\nReply: We thank the reviewer for this crucial comment, we have now conducted an\nadditional in vivo experiment that includes the two critical control groups. The detailed\nexperimental procedure can be found in the revised manuscript (Page 37, line 11-Page\n38, line 11) or below for your reference.\n57\n“Animal experiments were performed and approved by the Beatcell Model Biological\nCenter (Approval No. 2025-07-31A). Male C57BL/6J mice (n = 6, 6-week-old) were\nacclimatized in IVC cages under SPF conditions (22 ± 1 °C, 55% humidity, 12 h light-\ndark cycle) with autoclaved water and a standard feed. Following 2-week standard chow,\nmice underwent metabolic challenge via HFD for 10-week intervention, establishing a\nvalidated insulin-resistant prediabetic model. The animal study included six groups: 1)\nND group, 2) HFD group, 3) HFD+F/Ca vehicle group, 4) HFD+EcN-F/Ca group, 5)\nHFD+EcN-F/Ca group, and HFD+EcN-F/Ca+GW6471 (PPARα signaling inhibitor)\ngroup. Pharmacokinetic-informed intervention consisting of 0.5 mL probiotic\nsuspension (5 × 108 CFU mL-1) was administered via orogastric gavage thrice weekly\n(at 9:00 AM on Monday, Wednesday, and Friday). For HFD+EcN-F/Ca+GW6471\ngroup, mice were treated with GW6471 (20 mg kg-1 in DMSO) by intraperitoneal\ninjection after orogastric gavage. Weekly body weight measurements was recorded. At\nweek 10, fasting blood samples acquired via tail venipuncture were processed for\nHOMA-IR calculation, while fecal pellets underwent immediate flash-freezing for\nSCFAs quantification and gut microbiome analysis. IPGTT was conducted involving\nintraperitoneal D-glucose (2g kg-1, 20% w/v solution) with glycemic profiling at\n0/30/60/90/120 min. Concurrent serum insulin dynamics were assessed using ELISA.\nTerminal procedures at week 10 employed cervical dislocation under isoflurane\nanesthesia (3% induction), with subsequent tissue harvest utilizing aseptic\nmicrodissection techniques. The F4/80, CD86, and BODIPY in eAT and the 8-OhdG in\ncolon tissue were detected by immunofluorescence staining. And the main organs were\nstained by H&E.”\n16, line 13) or below for your reference.\n“To establish causal links between REcN-FOS/CaCO (REcN-F/Ca) supplementation\n3\nand metabolic improvement, a high-fat diet (HFD)-induced obesity murine model was\nemployed. Compared to normolipidic diet (ND)-fed controls, HFD-fed mice developed\npronounced obesity phenotypes, evidenced by elevated body weight gain (Δ+71.9%\nversus Δ+43.5%), peritesticular fat accumulation, and higher epididymal adipose tissue\n(eAT) weight (Fig. 4a-d). Additionally, the wild-type EcN probiotic encapsulated within\nthe protective shell demonstrated a mitigating effect on obesity, which can be attributed\nto the action of the EcN probiotic. The F/Ca shell showed a negligible inhibitory effect\non obesity. However, oral administration of REcN-F/Ca during HFD feeding mitigated\nobesity development, as evidenced by reduced body weight gain and fat accumulation\ncompared to HFD-fed mice that did not receive supplementation (Fig. 4a-d).\nMetabolic profiling revealed HFD-driven hyperglycemia and insulin resistance,\nboth ameliorated by REcN-F/Ca (Fig. 4e). During intraperitoneal glucose tolerance\ntesting (IPGTT), ND-fed mice exhibited transient increases in blood insulin levels\nfollowing intraperitoneal glucose injection, with a rapid return to baseline (Fig. 4f). In\ncontrast, HFD-fed mice exhibited a significant decline in blood insulin levels following\nthe glucose challenge (Fig. 4f). This pattern is indicative of failure to mount an\n59\nappropriate secretory response, a hallmark of T2DM pathology, rather than mere insulin\nresistance.[36] On the contrary, in mice fed with F/Ca, the blood insulin levels continued\nto rise after glucose injection, which is a typical characteristic of insulin resistance. This\nminor improvement was metabolically insufficient, as evidenced by the poor overall\nglucose tolerance and high HOMA-IR, which remained comparable to the HFD group.\nHowever, HFD-fed mice supplemented with REcN-F/Ca demonstrated insulin\nresponses comparable to those of ND-fed mice (Fig. 4f). Consistent with these\nobservations, the increases in blood glucose levels following intraperitoneal glucose\ninjection in HFD-fed mice were normalized to levels similar to those of ND-fed mice\nwhen supplemented with REcN-F/Ca (Fig. 4g).\nInflammation within the eAT is known to contribute to the development of obesity-\ninduced diabetes.[36] Histopathological evaluation of eAT in HFD and HFD+F/Ca\ngroups revealed M1 macrophage infiltration (Fig. 4h), a hallmark of obesity-associated\nadipose inflammation. In line with the inhibitory effects of REcN on diabetes\npathogenesis, the eAT of HFD-fed mice supplemented with REcN-F/Ca exhibited\nminimal macrophage accumulation (Fig. 4h). The administration of REcN significantly\nalso reduced the number of lipid droplets infiltrating the eAT of HFD-fed mice (Fig.\n4i,j). Additionally, RT-qPCR analysis indicated that the expression of S100a8 and Tnfα\n(Fig. 4k,l), which encode a chemokine that recruits macrophages and an inflammatory\ncytokine, respectively, was downregulated in the mature adipocyte fraction of the eAT\nin HFD-fed mice supplemented with REcN-F/Ca. Therefore, the administration of\nREcN-F/Ca not only inhibited body weight gain but also attenuated inflammatory\nresponses in the eAT of HFD-fed mice.\nNotably, colonic Pparα expression was upregulated in REcN-F/Ca-treated HFD mice\nversus ND mice (Fig. 4m). As a nuclear receptor regulating lipid oxidation and anti-\ninflammatory pathways, PPARα activation may mechanistically link metabolic benefits\nof REcN to transcriptional reprogramming of host energy utilization and inflammatory\nresponses. Owing to the superior antioxidant capacity of REcN, the colon tissues after\ntherapy showed the least oxidative stress (Fig. 4n,o). Furthermore, histopathological\nanalysis via hematoxylin and eosin (H&E) staining demonstrated distinct hepatic\nmorphological alterations across experimental cohorts. The ND group maintained intact\nhepatic lobular architecture with characteristic radial hepatocyte arrangement around\ncentral veins (Supplementary Fig. 21). Conversely, HFD group exhibited pronounced\nmicrovesicular and macrovesicular steatosis, accompanied by hepatocyte ballooning\ndegeneration. Notably, REcN-F/Ca intervention substantially attenuated HFD-induced\nhepatosteatosis. Critical extrahepatic organs (heart, spleen, lung, and kidney) displayed\npreserved histoarchitectural integrity across all groups, suggesting absence of\nmultiorgan toxicity after REcN-F/Ca treatment.”\n6. The results presented in Fig. 4f are puzzling. The authors observe that serum insulin\nlevels in HFD mice decreased following a glucose challenge. This appears to contradict\nthe established consensus in the field that HFD-induced insulin resistance is typically\naccompanied by a compensatory increase in insulin secretion to maintain glucose\nhomeostasis. Could the authors please clarify this observation? To enable proper\n62\ninterpretation of this important data, we ask the authors to provide more details or\ndiscuss this unexpected finding.\nReply: We thank the reviewer for the meticulous observation regarding the insulin\nsecretion dynamics, which has allowed us to provide a more nuanced and accurate\ninterpretation of our data. In our expanded animal study including the critical control\ngroups, we observed distinct insulin response patterns following a glucose challenge.\nThe HFD group showed a decline in insulin levels, confirming the presence of T2DM\npathology. This pattern aligns with observations in other HFD models, such as that\nreported by Hosomi, K. et al. (Nat. Commun., 2022, 13, 4477), and is characteristic of\nstage T2DM pathology. Interestingly, both the HFD+F/Ca and HFD+REcN-\nF/Ca+GW6471 (PPARα inhibited) groups exhibited a upward trend in insulin levels\nover time. However, this minor improvement was metabolically insufficient, as\nevidenced by their poor overall glucose tolerance and high HOMA-IR, which remained\ncomparable to the HFD group.\n7. In the analysis of epididymal adipose tissue inflammation, the authors conclude that\nREcN treatment reduces “pro-inflammatory M1-like macrophages” (Fig. 4h-i).\nHowever, the methodology and data presented only show staining for F4/80, a pan-\nmacrophage marker. This marker cannot, by itself, distinguish between M1 and M2\npolarization states. To substantiate this claim, immunofluorescence co-staining with\ncanonical M1 markers (e.g., iNOS, CD86) is essential. As it stands, the conclusion\nregarding M1-like macrophages is an over-interpretation of the available evidence.\nimmunofluorescence data. To directly and accurately address the phenotype of adipose\ntissue macrophages, we have performed additional multiplex immunofluorescence\nstaining on the eAT sections in our expanded animal study. And the detailed results can\nbe found in the revised manuscript (Page 15, line 9-13) or below for your reference.\n“Histopathological evaluation of eAT in HFD and HFD+F/Ca groups revealed M1\nmacrophage infiltration (Fig. 4h), a hallmark of obesity-associated adipose\ninflammation. In line with the inhibitory effects of REcN on diabetes pathogenesis, the\neAT of HFD-fed mice supplemented with REcN-F/Ca exhibited minimal macrophage\naccumulation (Fig. 4h).”\nFig. 4h\n8. The authors should supplement their analysis with a quantitative morphological\nanalysis of the BODIPY-stained adipocytes in Fig. 4h. This would not only provide a\ndirect cellular mechanism for the fat mass reduction reported in Fig. 4d but also robustly\nlink the gross phenotype to the histopathological changes.\nReply: We thank the reviewer for this excellent suggestion to provide a direct cellular\nmechanism for the observed reduction in epididymal fat mass. We have performed a\nquantitative morphometric analysis of the BODIPY-stained adipocytes using\n64\nautomated image analysis software (Aipathwell). And the detailed results can be found\nin the revised manuscript (Page 15, line 13-15) or below for your reference.\n“The administration of REcN significantly also reduced the number of lipid droplets\ninfiltrating the eAT of HFD-fed mice (Fig. 4i,j).”\nFig. 4i,j\n9. The central hypothesis of this study—that engineered ROS tolerance confers a\nsurvival and colonization advantage to REcN within the inflamed gut of T2DM mice—\nis an unproven core assumption. The manuscript lacks direct in vivo evidence to support\nthis critical assertion. To validate this foundational hypothesis, the authors could\nprovide data on: a) a quantitative analysis of ROS levels in the intestinal lumen of HFD\nversus ND mice to confirm the high-ROS pathological environment; and b)\nquantification of strain-specific DNA in fecal samples (via qPCR) to directly compare\n65\nthe long-term survival and colonization dynamics of REcN-F/Ca versus a coated, non-\nengineered control strain in vivo.\nReply: We thank the reviewer for this absolutely critical comment, which rightly\nidentifies the need for direct in vivo validation of our central hypothesis. We have\nperformed a quantitative analysis of ROS levels in the intestinal lumen by the 8-OHdG\nstaining using automated image analysis software (Aipathwell). And the detailed results\ncan be found in the revised manuscript (Page 16, line 3-4) or below for your reference.\n“Owing to the superior antioxidant capacity of REcN, the colon tissues after therapy\nshowed the least oxidative stress (Fig. 4n,o).”\nFig. 4n,o\nquantitatively compare the gastrointestinal retention of the different probiotic\nformulations. The detailed experimental procedure can be found in the revised\nmanuscript (Page 35, line 8-15) or below for your reference.\n“Freshly prepared Cy5.5 dye (10 mg mL-1) was slowly added to probiotic suspensions\n(108 CFU mL-1). The mixtures were incubated at 37 oC for 2 h in the dark with gentle\nshaking, followed by repeated PBS washes until the supernatant was clear. The labeled\nprobiotic was then collected, and the FOS/CaCO encapsulation was performed on\n3\nintestinal tissues were collected 6 h post-administration for ex vivo fluorescence\nimaging using an IVIS Lumina XRMS Series III system (PerkinElmer).”\nAnd the detailed results can be found in the revised manuscript (Page 13, line 16-Page\n14, line 1 and Page 14, line 3-Page 16, line 13) or below for your reference.\n“To directly evaluate the gastrointestinal colonization capacity of the engineered\nprobiotic, an ex vivo tracking experiment using Cy5.5-labeled strains was performed.\nQuantitative fluorescence imaging of intestinal tissues revealed that REcN-FOS/CaCO\n3\nachieved the highest retention level among all groups (Fig. 3k,l). The FOS prebiotics\nimproved the retention of both strains compared to their unencapsulated counterparts.\nNotably, the fluorescent signal of REcN-FOS/CaCO was significantly greater than that\n3\n67\nof EcN-FOS/CaCO , indicating that the ROS-tolerant phenotype of REcN also\n3\nenhanced gut colonization.”\nFig. 3k,l\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nReply: We thank the reviewer for the thorough and constructive assessment of our\nmanuscript. We also gratefully acknowledge the contribution of the Early Career\nResearcher who co-reviewed our work as part of the Nature Communications peer-\nreview training initiative. Their time and insightful input are greatly appreciated and\nhave contributed to strengthening our paper.\nResearch Overview and Contribution: This study introduces a novel strategy for\ntreating type 2 diabetes mellitus (T2DM) by engineering a reactive oxygen species\n(ROS)-tolerant E. coli Nissle 1917 (EcN) strain via iterative hydrogen peroxide\nexposure. The strain is encapsulated with fructooligosaccharides (FOS) and calcium\ncarbonate (CaCO ) to enhance gut survival, forming REcN-F/Ca. In a high-fat diet\n3\n(HFD)-induced mouse model, this engineered probiotic alleviated weight gain and\ninsulin resistance, likely via modulation of the gut microbiota and activation of PPARα\nsignaling.\nReply: We thank the reviewer for this concise articulation of the contribution of our\nstudy. To further strengthen the manuscript, we have incorporated the extensive\nadditional data and mechanistic validations detailed in our point-by-point responses.\n1. Key Strengths: Conceptual novelty: Pre-adapting probiotics to oxidative gut\nconditions represents a significant improvement over traditional strategies.\nMethodological scope: The study integrates microbial engineering, transcriptomics, in\nvitro assays, in vivo phenotyping, and microbiome analysis, offering a broad\nperspective on therapeutic impact.\nReply: Thank you for this positive assessment. We are pleased that the reviewer\nrecognizes the conceptual novelty of our pre-adaptation strategy and the comprehensive\nmethodological scope of our study.\n70\n2. Summary of Core Flaws and Final Recommendation: Despite its potential, the\ncurrent manuscript contains several fundamental flaws that preclude its publication in\na top-tier journal. The major issues can be summarized as: (1) flaws in experimental\ndesign due to the absence of essential control groups, (2) insufficient statistical power\nand inappropriate analytical methods, and (3) mechanistic claims based on unproven\ncorrelations rather than causal evidence.\nReply: Thank you for this final summary. We acknowledge the seriousness of these\nconcerns and have undertaken a comprehensive revision to address these core flaws\ndirectly. The revised manuscript now includes substantial new data and analyses that\nwe believe resolve these issues and significantly elevate rigor and impact of the study.\nFor flaws in experimental design due to the absence of essential control groups, we\nhave conducted a new, controlled in vivo study that includes the critical missing groups:\nF/Ca vehicle alone and EcN-F/Ca (the coated, non-evolved strain).\nFor insufficient statistical power and inappropriate analytical methods, we have\nincreased the statistical rigor throughout and ensured appropriate sample sizes\n(explicitly stated in all figure legends).\nFor mechanistic claims based on unproven correlations rather than causal evidence, we\nhave performed a critical in vivo intervention experiment using a specific PPARα\nantagonist GW6471.\n71\n3. Critical Flaws in Experimental Design and Controls: The paper’s biggest flaw is its\nexperimental design, which lacks essential control groups. Without comparing the\nengineered probiotic to the non-engineered version or testing the effects of the delivery\nmatrix alone, the authors cannot attribute the observed benefits specifically to their\nengineered strain. This omission introduces confounding variables that undermine the\nstudy’s main conclusions. Absence of a Wild-Type Probiotic Control: The manuscript\ncompares HFD mice treated with REcN-F/Ca to untreated HFD mice. This design\nmakes it impossible to determine whether the observed benefits are due to the novel\nROS-tolerance engineering or simply the general effects of the parent strain, EcN. The\npaper's central claim—that the directed evolution adaptation confers a therapeutic\nadvantage—is therefore entirely unsupported by the current data.\nRequired Action: The 10-week animal study must be repeated to include a HFD + wild-\ntype EcN (in the same FOS/CaCO vehicle) control group. Only a direct comparison\n3\nbetween REcN-F/Ca and EcN-F/Ca can isolate and quantify the added benefit of the\nROS-tolerance engineering.\nReply: We thank the reviewer for this crucial comment, we have now conducted an\nadditional in vivo experiment that includes the two critical control groups. The detailed\nexperimental procedure can be found in the revised manuscript (Page 37, line 11-Page\n38, line 11) or below for your reference.\n“Animal experiments were performed and approved by the Beatcell Model Biological\nCenter (Approval No. 2025-07-31A). Male C57BL/6J mice (n = 6, 6-week-old) were\n72\nacclimatized in IVC cages under SPF conditions (22 ± 1 °C, 55% humidity, 12 h light-\ndark cycle) with autoclaved water and a standard feed. Following 2-week standard chow,\nmice underwent metabolic challenge via HFD for 10-week intervention, establishing a\nvalidated insulin-resistant prediabetic model. The animal study included six groups: 1)\nND group, 2) HFD group, 3) HFD+F/Ca vehicle group, 4) HFD+EcN-F/Ca group, 5)\nHFD+EcN-F/Ca group, and HFD+EcN-F/Ca+GW6471 (PPARα signaling inhibitor)\ngroup. Pharmacokinetic-informed intervention consisting of 0.5 mL probiotic\nsuspension (5 × 108 CFU mL-1) was administered via orogastric gavage thrice weekly\n(at 9:00 AM on Monday, Wednesday, and Friday). For HFD+EcN-F/Ca+GW6471\ngroup, mice were treated with GW6471 (20 mg kg-1 in DMSO) by intraperitoneal\ninjection after orogastric gavage. Weekly body weight measurements was recorded. At\nweek 10, fasting blood samples acquired via tail venipuncture were processed for\nHOMA-IR calculation, while fecal pellets underwent immediate flash-freezing for\nSCFAs quantification and gut microbiome analysis. IPGTT was conducted involving\nintraperitoneal D-glucose (2g kg-1, 20% w/v solution) with glycemic profiling at\n0/30/60/90/120 min. Concurrent serum insulin dynamics were assessed using ELISA.\nTerminal procedures at week 10 employed cervical dislocation under isoflurane\nanesthesia (3% induction), with subsequent tissue harvest utilizing aseptic\nmicrodissection techniques. The F4/80, CD86, and BODIPY in eAT and the 8-OhdG in\ncolon tissue were detected by immunofluorescence staining. And the main organs were\nstained by H&E.”\n16, line 13) or below for your reference.\n“To establish causal links between REcN-FOS/CaCO (REcN-F/Ca) supplementation\n3\nand metabolic improvement, a high-fat diet (HFD)-induced obesity murine model was\nemployed. Compared to normolipidic diet (ND)-fed controls, HFD-fed mice developed\npronounced obesity phenotypes, evidenced by elevated body weight gain (Δ+71.9%\nversus Δ+43.5%), peritesticular fat accumulation, and higher epididymal adipose tissue\n(eAT) weight (Fig. 4a-d). Additionally, the wild-type EcN probiotic encapsulated within\nthe protective shell demonstrated a mitigating effect on obesity, which can be attributed\nto the action of the EcN probiotic. The F/Ca shell showed a negligible inhibitory effect\non obesity. However, oral administration of REcN-F/Ca during HFD feeding mitigated\nobesity development, as evidenced by reduced body weight gain and fat accumulation\ncompared to HFD-fed mice that did not receive supplementation (Fig. 4a-d).\nMetabolic profiling revealed HFD-driven hyperglycemia and insulin resistance,\nboth ameliorated by REcN-F/Ca (Fig. 4e). During intraperitoneal glucose tolerance\ntesting (IPGTT), ND-fed mice exhibited transient increases in blood insulin levels\nfollowing intraperitoneal glucose injection, with a rapid return to baseline (Fig. 4f). In\ncontrast, HFD-fed mice exhibited a significant decline in blood insulin levels following\nthe glucose challenge (Fig. 4f). This pattern is indicative of failure to mount an\n74\nappropriate secretory response, a hallmark of T2DM pathology, rather than mere insulin\nresistance.[36] On the contrary, in mice fed with F/Ca, the blood insulin levels continued\nto rise after glucose injection, which is a typical characteristic of insulin resistance. This\nminor improvement was metabolically insufficient, as evidenced by the poor overall\nglucose tolerance and high HOMA-IR, which remained comparable to the HFD group.\nHowever, HFD-fed mice supplemented with REcN-F/Ca demonstrated insulin\nresponses comparable to those of ND-fed mice (Fig. 4f). Consistent with these\nobservations, the increases in blood glucose levels following intraperitoneal glucose\ninjection in HFD-fed mice were normalized to levels similar to those of ND-fed mice\nwhen supplemented with REcN-F/Ca (Fig. 4g).\nInflammation within the eAT is known to contribute to the development of obesity-\ninduced diabetes.[36] Histopathological evaluation of eAT in HFD and HFD+F/Ca\ngroups revealed M1 macrophage infiltration (Fig. 4h), a hallmark of obesity-associated\nadipose inflammation. In line with the inhibitory effects of REcN on diabetes\npathogenesis, the eAT of HFD-fed mice supplemented with REcN-F/Ca exhibited\nminimal macrophage accumulation (Fig. 4h). The administration of REcN significantly\nalso reduced the number of lipid droplets infiltrating the eAT of HFD-fed mice (Fig.\n4i,j). Additionally, RT-qPCR analysis indicated that the expression of S100a8 and Tnfα\n(Fig. 4k,l), which encode a chemokine that recruits macrophages and an inflammatory\ncytokine, respectively, was downregulated in the mature adipocyte fraction of the eAT\nin HFD-fed mice supplemented with REcN-F/Ca. Therefore, the administration of\nREcN-F/Ca not only inhibited body weight gain but also attenuated inflammatory\nresponses in the eAT of HFD-fed mice.\nNotably, colonic Pparα expression was upregulated in REcN-F/Ca-treated HFD mice\n75\nversus ND mice (Fig. 4m). As a nuclear receptor regulating lipid oxidation and anti-\ninflammatory pathways, PPARα activation may mechanistically link metabolic benefits\nof REcN to transcriptional reprogramming of host energy utilization and inflammatory\nresponses. Owing to the superior antioxidant capacity of REcN, the colon tissues after\ntherapy showed the least oxidative stress (Fig. 4n,o). Furthermore, histopathological\nanalysis via hematoxylin and eosin (H&E) staining demonstrated distinct hepatic\nmorphological alterations across experimental cohorts. The ND group maintained intact\nhepatic lobular architecture with characteristic radial hepatocyte arrangement around\ncentral veins (Supplementary Fig. 21). Conversely, HFD group exhibited pronounced\nmicrovesicular and macrovesicular steatosis, accompanied by hepatocyte ballooning\ndegeneration. Notably, REcN-F/Ca intervention substantially attenuated HFD-induced\nhepatosteatosis. Critical extrahepatic organs (heart, spleen, lung, and kidney) displayed\npreserved histoarchitectural integrity across all groups, suggesting absence of\nmultiorgan toxicity after REcN-F/Ca treatment.”\n4. Absence of a Vehicle-Only Control: The encapsulation matrix contains\nfructooligosaccharides (FOS), a well-known prebiotic fiber. FOS itself can modulate\nthe gut microbiota, promote the growth of butyrate-producing bacteria (e.g.,\nLachnospiraceae), and improve metabolic health. The manuscript attributes the\nincrease in these bacteria and the restoration of SCFAs entirely to the action of REcN-\nmicrobiome could be partially or wholly attributable to the FOS vehicle.\nRequired Action: The animal study must include a HFD + FOS/CaCO vehicle-only\n3\ncontrol group. This is essential to disambiguate the effects of the prebiotic matrix from\nthose of the live probiotic.\nReply: We thank the reviewer for this crucial comment, we have now conducted an\nadditional in vivo experiment that includes the two critical control groups. The detailed\nexperimental procedure and results are as stated in the previous answer above.\n5. Limitations of the Animal Model: Preventive vs. Therapeutic Model: The current\nstudy uses a prevention model, where the probiotic is administered concurrently with\nthe HFD. While this shows mitigation of disease, it does not show reversal of\nestablished disease. For clinical relevance, a therapeutic model, where treatment begins\nafter obesity and insulin resistance are established, is far more meaningful.\n-Single-Sex Study: The exclusive use of male mice is a significant limitation, as\nmetabolic and immune responses can differ substantially in females. This sex bias limits\nthe generalizability of the findings.\n-Required Action: While performing a full therapeutic model study may be difficult\nduring revision, the authors must discuss these limitations in depth. It should be clearly\nstated that the efficacy in a therapeutic context and in females remains unknown and\nrequires future investigation.\nlimitations of our current animal model. We have addressed them by adding a dedicated\nparagraph in the Discussion section of our revised manuscript to explicitly discuss these\nissues and outline necessary future work. And the detail can be found in the revised\nmanuscript (Page 25, line 6-17) or below for your reference.\n“Furthermore, the therapeutic efficacy was demonstrated in a prevention model,\nwherein probiotic administration was initiated concurrently with the high-fat diet.\nAlthough this design effectively shows the capacity of REcN-F/Ca to counteract\nmetabolic dysfunction, future studies employing an intervention model—where\ntreatment begins after the establishment of obesity and insulin resistance—are essential\nto fully assess its clinical translational potential for treating existing disease. Finally,\nthis investigation was conducted exclusively in male mice. Given the well-documented\nsexual dimorphism in immune responses, gut microbiota composition, and metabolic\ndisease progression, evaluating the efficacy and mechanism of action of REcN-F/Ca in\nfemale subjects constitutes a critical and immediate future direction. Addressing these\naspects will be vital for comprehensively understanding the therapeutic scope of our\nbioengineered probiotic.”\n6. Inadequate Sample Size and Lack of Power Analysis: The manuscript relies on\ncritically small sample sizes for key conclusions, particularly SCFA measurements\n(Figure 6, n=3) and colonic gene expression analysis (Figure 5, n=3). The in vivo study\n79\n(n=6) is also on the low side for metabolic studies. The authors provide no justification\nor power analysis for these choices, raising serious concerns about the statistical power\nand reproducibility of the findings.\nRequired Action: The authors must provide a formal power analysis for the main in\nvivo endpoints. If possible, the sample size for SCFA and gene expression analysis in\nthe repeat experiment should be increased to enhance the reliability of the results.\nReply: We thank the reviewer for this critical comment regarding statistical rigor. In\nthe new, comprehensive in vivo experiment that includes the essential control groups\n(HFD+F/Ca vehicle and HFD+EcN-F/Ca), we have significantly increased the sample\nsizes to enhance the reliability of our conclusions. SCFAs measurements and colonic\ngene expression analysis now have n = 6 per group (increased from n = 3).\nFigure 5\n7. Data Reporting: For all key results, the authors must report exact p-values (e.g.,\np=0.034) instead of ranges (e.g., p<0.05). They should also report confidence intervals\nand/or effect sizes to provide a more complete picture. All figure captions must\nexplicitly state the statistical test used, the number of replicates (n), and what the error\nbars represent (e.g., mean ± SD).\nReply: We thank the reviewer for this important comment regarding statistical\ntransparency and reporting. We have comprehensively revised our statistical reporting\nand figure legends throughout the manuscript to address these points. All statistical\nresults in the text, figures, and supplementary material now report exact p-values\ninstead of ranges. The only exception is for p-values below 0.0001, which are reported\nas ****. For key comparisons in the main figures, we have added 95% confidence\n81\nintervals. Every figure legend now explicitly states the specific statistical test used for\neach analysis.\n8. Mechanistic Claims Lacking Causal Verification: The manuscript builds a strong\nnarrative, but relies on correlation without proving causation. It assumes that\nmicrobiome changes lead to PPARα activation, without ruling out alternative\nexplanations or providing direct mechanistic evidence.\nWithout experiments to test these links, the proposed pathway remains speculative.\nCorrelative Evidence for the PPARα/SCFA Axis: The central mechanistic claim—that\nREcN-F/Ca works by enriching butyrate-producing bacteria, whose SCFAs then\nactivate host PPARα signaling—is supported only by correlational data. The study\nshows these events occur concurrently but does not prove causation.\nRequired Action (to establish causality): The reviewers have provided an excellent\nroadmap. To truly strengthen the manuscript, the authors should consider (and if\npossible, perform):\n-To validate the mechanism, test whether blocking PPARα signaling with an inhibitor\n(e.g. GW6471) eliminates REcN-F/Ca’s effects, and use FMT to determine if\nmicrobiota changes alone can transfer the metabolic benefits.\n-If New Experiments Are Not Feasible: The authors are recommended to tone down\ntheir mechanistic claims throughout the manuscript. Phrasing like “driving” or\n“mediating” should be revised to “associating with,” and the Discussion should\n82\nexplicitly state that causality has not been established and the observed associations are\ncorrelational.\nReply: We thank the reviewer for this critical assessment and for providing a clear\nroadmap to establish causality. As suggested, we have performed a critical in vivo\nintervention experiment using a specific PPARα antagonist GW6471. The detail can be\nfound in the revised manuscript (Page 18, line 5-12 and Page 23, line 17-21) or below\nfor your reference.\n“To establish a causal role for the PPARα pathway, we pharmacologically inhibited\nPPARα signaling in REcN-F/Ca-treated mice using the antagonist GW6471. The\nintervention largely abolished the metabolic benefits conferred by REcN-F/Ca.\nSpecifically, we observed a significant rebound in body weight, eAT weight, HOMA-\nIR index, and a marked deterioration in both insulin secretion and blood glucose levels\nduring tolerance tests (Supplementary Fig. 25). The metabolic profile of this group\nreverted to a state closely resembling that of the HFD control group, demonstrating that\nthe host PPARα pathway is indispensable for the metabolic remediation by REcN-F/Ca.”\n“Most importantly, the pharmacological inhibition of PPARα signaling almost\nabrogated the therapeutic effects of REcN-F/Ca, unequivocally demonstrating that the\nactivation of this host signaling pathway is not merely associated with, but is strictly\nnecessary for, the observed metabolic improvements.”\n9. In Vivo Relevance of ROS Tolerance Unproven: The entire premise of the paper is\nbased on engineering a ROS-tolerant probiotic. The authors meticulously characterize\nthis trait in vitro (Figure 1). However, they provide no direct evidence that this\nenhanced ROS tolerance is functional or relevant in vivo. They do not measure whether\nREcN-F/Ca treatment actually reduces markers of oxidative stress (e.g., lipid\nperoxidation, 8-OHdG) in the colonic lumen or tissue of treated mice. This is a critical\nmissing link in the logical flow of the paper's narrative. Without this piece of data, the\n84\nentire “bioengineering for ROS tolerance” story is disconnected from the in vivo\noutcomes.\nRequired Action: The authors should analyze stored colon tissue from the animal study\nfor markers of oxidative stress. This would provide crucial evidence linking the in vitro\nengineered trait to an in vivo biological effect, a point raised in.\nReply: We thank the reviewer for this critical assessment. We have performed a\nquantitative analysis of ROS levels in the intestinal lumen by the 8-OHdG staining\nusing automated image analysis software (Aipathwell). And the detailed results can be\nfound in the revised manuscript (Page 16, line 3-4) or below for your reference.\n“Owing to the superior antioxidant capacity of REcN, the colon tissues after therapy\nshowed the least oxidative stress (Fig. 4n,o).”\nFig. 4n,o\nReviewer #1 (Remarks to the Author):\nThe authors have satisfactorily addressed many of the concerns raised in the previous\nreview. However, several points still require clarification and revision before the\nmanuscript can be deemed acceptable for publication.\nReply: We sincerely thank the reviewer for the continued engagement. We are pleased\nthat the manuscript has been strengthened through this iterative process. Below, we\nprovide point-by-point responses to the remaining issues requiring clarification and\nrevision.\n1. Regarding the rationale for selecting FOS and calcium carbonate: The authors have\nsupplemented the experimental design considerations in the Discussion section. It is\nrecommended that this content be relocated to the Introduction section, with additional\nreferences provided to support the design basis. For example, citing literature that\nvalidates the antacid effect of calcium carbonate as a key rationale for its inclusion.\nReply: Thank you for this constructive suggestion. In the revised manuscript, we have\nmoved and expanded the relevant explanation to the Introduction section. The detail\ncan be found in the revised manuscript (Page 4, line 11-17) or below for your reference.\n“While other prebiotics (e.g., inulin) exist, FOS has a shorter chain length than inulin,\nmaking it potentially more readily fermentable by a broader range of beneficial\nbacteria.[21] Unlike some encapsulation polymeric materials (e.g., chitosan, alginate)\n1\nthat may require complex synthesis or raise biocompatibility concerns, CaCO is a Food\n3\nand Drug Administration–approved antacid.[22] Its mineralization process is simple,\nscalable, and results in a highly stable, protective shell.[23]”\n21. Cheon S. et al. Comparative analysis of prebiotic effects of four oligosaccharides\nusing in vitro gut model: digestibility, microbiome, and metabolome changes.\nFEMS Microbiol. Ecol. 99, fiad002 (2023).\n22. Trushina, D. B., Borodina, T. N., Belyakov, S. & Antipina, M. N. Calcium carbonate\nvaterite particles for drug delivery: Advances and challenges. Mater. Today Adv. 14,\n100214 (2022).\n23. Lee, Y., Shin, S. & Kim, M. J. Production of CaCO -single-coated probiotics and\n3\nevaluation of their spectroscopic properties, morphological characteristics, viability,\nand intestinal delivery efficiency. Food Chem. 457, 140076 (2024).\n2. The reviewer strongly recommends incorporating whole-genome sequencing (WGS)\nand comparative genomics analysis of the evolved strains. This addition is essential\nbecause readers will naturally seek to understand the genetic changes underlying the\nimproved performance of REcN (e.g., the enhanced NADH dehydrogenase activity),\nwhich is critical for gaining mechanistic insights into its functional optimization. While\ntranscriptomic data can provide dynamic expression profiles, it is highly susceptible to\nenvironmental fluctuations and thus less robust for elucidating stable evolutionary\nmechanisms. In contrast, comparative genomics would offer a solid data foundation for\n2\nformulating mechanistic hypotheses linking domestication phenotypes, transcriptomic\nchanges, and genetic variations. Given the affordability and accessibility of genome\nsequencing, it remains unclear why the authors have not included this valuable dataset.\nReply: We sincerely thank the reviewer for the strong recommendation and valuable\ninsight regarding the importance of whole-genome sequencing (WGS). We have now\nperformed WGS and comparative genomic analysis of the ancestral EcN strain and the\nevolved REcN strain. The analysis has successfully identified a set of non-synonymous\nmutations that are highly responsible for the robust ROS-tolerant and metabolically\nenhanced phenotype of REcN. The detailed experimental procedure can be found in the\nrevised manuscript (Page 31, line 15-Page 33, line 1) or below for your reference.\n“Whole-genome sequencing and SNPs/InDels analysis\na) Genomic DNA extraction: The bacterial strains (EcN and REcN) were\ninoculated onto an LB agar plate and incubated overnight at 37 °C. A single colony was\npicked with an inoculation needle and transferred into 200 mL of LB liquid medium,\nfollowed by incubation at 37 °C with shaking until the logarithmic growth phase was\nreached. The bacterial pellet was collected by refrigerated centrifugation and washed\nwith sterile water to remove residual medium components. Genomic DNA was\nextracted and quantified, and high-quality DNA was used for subsequent library\nconstruction.\nb) Library construction and genome sequencing: Sequencing library was prepared\nusing the Illumina platform. Genomic DNA was fragmented to approximately 400 bp\n3\nusing a Covaris M220 Focused‑Acoustic Shearer. Library construction was performed\nwith the NEXTFLEX Rapid DNA‑Seq Kit. Adapter‑ligated fragments were enriched\nby PCR. The final library was subjected to paired‑end sequencing (2 × 150 bp) on an\nIllumina NovaSeq 6000.\nc) Sequencing data quality control: Initially, adapter sequences were removed from\nthe reads. The 5’ ends of reads were then trimmed to eliminate any bases that were not\nA, G, C, or T. Next, read ends with low sequencing quality (Phred score ≤ Q20) were\ntrimmed. Furthermore, reads containing more than 10% undetermined bases (N) were\nfiltered out. Finally, fragments shorter than 30 bp after adapter removal and quality\ntrimming were discarded.\nd) Read mapping: Clean reads were aligned to a designated reference genome\nusing the BWA‑MEM algorithm. PCR duplicates were identified and removed with\nPicard‑tools. Sequencing depth and genome coverage were calculated from the\nresulting BAM alignment files.\ne) SNP and InDel analysis: SNPs/InDels were detected using a standardized\nvariant‑calling pipeline. Initially, local realignment around InDel regions was\nperformed with GATK v4.3.0.0 to reduce false‑positive SNP calls. Variant calling was\nthen carried out with Snippy v4.6.0, applying filters for minimum sequencing depth and\nmapping quality. Detected variants were functionally annotated using SnpEff to predict\ntheir potential effects on coding and regulatory regions.”\nbelow for your reference.\n“Notably, whole-genome sequencing (WGS) with single‑nucleotide polymorphisms\n(SNPs) and insertions/deletions (InDels) analysis revealed that 6 missense mutations\nwere found in the nuoCD gene (Table 1 and Supplementary Table S1), which encodes\nNADH-quinone oxidoreductase subunit C/D (Supplementary Table S2). This offers a\nplausible genetic basis for the observed increase in NADH dehydrogenase activity,\nwhich we confirmed through the enzymatic assay. Directed H O selection pressure\n2 2\nfixed mutations in key metabolic component, which led to stable transcriptional\nreprogramming, resulting in the optimized functional phenotype.”\nTable 1\nGene name Gene ID Effects Type Location Ref Alt\nnuoCD gene1583 synonymous SNP 304081 T C\nnuoCD gene1583 synonymous SNP 304087 G A\nnuoCD gene1583 synonymous SNP 304096 C G\nnuoCD gene1583 missense SNP 304099 C G\nnuoCD gene1583 synonymous SNP 304117 G T\nnuoCD gene1583 missense SNP 304119 T A\nnuoCD gene1583 synonymous SNP 304123 A G\nnuoCD gene1583 synonymous SNP 304126 G C\nnuoCD gene1583 synonymous SNP 304129 T C\nnuoCD gene1583 synonymous SNP 304132 C T\nnuoCD gene1583 synonymous SNP 304159 G A\nnuoCD gene1583 synonymous SNP 304174 T C\nnuoCD gene1583 synonymous SNP 304204 A G\nnuoCD gene1583 synonymous SNP 304207 G T\nnuoCD gene1583 synonymous SNP 304210 G C\nnuoCD gene1583 synonymous SNP 304216 T C\nnuoCD gene1583 synonymous SNP 304222 G C\n5\nnuoCD gene1583 synonymous SNP 304228 T G\nnuoCD gene1583 synonymous SNP 304234 T C\nnuoCD gene1583 missense SNP 304238 T G\nnuoCD gene1583 missense SNP 304250 G A\nnuoCD gene1583 synonymous SNP 304252 T C\nnuoCD gene1583 synonymous SNP 304267 G T\nnuoCD gene1583 synonymous SNP 304276 T C\nnuoCD gene1583 synonymous SNP 304360 G C\nnuoCD gene1583 missense SNP 304371 G A\nnuoCD gene1583 missense SNP 304382 G A\nTable S1\nGene name Gene ID Effects Type Location Ref Alt\nrpsA gene0590 synonymous SNP 651486 C T\nrpsA gene0590 synonymous SNP 651492 T C\nrpsA gene0590 synonymous SNP 651525 A G\nrpsA gene0590 synonymous SNP 651537 A C\nrpsA gene0590 synonymous SNP 651552 G T\nrpsA gene0590 synonymous SNP 651555 T C\nrpsA gene0590 synonymous SNP 651561 T C\nrpsA gene0590 missense SNP 651562 C A\nrpsA gene0590 missense SNP 651563 T C\nrpsA gene0590 synonymous SNP 651585 T C\nrpsA gene0590 synonymous SNP 651588 A G\nrpsA gene0590 synonymous SNP 651594 A G\nrpsA gene0590 synonymous SNP 651606 G C\nrpsA gene0590 synonymous SNP 651639 T C\nrpsA gene0590 missense SNP 651643 G A\nrpsA gene0590 missense SNP 651644 C G\nrpsA gene0590 synonymous SNP 651648 T C\nrpsA gene0590 missense SNP 651649 A C\nrpsA gene0590 missense SNP 651651 C G\nrpsA gene0590 missense SNP 651655 T G\nrpsA gene0590 synonymous SNP 651660 A G\nrpsA gene0590 synonymous SNP 651669 A C\nrpsA gene0590 missense SNP 651693 C G\nrpsA gene0590 missense SNP 651706 A C\nrpsA gene0590 missense SNP 651707 T A\nrpsA gene0590 synonymous SNP 651738 T C\nrpsA gene0590 synonymous SNP 651771 T A\nrpsA gene0590 synonymous SNP 651783 G A\nrpsA gene0590 synonymous SNP 651792 T C\n6\nrpsA gene0590 synonymous SNP 651807 A G\nrpsA gene0590 missense SNP 651811 G A\nrpsA gene0590 synonymous SNP 651813 T C\nrpsA gene0590 missense SNP 651823 A T\nrpsA gene0590 missense SNP 651824 G C\nrpsA gene0590 synonymous SNP 651828 A G\nrpsA gene0590 synonymous SNP 651840 G T\nrpsA gene0590 synonymous SNP 651849 A G\nrpsA gene0590 synonymous SNP 651858 T C\nrpsA gene0590 synonymous SNP 651861 A G\nrpsA gene0590 synonymous SNP 651864 G C\nrpsA gene0590 synonymous SNP 651882 A G\nrpsA gene0590 missense SNP 651887 C A\nrpsA gene0590 synonymous SNP 651936 T C\nrpsA gene0590 synonymous SNP 651942 T G\nrpsA gene0590 missense SNP 651943 A G\nrpsA gene0590 synonymous SNP 651945 A G\nrpsA gene0590 missense SNP 651964 A C\nrpsA gene0590 missense SNP 651965 A G\nrpsA gene0590 missense SNP 651966 A C\nrpsA gene0590 missense SNP 651967 C G\nrpsA gene0590 synonymous SNP 651969 G C\nrpsA gene0590 synonymous SNP 651975 T C\nrpsA gene0590 synonymous SNP 651981 G C\nrpsA gene0590 synonymous SNP 651990 G C\nrpsA gene0590 synonymous SNP 652002 T C\nrpsA gene0590 synonymous SNP 652059 T C\nrpsA gene0590 synonymous SNP 652071 A G\nrpsA gene0590 synonymous SNP 652080 C T\nrpsA gene0590 synonymous SNP 652086 C G\nrpsA gene0590 synonymous SNP 652092 T C\nrpsA gene0590 missense SNP 652096 A C\nrpsA gene0590 missense SNP 652098 C G\nrpsA gene0590 missense SNP 652109 T A\nrpsA gene0590 missense SNP 652120 A C\nrpsA gene0590 missense SNP 652121 T A\nrpsA gene0590 synonymous SNP 652131 T C\nrpsA gene0590 synonymous SNP 652143 A G\nrpsA gene0590 missense SNP 652165 C A\nrpsA gene0590 synonymous SNP 652167 G C\nrpsA gene0590 synonymous SNP 652170 A G\nrpsA gene0590 missense SNP 652180 G T\nrpsA gene0590 synonymous SNP 652182 T C\nrpsA gene0590 missense SNP 652192 C G\n7\nrpsA gene0590 synonymous SNP 652194 G A\nrpsA gene0590 missense SNP 652195 C G\nrpsA gene0590 missense SNP 652197 G C\nrpsA gene0590 missense SNP 652201 G T\nrpsA gene0590 missense SNP 652206 A C\nrpsA gene0590 missense SNP 652208 C G\nrpsA gene0590 synonymous SNP 652221 C T\nrpsA gene0590 missense SNP 652228 G A\nrpsA gene0590 synonymous SNP 652230 T C\nrpsA gene0590 stop_gained SNP 652231 G T\nrpsA gene0590 missense SNP 652232 A C\nrpsA gene0590 missense SNP 652233 A C\nrpsA gene0590 missense SNP 652238 A C\nrpsA gene0590 missense SNP 652239 A C\nrpsA gene0590 synonymous SNP 652248 T G\nrpsA gene0590 synonymous SNP 652254 T C\nrpsA gene0590 synonymous SNP 652275 C T\nrpsA gene0590 synonymous SNP 652302 T C\nrpsA gene0590 synonymous SNP 652311 T C\nrpsA gene0590 synonymous SNP 652329 T A\nrpsA gene0590 missense SNP 652331 C T\nrpsA gene0590 synonymous SNP 652332 A C\nrpsA gene0590 synonymous SNP 652344 A C\nrpsA gene0590 missense SNP 652352 A G\nrpsA gene0590 missense SNP 652353 A C\nrpsA gene0590 missense SNP 652355 A T\nnarH gene2332 missense SNP 111587 G C\nnarH gene2332 missense SNP 111817 A C\nnarH gene2332 missense SNP 111820 A G\nnarH gene2332 missense SNP 111826 A G\nnarH gene2332 missense SNP 111827 A C\nnarH gene2332 synonymous SNP 111837 T C\nnarH gene2332 missense SNP 111838 A G\nnarH gene2332 synonymous SNP 111849 A G\nnarH gene2332 synonymous SNP 111867 T C\nnarH gene2332 synonymous SNP 111868 T C\nnarH gene2332 synonymous SNP 111879 G C\nnarH gene2332 synonymous SNP 111885 A G\nnarH gene2332 synonymous SNP 111891 T C\nnarH gene2332 synonymous SNP 111903 A G\nnarH gene2332 synonymous SNP 111906 T C\nnarH gene2332 synonymous SNP 111927 T G\nnarH gene2332 synonymous SNP 111933 T C\nnarH gene2332 synonymous SNP 111942 T C\n8\nnarH gene2332 synonymous SNP 111945 A G\nnarH gene2332 synonymous SNP 111948 A G\nnarH gene2332 synonymous SNP 111951 T C\nnarH gene2332 synonymous SNP 111975 T C\nnarH gene2332 synonymous SNP 111978 A G\nnarH gene2332 synonymous SNP 111984 T C\nnarH gene2332 synonymous SNP 111993 T G\nnarH gene2332 missense SNP 112003 A T\nnarH gene2332 synonymous SNP 112008 A C\nnarH gene2332 synonymous SNP 112020 A G\nnarH gene2332 synonymous SNP 112023 A G\nnarH gene2332 synonymous SNP 112047 T C\nnarH gene2332 synonymous SNP 112053 T C\nnarH gene2332 synonymous SNP 112074 T C\nnarH gene2332 synonymous SNP 112080 T C\nnarH gene2332 synonymous SNP 112083 T C\nnarH gene2332 synonymous SNP 112086 A G\nnarH gene2332 synonymous SNP 112098 G C\nnarH gene2332 synonymous SNP 112101 A C\nnarH gene2332 missense SNP 112102 A G\nnarH gene2332 synonymous SNP 112104 A C\nnarH gene2332 synonymous SNP 112107 T C\nnarH gene2332 synonymous SNP 112110 A G\nnarH gene2332 synonymous SNP 112113 A G\nnarH gene2332 synonymous SNP 112119 T C\nnarH gene2332 synonymous SNP 112125 T G\nnarH gene2332 synonymous SNP 112128 T C\nnarH gene2332 synonymous SNP 112134 T C\nnarH gene2332 synonymous SNP 112140 T C\nnarH gene2332 synonymous SNP 112152 G C\nrpsF gene2767 synonymous SNP 236551 T G\nrpsF gene2767 synonymous SNP 236554 T C\nrpsF gene2767 missense SNP 236555 A C\nrpsF gene2767 synonymous SNP 236560 C T\nrpsF gene2767 synonymous SNP 236563 T C\nrpsF gene2767 synonymous SNP 236566 T G\nrpsF gene2767 synonymous SNP 236581 G A\nrpsF gene2767 missense SNP 236586 C G\nrpsF gene2767 missense SNP 236594 A G\nrpsF gene2767 synonymous SNP 236602 C T\nrpsF gene2767 synonymous SNP 236608 T C\nrpsF gene2767 missense SNP 236609 G A\nrpsF gene2767 missense SNP 236610 C A\nrpsF gene2767 synonymous SNP 236611 T G\n9\nrpsF gene2767 missense SNP 236618 A G\nrpsF gene2767 missense SNP 236619 C A\nrpsF gene2767 synonymous SNP 236620 T A\nrpsF gene2767 missense SNP 236622 G A\nrpsF gene2767 synonymous SNP 236623 T A\nrpsF gene2767 missense SNP 236625 C A\nrpsF gene2767 synonymous SNP 236626 A C\nrpsF gene2767 missense SNP 236628 A G\nrpsF gene2767 missense SNP 236629 A C\natpD gene2870 missense SNP 23052 A G\natpD gene2870 synonymous SNP 23108 T C\natpD gene2870 synonymous SNP 23117 A C\natpD gene2870 synonymous SNP 23129 G A\natpD gene2870 missense SNP 23157 T A\natpD gene2870 synonymous SNP 23165 C T\natpD gene2870 synonymous SNP 23168 T C\natpD gene2870 synonymous SNP 23174 T C\natpD gene2870 synonymous SNP 23186 T C\natpD gene2870 synonymous SNP 23189 A G\natpD gene2870 synonymous SNP 23222 A G\natpD gene2870 missense SNP 23227 C A\natpD gene2870 synonymous SNP 23228 C G\natpD gene2870 missense SNP 23241 A C\natpD gene2870 missense SNP 23243 C G\natpD gene2870 synonymous SNP 23249 A G\natpD gene2870 missense SNP 23253 T G\natpD gene2870 synonymous SNP 23261 G A\natpD gene2870 synonymous SNP 23264 T C\natpD gene2870 synonymous SNP 23288 A C\natpD gene2870 synonymous SNP 23303 T C\natpD gene2870 synonymous SNP 23306 T A\natpD gene2870 synonymous SNP 23315 T C\natpD gene2870 synonymous SNP 23327 T C\natpD gene2870 synonymous SNP 23333 A G\natpD gene2870 synonymous SNP 23348 T C\natpD gene2870 synonymous SNP 23357 A T\natpD gene2870 synonymous SNP 23358 T C\natpD gene2870 synonymous SNP 23361 C T\natpD gene2870 missense SNP 23367 G A\natpD gene2870 synonymous SNP 23372 T C\natpD gene2870 synonymous SNP 23381 T C\natpD gene2870 synonymous SNP 23393 G C\natpD gene2870 synonymous SNP 23432 T G\natpD gene2870 synonymous SNP 23435 A C\n10\natpD gene2870 synonymous SNP 23441 A G\natpD gene2870 synonymous SNP 23444 T C\natpD gene2870 synonymous SNP 23462 G C\natpD gene2870 synonymous SNP 23486 A G\natpD gene2870 synonymous SNP 23489 T C\natpD gene2870 synonymous SNP 23504 A G\natpD gene2870 missense SNP 23506 C A\natpD gene2870 synonymous SNP 23507 C A\natpD gene2870 synonymous SNP 23510 T C\natpD gene2870 synonymous SNP 23513 T G\natpD gene2870 synonymous SNP 23543 T C\natpD gene2870 synonymous SNP 23549 T C\natpD gene2870 synonymous SNP 23553 T C\natpD gene2870 synonymous SNP 23558 T C\natpD gene2870 synonymous SNP 23567 T C\natpD gene2870 synonymous SNP 23573 A G\natpD gene2870 synonymous SNP 23585 G C\natpD gene2870 synonymous SNP 23696 T C\natpD gene2870 synonymous SNP 23741 A G\natpD gene2870 synonymous SNP 23744 T C\natpD gene2870 synonymous SNP 23747 T C\natpD gene2870 missense SNP 23748 C A\natpD gene2870 synonymous SNP 23765 T C\natpD gene2870 synonymous SNP 23771 C G\natpD gene2870 synonymous SNP 23780 T C\natpD gene2870 missense SNP 23800 A C\natpD gene2870 missense SNP 23801 A C\natpD gene2870 synonymous SNP 23864 G A\natpD gene2870 synonymous SNP 23867 A G\natpD gene2870 synonymous SNP 23873 A C\natpD gene2870 synonymous SNP 23882 T C\natpD gene2870 synonymous SNP 23885 T G\natpD gene2870 synonymous SNP 23891 T C\natpD gene2870 synonymous SNP 23894 A G\natpD gene2870 synonymous SNP 23900 C T\natpD gene2870 synonymous SNP 23909 A G\natpD gene2870 missense SNP 23919 C G\natpD gene2870 missense SNP 23920 G C\natpD gene2870 synonymous SNP 23927 T C\natpD gene2870 synonymous SNP 23930 A G\natpD gene2870 synonymous SNP 23936 C T\natpD gene2870 missense SNP 23937 A C\natpD gene2870 missense SNP 23939 G C\natpD gene2870 missense SNP 23940 G A\n11\natpD gene2870 missense SNP 23942 A C\natpD gene2870 missense SNP 23948 A C\natpD gene2870 synonymous SNP 24008 A G\nbtsT gene3437 synonymous SNP 163457 A G\nbtsT gene3437 missense SNP 163500 G A\nbtsT gene3437 missense SNP 163512 C A\nbtsT gene3437 synonymous SNP 163514 G C\nbtsT gene3437 missense SNP 163524 G A\nbtsT gene3437 synonymous SNP 163526 G C\nbtsT gene3437 missense SNP 163527 C G\nbtsT gene3437 synonymous SNP 163529 G C\nbtsT gene3437 missense SNP 163531 A T\nbtsT gene3437 missense SNP 163532 C G\nbtsT gene3437 synonymous SNP 163544 A G\nbtsT gene3437 synonymous SNP 163550 T G\nbtsT gene3437 missense SNP 163564 A T\nbtsT gene3437 missense SNP 163567 T C\nbtsT gene3437 synonymous SNP 163568 T C\nbtsT gene3437 synonymous SNP 163574 T C\nbtsT gene3437 synonymous SNP 163577 T C\nbtsT gene3437 missense SNP 163584 C G\nbtsT gene3437 synonymous SNP 163586 G C\nbtsT gene3437 synonymous SNP 163631 T C\nbtsT gene3437 synonymous SNP 163634 T C\nbtsT gene3437 synonymous SNP 163640 A G\nbtsT gene3437 synonymous SNP 163643 T C\nbtsT gene3437 synonymous SNP 163664 T C\nbtsT gene3437 synonymous SNP 163667 C G\nbtsT gene3437 synonymous SNP 163670 T G\nbtsT gene3437 synonymous SNP 163673 G C\nbtsT gene3437 synonymous SNP 163679 A G\nbtsT gene3437 synonymous SNP 163682 A G\nbtsT gene3437 synonymous SNP 163688 G C\nbtsT gene3437 missense SNP 163689 G A\nbtsT gene3437 missense SNP 163690 C A\nbtsT gene3437 synonymous SNP 163691 T C\nbtsT gene3437 missense SNP 163692 A C\nbtsT gene3437 missense SNP 163693 A G\nbtsT gene3437 synonymous SNP 163694 T C\nbtsT gene3437 synonymous SNP 163697 A G\nbtsT gene3437 missense SNP 163698 A C\nbtsT gene3437 synonymous SNP 163706 G C\nbtsT gene3437 synonymous SNP 163709 T C\nbtsT gene3437 missense SNP 163711 T A\n12\nbtsT gene3437 missense SNP 163726 C G\nbtsT gene3437 synonymous SNP 163727 A C\ntuf gene4295 synonymous SNP 145 A G\ntuf gene4295 synonymous SNP 154 T C\ntuf gene4295 missense SNP 164 C G\ntuf gene4295 missense SNP 165 A C\ntuf gene4295 synonymous SNP 166 C T\ntuf gene4295 synonymous SNP 175 G C\ntuf gene4295 missense SNP 181 C A\ntuf gene4295 synonymous SNP 184 C T\ntuf gene4295 synonymous SNP 187 T C\ntuf gene4295 synonymous SNP 193 T C\ntuf gene4295 synonymous SNP 199 A G\ntuf gene4295 synonymous SNP 205 T C\ntuf gene4295 synonymous SNP 229 G C\nrpoC gene4428 synonymous SNP 10429 T C\nrpoC gene4428 synonymous SNP 10441 T C\nrpoC gene4428 synonymous SNP 10450 T G\nrpoC gene4428 synonymous SNP 10453 T A\nrpoC gene4428 synonymous SNP 10465 T C\nrpoC gene4428 synonymous SNP 10474 G C\nrpoC gene4428 synonymous SNP 10483 T C\nrpoC gene4428 synonymous SNP 10489 C G\nrpoC gene4428 synonymous SNP 10498 A G\nrpoC gene4428 synonymous SNP 10501 A C\nrpoC gene4428 synonymous SNP 10504 A G\nrpoC gene4428 synonymous SNP 10528 T C\nrpoC gene4428 synonymous SNP 10573 A G\nrpoC gene4428 synonymous SNP 10591 A G\nrpoC gene4428 synonymous SNP 10597 A G\nrpoC gene4428 synonymous SNP 10600 T C\nrpoC gene4428 synonymous SNP 10621 T C\nrpoC gene4428 synonymous SNP 10633 T C\nrpoC gene4428 synonymous SNP 10642 G C\nrpoC gene4428 synonymous SNP 10648 C T\nTable S2\nGene name KO KEGG Definition\nrpsA K02945 small subunit ribosomal protein S1\nnuoCD K13378 NADH-quinone oxidoreductase subunit C/D\nnarH K00371 nitrate reductase/nitrite oxidoreductase, beta subunit\nrpsF K02990 small subunit ribosomal protein S6\n13\natpD K02112 F-type H+/Na+-transporting ATPase subunit beta\nbtsT K23676 pyruvate/proton symporter\nrpoC K03046 DNA-directed RNA polymerase subunit beta’\n3. The authors replaced References 5–7 to support the following claim: “While\npharmacological interventions (e.g., PPAR agonists and GLP-1 analogs) offer\nsymptomatic relief, their long-term efficacy is limited by an increased risk of side\neffects and failure to address gut microbiota dysbiosis—a hallmark of metabolic\ndysfunction.[5-7]” However, the current References 5–7 only provide support for GLP-\n1 analogs and lack relevant evidence for PPAR agonists. Additional references should\nbe supplemented to validate the limitations of PPAR agonists as stated in the sentence.\nReply: Thank you for this precise and correct observation. We sincerely apologize for\nthe oversight in our previous revision. We have now identified and incorporated two\nkey references (8 and 9) that directly address the specified limitations of PPAR agonists,\nthereby strengthening the foundation of our statement.\n5. Sodhi, M., Rezaeianzadeh, R., Kezouh, A. & Etminan, M. Risk of gastrointestinal\nadverse events associated with glucagon-like peptide-1 receptor agonists for weight\nloss. JAMA 330, 1795–1797 (2023).\n6. Qi, Q. et al. Hydrogen sulfide produced by the gut microbiota impairs host\nmetabolism via reducing GLP-1 levels in male mice. Nat. Metab. 6, 1601–1615\n(2024).\n7. Yun, C. et al. The microbial metabolite agmatine acts as an FXR agonist to promote\npolycystic ovary syndrome in female mice. Nat. Metab. 6, 947–962 (2024).\n14\n8. Hu, D. et al. Characterizing the mechanism of thiazolidinedione-induced\nhepatotoxicity: An in vitro model in mitochondria. Toxicol. Appl. Pharmacol. 284,\n134–141 (2015).\n9. Hodel C. Myopathy and rhabdomyolysis with lipid-lowering drugs. Toxicol. Lett.\n128, 159–168 (2002).\nI think that the authors have satisfactorily addressed the comments provided with the\noriginal version, and I believe the paper is suitable for publication.\nReply: We are deeply grateful to the reviewer for the enthusiastic support of our work\nand the positive assessment.\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nReply: We thank the reviewer for the continued engagement. We extend our sincere\nthanks to both the main reviewer and the co-reviewing Early Career Researcher for\ntheir time, careful evaluation, and insightful comments, which have collectively\nstrengthened our work.\nThe authors have satisfactorily addressed all my concerns with a high level of rigor.\nMost notably, the inclusion of the comprehensive new in vivo study with the critical\ncontrol groups (F/Ca vehicle and wild-type EcN-F/Ca) has resolved the major flaw in\nthe original experimental design. These data robustly support the conclusion that the\nengineered ROS tolerance—rather than the delivery vehicle or the parental strain—is\nthe primary driver of the observed therapeutic efficacy. Furthermore, the additional\nmechanistic evidence, particularly regarding in vivo oxidative stress reduction (8-\nOHdG), macrophage polarization, and colonization kinetics, has significantly\nstrengthened the manuscript. I therefore recommend acceptance.\nReply: We are extremely grateful to the reviewer for this highly positive evaluation\nand for the recommendation of acceptance.\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nReply: We thank the reviewer for the continued engagement. We extend our sincere\nappreciation to both the main reviewer and the co-reviewer for their time, careful\nconsideration, and constructive feedback, which have significantly contributed to\nimproving our manuscript.\n19"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have satisfactorily addressed the comments provided with the original version, and I believe the paper is\nsuitable for publication.", "reviewer_2": "I think that the authors have satisfactorily addressed the comments provided with the original version, and I believe the paper\nis suitable for publication.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.", "reviewer_4": "The authors have satisfactorily addressed all my concerns with a high level of rigor. Most notably, the inclusion of the\ncomprehensive new in vivo study with the critical control groups (F/Ca vehicle and wild-type EcN-F/Ca) has resolved the\nmajor flaw in the original experimental design. These data robustly support the conclusion that the engineered ROS\ntolerance—rather than the delivery vehicle or the parental strain—is the primary driver of the observed therapeutic efficacy.\nFurthermore, the additional mechanistic evidence, particularly regarding in vivo oxidative stress reduction (8-OHdG),\nmacrophage polarization, and colonization kinetics, has significantly strengthened the manuscript. I therefore recommend\nacceptance.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": ""}, {"round": 3, "reviewer_comments": {"reviewer_1": "The authors have satisfactorily addressed the comments provided with the original version, and I believe the paper is\nsuitable for publication."}, "author_response": ""}]

Decision letter