Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

Achieving efficient microbial conversion of lignocellulosic biomass requires in-depth understanding of how corn stover hydrolysate compositions influences the cellular physiology and formation of products of interest. In this we evaluated the performance of R. toruloides on four DMR-EH treated corn stover hydrolysates (CSH-1, CSH-2, CSH-3 and CSH-4) with distinct compositional profiles, focusing on the bisabolene production and proteomic adaptation. We further evaluated the effects of compounds identified in CSH as well as the combined effects of calcium, iron and sodium in a mixture. Of all the hydrolysates studied, CHS-4 with low calcium, iron, and sodium supported the highest bisabolene titer (0.010 M) and yield (0.02 mol/mol of sugar consumed), accompanied by proteomic shifts that favor sulfur metabolism and reduced iron–sulfur cluster activity. These results reveal that the composition of metal ions in CSH drives metabolic adaptation in R.toruloides. A Scheffé cubic mixture design was used to model the interactive effects of FeCl3·6H2O, Na2SO4, and CaCl2·2H2O on the growth of R. toruloides. The model revealed strong nonlinear blending effects, with high predictive accuracy (R2 = 0.93) and excellent reproducibility (R2 = 0.9587) as well as predictive power (R2 = 0.765). These results provide a basis for predictive hydrolysate optimization in bioprocessing.

Microbes in natural environments often encounter diverse mixtures of organic compounds, yet how mixed substrate environments and their molecular composition shape microbial phenotypes remains understudied. Here, we examined how a defined fungal exudate mimic (FEM) mixture influences growth and metabolism in Pseudomonas putida KT2440 compared to individual substrates matched for total carbon and nitrogen. Growth on FEM initiated 2 h earlier than growth on glucose alone and exhibited both the lowest lag and shortest time to maximum biomass compared to individual substrates. Fructose was the only individual substrate that supported significantly higher maximum biomass than FEM, but exhibited a nearly 15-fold longer lag phase. Gas chromatography mass spectrometry analysis revealed dynamic temporal patterns of substrate utilization within the FEM mixture, with early preferential utilization of malate, followed by overlapping utilization of multiple substrates between 3 and 8 h. By integrating growth and substrate uptake kinetics with genome-scale metabolic modeling and validating model-predicted pathway activity using temporal proteomics, we show that experimentally constrained model predictions accurately captured substrate utilization dynamics across multiple FEM concentrations, and predicted temporal shifts in the dominant substrates supporting growth. Through this integrative experimental-modeling approach, we demonstrate that the mixed substrate FEM environment elicits an emergent growth phenotype characterized by the lowest lag, shortest time to maximum biomass, and relatively high maximum biomass in Pseudomonas putida, a combination of traits not simultaneously reproduced by any individual substrate. IMPORTANCE:How mixed-nutrient substrate environments influence bacterial growth and metabolism is not well understood and is challenging to predictively model. Using Pseudomonas putida KT2440, we show that growth on a defined mixture of substrates inspired by mycorrhizal fungal hyphal exudates produces a distinct and emergent growth phenotype characterized by a lower lag, shorter time to maximum biomass, and relatively high biomass accumulation when compared to individual substrates alone. This combination of growth traits is not simultaneously reproduced by any individual substrate, even when total carbon and nitrogen are matched. By integrating growth measurements and temporal substrate uptake data with dynamic flux balance analysis and proteomics, we demonstrate that metabolic responses to mixed substrates can be quantitatively interpreted. These findings highlight the importance of studying microbes under chemically realistic conditions and suggest that learning from naturally occurring molecular environments may provide new strategies for engineering microbial growth conditions and improving bioprocess performance.

The soil microbiome plays a vital role in key ecosystem processes, but its functional capacity remains poorly understood. Microbial activities underpin many applications in environmental biotechnology, such as nutrient cycling, contaminant degradation, and the recovery and transformation of minerals and elements. However, analyzing the complex soil metaproteome is challenging. Here, we propose an approach to explore soil metaproteomes, which will improve our understanding of the metabolic potential within the soil microbiome. As a proof of concept, we generated high-quality metaproteomes from native prairie soil using high-resolution tandem mass spectrometry. Over 15,000 peptides were identified using paired metagenomes. By using lowest common ancestor method, the peptides were conservatively assigned to 21 bacterial, fungal, and archaeal phyla or superphyla, including rare soil bacterial phyla such as Candidatus Tectomicrobia, as well as viruses. Functional analysis at the pathway level was performed using complementary KEGG and MetaCyc databases, revealing essential biogeochemical cycles, such as carbon and sulfur cycling. By combining taxonomic and functional analyses, we disentangled the relative contributions of individual soil microbial phylum-level taxon to community metabolic functions. This study highlights the importance of taxon-resolved functional analysis enabled by soil metaproteomics, surpassing the capabilities of other single-omics methods. It offers new insights into how individual microbes function within complex soil microbiomes, paving the way for more targeted microbial strategies to improve system performance in bioeconomy applications.

Hydrogenosomes are mitochondrion-derived organelles that produce ATP and H2 to support energy metabolism in anaerobic eukaryotes. H2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H2 production in anaerobic eukaryotes remain incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P)+ and link electron transfer to H2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H2 production in the AF Caecomyces churrovis. Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H2:NAD+ oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE and NuoF) in C. churrovis and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme known from anaerobic prokaryotes. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex for H2 production in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H2 production and altering fungal metabolism. IMPORTANCE:H2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H2 production in Neocallimastix was first reported, the molecular mechanism for hydrogenosomal H2 production and redox balance remains unclear. We demonstrate that AF produce H2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H2-producing systems.

Circadian rhythms, driven by 24-h molecular oscillators, or "clocks", widely tune physiology to the daily rhythms of light and dark to enhance organismal fitness. In mammals, the cellular immune response is tightly regulated by these rhythms such that immunometabolic output is coordinated across the day, consolidating macrophage physiology into temporally distinct phases that determine the macrophage response to stimuli. Importantly, key proteins in the macrophage response to viral infection have been found to be under circadian control, and time of day of adjuvant application is known to affect the efficacy of vaccinations, including in the case of the SARS-CoV-2 virus. However, little is known about the molecular changes that underly the temporal response to vaccine application. Therefore, to investigate the circadian response of macrophage physiology to adjuvant exposure, we exposed primary mouse and human macrophages to the SARS-CoV-1 and CoV-2 spike proteins at different times over the circadian day. To further explore the time-of-day effect, we performed a multi-omics analysis and in vitro tissue culture assays examining macrophage responses over circadian time. We found that, conserved across the species, the timing of spike protein exposure dictated two distinct temporal responses which were characterized by hallmarks of immunometabolic suppression and modest immunometabolic activation. Intriguingly, these temporal responses were driven by central metabolic and mitochondrial changes rather than classical immune activation, suggesting immunometabolic control is a primary regulator of the temporal response of immune cells to stimuli.

Earlier detection is strongly associated with increased survival for women with ovarian cancer. Unfortunately, current screening strategies, employing serial serum or ultrasound assessments, lack adequate sensitivity and specificity for use in the low-prevalence general population. In contrast, screening for cervical cancer by Pap tests has been routinely performed for over 50 years. Since ovarian cancer cells have been observed in Pap tests, ovarian cancer protein biomarkers may also be present; yet Pap samples have not been rigorously examined for diagnostic proteins. Assessment of cervical effluent, as can be collected in a Pap test, has the potential to differentiate ovarian cancer cases from healthy controls, and thereby demonstrate that intra-abdominal pathology may be detected using this commonly acquired specimen. We hypothesize that proteins shed by ovarian cancer cells can be detected in the SurePath™ liquid-based Pap test fixative using mass spectrometry (MS)-based proteomics, making it possible to distinguish women with ovarian cancer from healthy women. Candidate ovarian cancer biomarkers were successfully identified in liquid-based Pap test samples from 20 cases of high grade serous ovarian cancer, 10 benign ovarian conditions, and 10 healthy control samples, by performing Tandem Mass Tag™ isobaric labeling, 2D liquid chromatography-MS/MS, and bioinformatics integration. Selected reaction monitoring (SRM) MS-based targeted proteomics was then performed using a panel of candidate biomarkers to quantify their abundance in an expanded patient cohort of 90 liquid-based Pap tests. A multi-protein classifier was developed using the SRM-MS data comprised of 6 proteins and achieving an AUC of 0.880 (95

ABSTRACT Genome-scale metabolic models (GEMs) are powerful tools for predicting cellular phenotypes and guiding microbial strain engineering, yet broad adoption remains challenging due to the computational expertise required. To overcome that, we present ChatGEM, an agentic platform that enables interactive GEM simulation through natural language. Built on the multi-agent ADEPT framework, ChatGEM integrates COBRApy within a retrieval-augmented generation (RAG) architecture that coordinates code generation and execution through specialized agents. Benchmarking across three tasks of increasing complexity showed that RAG-enabled code generation improved the mean overall performance score from 2.63 to 4.20 while reducing the execution time significantly starting from routine to complex tasks. Application of ChatGEM using an enzyme-constrained GEM (ecGEM) for four engineered Pseudomonas putida KT2440 strains identified the constitutive strain as the optimal chassis for succinate overproduction using a succinate leakage index - a prediction observed experimentally. Therefore, ChatGEM democratizes metabolic modeling by enabling researchers without computational expertise to perform sophisticated GEM-based analyses through natural language, and, hence, accelerating scientific discovery.

Lipomyces starkeyi is an oleaginous yeast with a native metabolism well-suited for production of lipids and biofuels from complex lignocellulosic and waste feedstocks. Recent advances in genetic engineering tools have facilitated the development of L. starkeyi into a microbial chassis for biofuel and chemical production. However, the feasibility of redirecting L. starkeyi lipid flux away from lipids and towards other products remains relatively unexplored. Here, we engineer the native metabolism to produce malic acid by introducing the reductive TCA pathway and a C4-dicarboxylic acid transporter to the yeast. Heterogeneous expression of two genes, the Aspergillus oryzae malate transporter and malate dehydrogenase, enabled L. starkeyi malic acid production. Overexpression of a third gene, the native pyruvate carboxylase, allowed titers to reach approximately 10 g/L during shaking flasks cultivations, with production of malic acid inhibited at pH values less than 4. Corn-stover hydrolysates were found to be well-tolerated, and controlled bioreactor fermentations on the real hydrolysate produced 26.5 g/L of malic acid. Proteomic, transcriptomic and metabolomic data from real and mock hydrolysate fermentations indicated increased levels of a S. cerevisiae hsp9/hsp12 homolog (proteinID: 101453), glutathione dependent formaldehyde dehydrogenases (proteinIDs: 2047, 278215), oxidoreductases, and expression of efflux pumps and permeases during growth on the real hydrolysate. Simultaneously, machine learning based medium optimization improved production dynamics by 18

In this study, a novel nonylphenol (NP)-degrading bacterium, Pseudoxanthomonas mexicana CH, was isolated from wastewater treatment plant effluent. Phylogenetic analysis showed its close relationship to P. mexicana AMX 26BT. The strain displayed chemotaxis toward NP, with Mcp24 as the key chemoreceptor. The Mcp24 deletion mutant (CH- 1) had weaker chemotaxis and NP degradation (over 30% lower in solution and 8% lower in sludge than the wild type). In vitro, Mcp15’s C-terminal pentapeptide DWQEF was methylated by CheR. Using CRISPR, this pentapeptide was added to Mcp24 to create CH- 2. CH- 2 showed better NP chemotaxis (17% higher in plate assays and 39% higher in capillary assays) and higher NP degradation rates (23.5% and 24.2% higher in solution and sludge, respectively). These findings demonstrate that NP acts as a bacterial chemoattractant, with Mcp24 as the receptor. Enhancing Mcp24’s C-terminal pentapeptide improves chemotaxis and degradation efficiency, representing a significant advancement in bioremediation by strengthening bacterial responses to pollutants.

Triacetic acid lactone (TAL) is a promising platform chemical to produce valuable compounds. The development of engineered microbial hosts to efficiently produce TAL from lipid-containing waste streams could be a cost-effective, sustainable and environmentally friendly approach to meet the industrial demand. In this study, we engineered the yeast Candida viswanathii, possessing robust fatty acid conversion capabilities, to develop an alternative route for TAL production from fatty acids that aims to maximize conversion of the acetyl-CoA pool generated by β-oxidation in the peroxisome. To do so, we inactivated the carnitine acetyltransferase gene to block the transport of acetyl-CoA out of the peroxisome and overexpressed the enzymes methylmalonyl-CoA carboxyltransferase, 2-pyrone synthase and pyruvate carboxylase in the peroxisome to convert acetyl-CoA into TAL. We also performed an adaptive laboratory evolution experiment to obtain mutants with higher growth rate in medium with oleic acid and observed marked differences in central carbon metabolism and organic acid production pathways between the evolved and parental strains. These strains were further engineered by integrating additional copies of TAL biosynthetic genes while reducing competing reactions like ω-oxidation and Lipid biosynthesis, resulting in up to 50-fold increase in titers relative to the initial strain, reaching 280 mg/L. This study contributes to the development of bioprocesses that valorize fatty acids as microbial conversion substrates for the production of valuable compounds.

The oleaginous yeast Rhodosporidiumtoruloides has been exploited for many bioproducts, including several terpenes, owing to its oleaginous nature and biomass inhibitor tolerance. Here, we built upon previous (E)-α-bisabolene work by iteratively stacking the complete mevalonate pathway from Saccharomyces cerevisiae onto a multicopy bisabolene synthase parent strain. Metabolomics and proteomics verified heterologous pathway expression and identified metabolic bottlenecks at three intermediate steps, with candidate feedback-resistant mevalonate kinases screening improving titers 15%. Subtle differences in codon optimization, and preliminary attenuation of competing flux toward lipids resulted in 6-fold, 7-fold higher titers relative to controls, respectively. Media optimization led to modest improvements, with zinc identified as the most promising at 10% titer improvement. Ultimately, high-performance strains were cultivated with corn-stover biomass hydrolysate in microtiter plates at 300 g/L total sugar, achieving 20.8 g/L bisabolene, the highest reported titer in the literature. A 2 L glucose minimal medium bioreactor achieved 19.3 g/L bisabolene and a literature-high productivity of 0.11 g/L/h.

Engineered polyketide synthases (PKSs) have great potential as biocatalysts. These unnatural enzymes are capable of synthesizing molecules that are either not amenable to biosynthesis or are extremely challenging to access chemically. PKSs can thus be a powerful platform to expand the chemical landscape beyond the limits of conventional metabolic engineering. Here we employ a retrobiosynthesis approach to design and construct PKSs to produce δ-valerolactam (VL) and three enantiopure α-substituted VL analogues that have no known biosynthetic route. We introduce the engineered PKSs and pathways for various malonyl-CoA derivatives into Pseudomonas putida and use proteomics, metabolomics and culture condition optimization to improve the production of our target compounds. These α-substituted VLs are polymerized into polyamides (nylon-5) or converted into their N-acryloyl derivatives. RAFT polymerization produces bio-derived polymers with potential biomedical applications. Overall, this interdisciplinary effort highlights the versatility and effectiveness of a PKS-based retrobiosynthesis approach in exploring and developing innovative biomaterials. Engineered polyketide synthases (PKSs) have great potential as biocatalysts for the synthesis of chemically challenging molecules. Here the authors show a retrobiosynthesis approach to design and construct PKSs to produce a series of valerolactams for biopolymer production.

The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.

Oyster mushrooms (Pleurotus ostreatus) are one of the most commonly grown edible mushrooms using compost, which contains high concentrations of ammonia. In this study, inoculation of the oyster mushroom culture substrate with ammonia-assimilating bacterium Enterobacter sp. B12, either before or after composting, reduced the ammonia nitrogen content, increased the total nitrogen content of the compost, and enhanced the mushroom yield. Co-cultivation with P. ostreatus mycelia on potato dextrose agar (PDA) plates containing 200 mM NH4+, B12 reduced reactive oxygen species (ROS) accumulation in the mycelia and downregulated the expression of the ROS-generating enzymes NADPH oxidase A (NOXA) and the stress hormone ethylene synthase 1-aminocyclopropane-1-carboxylate oxidase (ACO). It also downregulated the expression of the ammonia-assimilating related genes in the mycelia, such as glutamate dehydrogenase (GDH), glutamate synthase (GOGAT), glutamine synthetase (GS), ammonia transporter protein (AMT), and amino acid transporter protein (AAT), while upregulating its own ammonia-assimilation genes. These findings suggest that the mechanism by which B12 promoted oyster mushroom growth was that B12 assimilated ammonia, alleviated ammonia stress, mitigated ROS accumulation in the mycelia, and supplied ammonia and amino acids to the mycelia. To our knowledge, ammonia-assimilating bacteria are a novel type of mushroom growth promoter (MGP).

BACKGROUND:The risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via human milk-feeding is virtually nonexistent. Adverse effects of coronavirus disease 2019 (COVID-19) vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. OBJECTIVES:Herein, we aimed to determine if compositional changes in milk occur following SARS-CoV-2 infection or COVID-19 vaccination, including any evidence of vaccine components. METHODS:An extensive multiomics approach was taken using a subset of milk samples obtained as part of our broad studies examining the effects on milk of SARS-CoV-2 infection and COVID-19 vaccination. RESULTS:We found that compared with unvaccinated individuals, SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 h for the mRNA-based Moderna vaccine (8 changed proteins), 3 d for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. CONCLUSIONS:Together, our data provide evidence of only minimal changes in milk composition because of COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

Prostate cancer (PCa) is the most common non-skin cancer among men in the United States. However, the widely used protein biomarker in PCa, prostate-specific antigen (PSA), while useful for initial detection, its use alone cannot detect aggressive PCa and can lead to overtreatment. This chapter provides an overview of PCa protein biomarker development. It reviews the state-of-the-art liquid chromatography-mass spectrometry-based proteomics technologies for PCa biomarker development, such as enhancing the detection sensitivity of low-abundance proteins through antibody-based or antibody-independent protein/peptide enrichment, enriching post-translational modifications such as glycosylation as well as information-rich extracellular vesicles, and increasing accuracy and throughput using advanced data acquisition methodologies. This chapter also summarizes recent PCa biomarker validation studies that applied those techniques in diverse specimen types, including cell lines, tissues, proximal fluids, urine, and blood, developing novel protein biomarkers for various clinical applications, including early detection and diagnosis, prognosis, and therapeutic intervention of PCa.

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic β-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity - is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

Plant root border cells (RBCs) prevent the colonization of plant growth-promoting rhizobacteria (PGPR) at the root tip, rendering the PGPR unable to effectively control pathogens infecting the root tip. In this study, we engineered four strains of Pseudomonas sp. UW4, a typical PGPR strain, each carrying an enhanced green fluorescent protein (EGFP)-expressing plasmid. The UW4E strain harboured only the plasmid, whereas the UW4E-flg22 strain expressed a secreted EGFP-Flg22 fusion protein, the UW4E-Flg(flg22) strain expressed a non-secreted Flg22, and the UW4E-flg22-D strain expressed a secreted Flg22-DNase fusion protein. UW4E-flg22 and UW4E-flg22-D, which secreted Flg22, induced an immune response in wheat RBCs and colonized wheat root tips, whereas the other strains, which did not secrete Flg22, failed to elicit this response and did not colonize wheat root tips. The immune response revealed that wheat RBCs synthesized mucilage, extracellular DNA, and reactive oxygen species. Furthermore, the Flg22-secreting strains showed a 33.8%-93.8% higher colonization of wheat root tips and reduced the root rot incidence caused by Rhizoctonia solani and Fusarium pseudograminearum by 24.6%-35.7% compared to the non-Flg22-secreting strains in pot trials. There was a negative correlation between the incidence of wheat root rot and colonization of wheat root tips by these strains. In contrast, wheat root length and dry weight were positively correlated with the colonization of wheat root tips by these strains. These results demonstrate that engineered secretion of Flg22 by PGPR is an effective strategy for controlling root rot and improving plant growth.