High yield production of 3-hydroxypropionic acid using Issatchenkia orientalis

Domain: chemistry
Published: 2026-01-09
Editorial outcome: major_revision

Abstract
Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate aminotransferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as an next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Introduction
Biomanufacturing has been increasingly used to produce chemicals and materials from renewable plant biomass1–3. 3-Hydroxypropionic acid (3HP) is one of the top 12 sugar-based platform chemicals that were identified by the United States Department of Energy to have great potential for commercial applications4–8. For example, it can be converted to acrylic acid, 1,3-propanediol, methyl acrylate, acrylamide, ethyl 3HP, malonic acid, propiolactone, and acrylonitrile6,9,10. In particular, acrylic acid represents a large market opportunity (approximately US$20 billion), with a global annual demand of approximately 6.6 million tons in 2019 and is expected to grow by more than 5% every year11. Currently, both 3HP and acrylic acid are produced almost exclusively via chemical synthesis routes, which rely on fossil-derived feedstocks and involve energy-intensive processes that contribute to greenhouse gas emissions and environmental pollution9,12,13.

Both bacteria and yeasts have been extensively explored for the biological production of 3HP in the past few decades14. Bacteria such as Escherichia coli have been engineered to produce 3HP with high yields and titers (0.6 g/g yield with a titer of 72 g/L15). However, the inhibitory effects of low pH on bacterial growth necessitates the use of neutralization agents such as calcium carbonate to maintain fermentations at neutral pH, i.e., above the pKa of 3HP (4.5). As a result, an acidification step is necessary to recover 3HP, which leads to the formation of gypsum, rendering downstream processing complex and costly (Supplementary Fig. 1). In contrast, due to their tolerance to low pH, yeasts can be engineered to produce 3HP at low pH, which greatly simplifies the whole 3HP production process and eliminates the formation of gypsum. A previous techno-economic analysis of the theoretical fermentation space suggested a yield of >0.78 g/g combined with a titer of >80 g/L or a yield of >0.62 g/g combined with a titer of >60 g/L would be needed to achieve financial viability under neutral and low-pH regimes, respectively16. However, to the best of our knowledge, the highest titer and yield achieved using a yeast are 100.4 g/L (with a yield of 0.2 g/g)17 and 0.56 g/g (with a titer of 11.25 g/L)18, respectively.

To develop a cost-effective biological process for 3HP production, we seek to engineer a low-pH tolerant yeast Issatchenkia orientalis SD10819 capable of producing 3HP at high titer and yield and establish an end-to-end pipeline consisting of biomanufacturing facility design, simulation, techno-economic analysis (TEA), life cycle assessment (LCA), strain development, downstream processing, and scale-up. We previously developed a genetic toolbox for metabolic engineering of I. orientalis, including episomal plasmids, a library of promoters and terminators with varying strengths, a homologous recombination-based DNA assembly method20, a multiplex CRISPR-based gene deletion system21, and a landing pad system for multiple copy gene integration22. In this work, we leverage this toolbox to identify the rate-limiting enzyme in the 3HP biosynthetic pathway, the PAND enzyme which catalyzes the transformation of aspartate to β-alanine. We then introduce up to eight copies of the PAND gene, block the ethanol and glycerol production pathways, and overexpress pyruvate carboxylase (PYC) and aspartate aminotransferase (AAT) enzymes. The final strain can produce 29 g/L of 3HP with a yield of 0.58 g/g in shake flask fermentation. Next, we perform fed-batch fermentation at the lab scale, which results in a titer of 92 g/L and a 0.7 g/g glucose yield. Future efforts directed toward scaling up, integrating downstream processing (DSP), and utilizing alternative renewable feedstocks are expected to further enhance the economic feasibility of the process and substantially reduce environmental impacts compared with conventional fossil-based production routes.

Results
Selection of 3HP biosynthetic pathway in I. orientalis
For host selection, we chose I. orientalis SD108 for 3HP production because of its high tolerance to 3HP (up to 125 g/L, Supplementary Fig. 2 at initial pH of 5.6). For pathway selection, we employed a genome-scale metabolic (GSM) model of I. orientalis23 augmented separately with reactions capable of producing 3HP by seven previously reported pathways24, including β-alanine and malonyl-CoA pathways. Systematic evaluation revealed that in context of an I. orientalis background, the β-alanine pathway has both the highest maximum theoretical yield of 3HP (i.e., carbon yield from glucose of 99.7% or 0.986 g 3HP/g glucose) as well as the most favorable (i.e., lowest) minimal oxygen uptake requirements at high yield (i.e., only 0.018 mmol/mmol glucose) (Fig. 1). The reactions of this pathway, provided in Table 1, starting from the conversion of pyruvate requires three non-native enzymes: PAND (aspartate 1-decarboxylase), BAPAT (β-alanine-pyruvate aminotransferase), and YDFG (3HP dehydrogenase). Subsequently, we performed thermodynamics analysis of this pathway since external pH is known to affect the intracellular pH of Saccharomyces cerevisiae25 and pH can impact thermodynamics. Table 1 gives the change in Gibbs free energy for each reaction step using dGPredictor, a recently developed moiety-based automated fragmentation tool that has improved goodness of fit over group contribution (GC) methods26, at pH 7 and 6 and an assumed ionic strength of 0.1 M (see Supplementary Table 1 for computations using eQuilibrator27). For pH 6, two non-native steps are substantially more negative (i.e., favorable) than at pH 7. Notably, though, for pH 6 the net change becomes more positive at the aspartate transaminase step and less negative at the pyruvate carboxylase step than they are at pH 7. By shifting the equilibrium through accumulation of reactants and fast removal of products (i.e., the latter by increased PAND levels), aspartate transaminase could nevertheless proceed in the desired direction. Therefore, we decided to assemble and express the β-alanine pathway in I. orientalis for 3HP production.

Construction of efficient 3HP biosynthetic pathway in I. orientalis
To design an optimal β-alanine pathway in I. orientalis, we used the sequence similarity network (SSN) analysis tool28 to identify up to 10 different genes for each of the three genes in the pathway. The template PAND, BAPAT and YDFG genes were from a previous report in which S. cerevisiae was engineered to produce 3HP via the β-alanine pathway29. At the beginning, we designed an in vivo strategy in which the screening strains were integrated with template BAPAT and template YDFG or template PAND and template YDFG or template PAND and template YDFG for screening candidate PAND or candidate BAPAT or candidate YDFG, respectively. Our first strategy could only allow us to effectively screen the best PAND, but not for BAPAT and YDFG (Supplementary Figs. 3, 4, and 5), which indicated that the first step was significantly rate-limiting due to limited supply of the precursors for BAPAT and YDFG. For the PAND gene, we also started another screening assay by directly measuring the intracellular β-alanine accumulation using the recombinant I. orientalis harboring different candidate PAND-encoding plasmids in SC-URA with 50 g/L glucose after two days. As shown in Fig. 2A, the hypothetical protein GE061_003755-Apolygus lucorum (i.e., P5), gave us the highest production of β-alanine, which was consistent with the result obtained from the in vivo test (Supplementary Fig. 3). For characterizing the other two enzymes, BAPAT and YDFG, we chose an in vitro enzymatic reaction, in which the cell lysate with enzymes produced from I. orientalis were directly mixed with the enzyme substrate (Fig. 2B). For BAPAT, we adopted a previously developed assay by Borodina et al.29, which used colorimetry to quantify the formation of an aldehyde product using Purpald as a purple-color-forming agent (Supplementary Fig. 6). We found that the protein aminotransferase class III-fold pyridoxal phosphate-dependent enzyme from Methanosarcina sp. MTP4 (i.e., B6), gave the best result (Fig. 2C). For YDFG, due to the lack of commercially available malonic semialdehyde and the high cost of NADPH, we decided to couple the best BAPAT enzyme and glucose dehydrogenase (GDH) to synthesize malonic semialdehyde and NADPH for the YDFG catalyzed reaction. The results shown in Fig. 2D indicate that the bifunctional NADP-dependent 3-hydroxyacid dehydrogenase/3-hydroxypropionate dehydrogenase YDFG from Erwinia mallotivora (i.e., Y3) produced the most 3HP.

Improving 3HP production via metabolic engineering
To improve the production of 3HP in I. orientalis, we explored various metabolic engineering strategies (Fig. 3). The strain containing an episomal plasmid, harboring β-alanine pathway consisting of the best genes selected from the section of construction of efficient 3HP biosynthetic pathway in I. orientalis, referred to as PBY, produced 2.5 g/L of 3HP (Fig. 3B, column 2) compared to 0.86 g/L (Fig. 3B, column 1) from the strain harboring the β-alanine pathway consisting of the original PAND, BAPAT and YDFG genes. We posited that introducing more copies of the β-alanine pathway integrated into the genome along with an episomal plasmid harboring PBY would increase production. The resulting strain pPBY/PBY3/ura3Δ (3 copies of the pathway integrated in the genome with PBY on an episomal plasmid) led to an increase in 3HP production, reaching 5.81 g/L (Fig. 3B, column 5). To identify the rate-limiting step, we introduced individual episomal plasmids for the PAND gene, the BAPAT gene, the YDFG gene, and all three genes (PBY) into the strain PBY2/ura3Δ (Fig. 3B, column 6 to column 8). Only the strain harboring the plasmid with the PAND gene could produce 3HP as the strain harboring the plasmid with all three genes, indicating PAND was the rate-limiting step. We further investigated the effect of the copy number of the PAND gene on 3HP production by integrating up to eight copies into the LPB/Δura3 strain, our landing pad strain22 that allows multiple gene integrations at a time. This also circumvented generating redundant expression of the BAPAT and YDFG genes. This led to a substantial increase in the 3HP titer from 3.2 g/L for strain pPBY/1P/ura3Δ (1 copy of PAND, Fig. 3B, column 9) to 8.4 g/L for pPBY/8P/ura3Δ (8 copies of PAND, Fig. 3B, column 16), despite a drop to 5.5 g/L with five to seven copies of PAND. qPCR analysis (Supplementary Method 1) confirmed that the expression level of PAND increased with increasing copy number (Supplementary Fig. 7, yellow bar), but the 3HP production did not continually increase. Further investigation of the PYC gene revealed its elevated expression levels at three and eight PAND copies (Supplementary Fig. 7, orange bar), suggesting that integration at the EG6 site activated PYC, boosting the production. The data indicated that the native aspartate flux supported only three to four PAND copies.

To further enhance the 3HP production, we knocked out the PDC gene in the pPBY/8P/ura3Δ strain to generate pPBY/8P/ura3Δ/pdcΔ, and the 3HP titer significantly increased from 8.4 g/L to 17.4 g/L (Fig. 3B, column 17). Next, to further reduce the glycerol byproduct, we knocked out GPD (glycerol-3-phosphate dehydrogenase) in the PDC knock-out strain, leading to a production of 18.6 g/L (Fig. 3B, column 19). Next, considering that an industrially relevant strain should have all genes integrated into the chromosome to improve genetic stability, we decided to integrate the BAPAT and YDFG genes to the chromosome to generate the 1AP/ura3Δ strain and cultured it in synthetic complete medium (CSM medium), which produced 25 g/L of 3HP (Fig. 3B, column 20). Because the BAPAT and YDGF genes were provided from a two-copy episomal plasmid in the previous section, we transformed the episomal plasmid pPBY and empty episomal plasmid back to the 1AP/ura3Δ strain to evaluate the gene copy number effect from BAPAT and YDFG. However, the results showed that there is no difference in production (Supplementary Fig. 9). To further increase the yield, another copy of PYC-AAT was integrated, which resulted in a titer of 29 g/L (Fig. 3B, column 21). After integrating a second copy of PYC-AAT, the resulting strain, 2AP/ura3Δ, consumed glucose slightly slower than the 1AP/ura3Δ strain (Supplementary Fig. 10A), but the pyruvate accumulation reduced from 2.6 g/L to 0.86 g/L (Supplementary Fig. 10B).

Fed-batch fermentation
Next, we performed fed-batch fermentation to further increase the titer and yield of 3HP production. During fed-batch fermentation, a pH of 4 was maintained, which eliminated the acidification step for downstream processing. Moreover, dissolved oxygen (DO) was maintained at 5% to create a microaerobic environment, based on the computational modeling studies as illustrated in Fig. 1, to increase 3HP production. We utilized CSL (Corn Steep Liquor) as the fermentation medium to make this fermentation industrially feasible and lower cost. To culture the strain in CSL, we recovered the ura3 gene in the 2AP/ura3Δ strain to generate the 2AP strain since the 2AP/ura3Δ strain grew very slowly in pure CSL medium but with uracil supplement, 2AP/ura3Δ could grow similarly as the 2AP strain in pure CSL (Supplementary Fig. 11). The 2AP strain consumed 50 g/L of glucose, accumulated up to 15 g/L of pyruvate and produced 18 g/L of 3HP in CSM medium by day 3. From day 3 to day 5, the 2AP strain consumed pyruvate to produce 3HP, which reached 26 g/L and a yield of 0.52 g/g on day 5 (Fig. 4A–C). As for the CSL medium, the 2AP strain consumed 50 g/L glucose in 9 days and accumulated only 0.7 g/L pyruvate with a 3HP production of 32 g/L (Fig. 4A–C). Lower pyruvate accumulation in CSL explain why the 2AP strain produced more 3HP in CSL because pyruvate is an important precursor in the β-alanine pathway. Overall, although CSL medium reduced the glucose uptake rate, pyruvate did not accumulate and the 3HP yield was increased to 0.64 g/g glucose. The 2AP strain was used for all fed-batch fermentations. To demonstrate the maximum performance of 2AP, we performed the fed-batch fermentation in 300 mL DAS box system with CSL medium, DO set to 5%, pH of 4, and CO2 gassing, which resulted in a titer, yield, and productivity of 92 g/L, 0.7 g/g, and 0.55 g/L/h, respectively (Fig. 4D). Feeding was performed manually at each scale in pulse mode and was dependent on the concentration of glucose at the time of sampling (Supplementary Table 2). For the cell growth, the OD600 (optical density) along with the fermentation time was shown in Supplementary Fig. 12. Also, during the whole period of fermentation, no other metabolites at concentrations greater than 1 g/L were observed. We also attempted the preliminary scale-up study to 3 L scale and showed that the yield also reached 0.7 g/g with titer of 74.5 g/L. (Supplementary Fig. 13).

Financial viability and environmental benefits under uncertainty
Finally, we designed and simulated end-to-end biomanufacturing facilities for 3HP that could accept dextrose monohydrate as a feedstock (as well as corn, sugarcane, and corn stover), ferment to 3HP using I. orientalis, purify and concentrate the fermentation broth (to 30 wt% 3HP), catalytically upgrade 3HP to acrylic acid, and recover glacial acrylic acid of >99.5 wt% purity (Supplementary Fig. 14) at an annual production capacity of 134,000 metric tons of acrylic acid. We also performed sensitivity analyses using Spearman’s rank order correlation coefficients (Spearman’s ρ) to identify key drivers of production costs and life cycle carbon intensity (CI), and designed and simulated the biomanufacturing facility across the theoretical fermentation space (i.e., 2500 possible yield-titer combinations at the baseline productivity of 0.548 g/L/h as well as 100 possible productivity values at the baseline yield-titer combination of 0.694 g/g and 92 g/L) for each feedstock under both low-pH fermentation (i.e., fermentation pH of 4 and no acidulation required after fermentation) and neutral fermentation regimes (i.e., neutralization by base addition during fermentation and complete re-acidulation after fermentation) to prioritize research and development pathways to advance system sustainability.

For the simulated dextrose-based 3HP biomanufacturing based on experimental performance in the DAS box, the biomanufacturing facility could produce acrylic acid at an estimated minimum product selling price (MPSP) of $1.36/kg (baseline) with a range of $1.21−1.58/kg [5th-95th percentiles, hereafter in brackets] and a CI of 4.43 kg CO2-eq./kg [4.01–5.10 kg CO2-eq./kg; Fig. 5A, B]. Integrating the end-to-end pipeline with an on-site corn dry-grind process would substantially improve the biomanufacturing’s financial viability (MPSP of $1.13/kg [$1.01−1.27/kg], below the acrylic acid market price range in 100% of simulations) and reduce CI (3.26 kg CO2-eq./kg [2.78−3.92 kg CO2-eq./kg], below the fossil-based acrylic acid CI range in 98.5% of simulations). Biomanufacturing facilities designed to accept sugarcane could unlock even greater environmental benefits from the production of excess electricity by the turbogenerator, offsetting marginal grid impacts to achieve a CI of 2.12 kg CO2-eq./kg [1.49−2.76 kg CO2-eq./kg].

Simulations across the theoretical fermentation space demonstrated improving yield in low-pH fermentation will have the most direct benefit to MPSP (Fig. 5C, E), which was consistent with MPSP being most sensitive to fermentation yield among 33 uncertain parameters (Spearman’s ρ of −0.69; Supplementary Fig. 15). Regardless of the feedstock used, the biomanufacturing facility’s MPSP benefited consistently from increased yield and titer values for both neutral and low-pH fermentation in the evaluated theoretical fermentation space (Fig. 5C, E; Supplementary Figs. 16–18), with potential minimum values of $1.39/kg for neutral fermentation and $1.02/kg for low-pH fermentation for dextrose-accepting facilities at the baseline productivity of 0.548 g/L/h. The benefits of a higher titer (e.g., lower heating demands from separation units) generally outweighed the increased expenses (e.g., larger fermentation reactors at a fixed 3HP productivity), but the magnitude of the net benefits diminished with increasing titer. Similarly, at higher yield values, further improvements to yield had diminishing benefits for MPSP. The relative benefits to MPSP from comparable relative improvements to yield and titer depended on the location in the theoretical fermentation space. For example, at the baseline fermentation yield (69.4% of the theoretical maximum) and titer (92.0 g/L), improving yield by 6.9% (a 10% relative increase) would decrease the MPSP by $0.06/kg, while improving titer by 9.2 g/L (a 10% relative increase) would decrease the MPSP by only $0.03/kg (Fig. 5E). The biomanufacturing facility’s MPSP, CI, and fossil energy consumption (FEC) were relatively insensitive to potential improvements to fermentation productivity (e.g., decreasing by $0.09/kg, 0.01 kg CO2-eq./kg, and 0.2 MJ/kg, respectively, with a 400% increase from the baseline productivity to 2.74 g/L/h; Supplementary Fig. 19). While the biomanufacturing facility’s CI and FEC were most substantially sensitive to 3HP titer (Spearman’s ρ of −0.78 and −0.73, respectively; Supplementary Fig. 15) and consistently benefited from titer improvements (Fig. 5F, Supplementary Fig. 20B), 3HP yield improvements at high yield values could actually increase CI and FEC. This was because the yield of I. orientalis cell mass was assumed to decrease with 3HP yield improvements, resulting in lower-energy wastes being diverted to the boiler for combustion. The resulting decrease in steam production necessitated the purchase of larger amounts of natural gas to satisfy the biomanufacturing facility’s heating, cooling, and power utility demands. For the simulated dextrose-based 3HP biomanufacturing based on experimental performance in the 3 L bioreactor (yield of 0.703 g/g, titer of 74.5 g/L, and productivity of 0.776 g/L/h), the MPSP did not change substantially ($1.39/kg) but the CI and FEC increased to 4.87 kg CO2-eq./kg and 54.06 MJ/kg, respectively, due to the decreased titer relative to that achieved in the DAS box (92.0 g/L). This demonstrates improving fermentation titer will have the most direct benefits to CI and FEC. However, high 3HP yields will be necessary to unlock the high titers needed for environmental benefits, with potential minima of 2.96 kg CO2-eq./kg and 31.8 MJ/kg for CI and FEC, respectively, for low-pH fermentation in dextrose-accepting biomanufacturing facilities (Fig. 5F, Supplementary Fig. 20 and Supplementary Method 2).

Methods
Strains, media, and materials
All the strains and plasmids were listed in Supplementary Table 4 and Supplementary Table 5, respectively. E. coli DH5α was used to maintain and amplify plasmids. I. orientalis SD108, and S. cerevisiae YSG50 were propagated in Yeast-Peptone-Adenine-Dextrose (YPAD) medium consisting of 1% yeast extract, 2% peptone, 0.01% adenine hemisulphate, and 2% glucose. Recombinant I. orientalis strains were grown in Synthetic Complete (SC) dropout medium lacking uracil (SC-URA). LB broth, bacteriological grade agar, yeast extract, peptone, yeast nitrogen base (w/o amino acid and ammonium sulfate), ammonium sulfate, and D-xylose were obtained from Difco (BD, Sparks, MD), while complete synthetic medium was purchased from MP Biomedicals (Solon, OH). All restriction endonucleases, Q5 DNA polymerase and Phusion polymerase were purchased from New England Biolabs (Ipswich, MA). The QIAprep spin mini-prep kit and RNA isolation mini kit were purchased from Qiagen (Valencia, CA), whereas Zymoclean Gel DNA Recovery Kit and Zymoprep Yeast Plasmid Miniprep Kits were purchased from Zymo Research (Irvine, CA). All other chemicals and consumables were purchased from Sigma (St. Louis, MO), VWR (Radnor, PA), and Fisher Scientific (Pittsburgh, PA). Oligonucleotides including gBlocks and primers (Supplementary Data 2–5) were all synthesized by Integrated DNA Technologies and Twist Biosciences (IDT, Coralville, IA; Twist Biosciences, San Francisco, CA). For plasmid construction, Gibson assembly or DNA assembly was used. For strain construction, the CRISPR method was used for gene integration/deletion and the lithium acetate-mediated method was used for transformation. Detailed plasmid construction, strain construction, and gene selection are described in the Supplementary Methods 3, 4 and 5, respectively.

PAND gene screening assay
Plasmids encoding different PAND genes were transformed into I. orientalis SD108/ura3Δ. Three colonies were picked into 2 mL SC-URA with 50 g/L of glucose and cultivated for one day and then transferred to 20 mL SC-URA and cultivated for two days at 30 °C with shaking at 250 rpm. All cells were collected and adjusted to OD600 of 100. The cells were disrupted by the glass beads method. For glass beads disruption, cells were lysed using FastPrep-24 5G for 20 s (6.0 m/s) and the lysed cycle was repeated three times. In each interval, the sample was placed on ice for 2 min cooling. The cell extract was derived by FMOC first and then subjected to amino acid analysis to quantify the β-alanine production. For sample preparation for amino acid analysis, 370 µL of 500 mM Borate (pH 10) and 20 µL of FMOC (2.5 mg/mL in acetonitrile) were added to the 110 µL sample. The mixture was vortexed and stood at room temperature for at least 20 min, followed by centrifugation and filtering.

BAPAT gene screening assay
Plasmids encoding different BAPAT genes were transformed into I. orientalis SD108/ura3Δ. Three colonies were picked into 2 mL SC-URA with 50 g/L of glucose and cultivated for one day and then transferred to 20 mL SC-URA and cultivated for three days at 30 °C with shaking at 250 rpm. All cells were collected and adjusted to OD600 of 100. The concentrated cells were disrupted by the glass beads method. To set up the in vitro enzyme assay, in 1 mL reaction, 900 µL of solution containing 11.1 mM of pyruvate, 11.1 mM of β-alanine, 0.11 mM of PLP, and 55.6 mM of phosphate buffer (pH 7) were mixed with 100 µL of cell extract, and the reaction mixtures were incubated at 37 °C for an hour. Then, 25% TCA was added to quench the reaction. To quantify the malonic semialdehyde production, 110 µL of the reaction mixture was mixed with 140 µL of 68 mM Purpald (4-amino-3-hydrazino-5-mercapto-1,2,4-triazole), and the purple product was measured at 540 nm using a plate reader (Molecular Devices, San Jose, CA).

YDFG gene screening assay
Plasmids encoding different YDFG genes were transformed into I. orientalis SD108/ura3Δ. Three colonies were picked into 2 mL SC-URA with 50 g/L of glucose for one day and then transferred to 20 mL SC-URA for three days at 30 °C with shaking at 250 rpm. All cells were collected and concentrated to OD600 of 100. Then, the cells were disrupted by the glass beads method. To set up the in vitro enzyme assay, in 1 mL reaction, 800 µl of solution containing 37.5 of mM pyruvate, 37.5 mM of β-alanine, 0.125 mM of PLP, 6.25 U of GDH, 2.5 mM of NADP+, 125 mM of glucose and 62.5 mM of phosphate buffer (pH 7) were mixed with 100 µL of YDFG-containing cell lysate and 100 µL of B6 cell lysate containing the BAPAT6 protein from Methanosarcina sp. MTP4. The reaction mixture was incubated at 37 °C for 2 hours. Then, 25% TCA was added to quench the reaction. 3HP was measured by HPLC.

Tube, shake-flask fermentation and DAS box fed-batch fermentation
For tube fermentation (2 mL), three colonies were picked into SC-URA with 50 g/L glucose and cultured for 5 days. 3HP was quantified at day 5. For shake flask fermentation (20 mL) using plasmid-harboring strain, three colonies were picked into 2 mL SC-URA with 50 g/L of glucose for 3 days at 30 °C with shaking at 250 rpm. Then, the cells were subcultured to 20 mL SC-URA with 50 g/L of glucose and 10 g/L of CaCO3 and cultured at 30 °C with shaking at 250 rpm. For shake flask fermentation using all-integrated strains (i.e., 1AP and 2AP strain), three colonies were picked in YPAD for 1 day. Then, the cells were subcultured into 20 mL CSM with 50 g/L of glucose and 10 g/L of CaCO3. The initial OD600 was 0.2 and, the samples were collected every 24 hours for HPLC analysis. For fed-batch fermentation in the DAS box bioreactors (DASbox Bioreactors, Eppendorf, Hamburg, Germany, 100 mL working volume, Supplementary Table 6), single colonies of the I. orientalis strain were inoculated into the YPAD medium and cultured for 1 day. Then, 1 mL of cells was injected into 100 mL of CSL liquid medium in the bioreactor. The cells were cultivated at 30 °C and the DO was set to 5%. A cascade program was used to maintain DO by changing the stirrer speed between 400-1200 RPM, O2 concentration in the gas mix between 21-100% pure O2 and then O2 flow rate between 1–3 vvm while maintaining the pH at 4 using 4M HCl and 28% ammonium hydroxide. When the DO dropped below 5%, CO2 was introduced at 0.2 vvm and conjointly aeration dropped to 0.2 vvm. Therefore, total aeration remained at 0.4 vvm and at this point DO was maintained using agitation only. The CO2 supply could provide an ample amount of bicarbonate for 3HP production.

Analytic methods
For quantification of glucose consumption and ethanol and glycerol productions, Agilent 1200 HPLC system equipped with a refractive index detector (Agilent Technologies, Wilmington, DE, USA) and Rezex ROA-Organic Acid H+ (8%) column (Phenomenex, Torrance, CA, USA) were used. The column was operated at 60 °C, and the mobile phase was 0.005 N H2SO4 at 0.6 mL/min. For quantification of 3HP production and pyruvate accumulation, Shimadzu HPLC with a UV-Vis detector and Aminex HPX-87H Column #1250140 (BioRad, USA) were used with injection of 50 µL sample. The column was operated at 60 °C with 0.005 N H2SO4 at a flow rate of 0.6 mL/min and 210 nm was used as the detection wavelength. For quantification of amino acids, Agilent 1260 HPLC system equipped with a DAD detector (262 nm was used as detecting wavelength) and Phenomenex Kinetex® 5 µm EVO C18 100Å LC column (150 × 4.6 mm2; Phenomenex) were used with injection of 5 µL sample. The column was run at room temperature with a gradient elution process using solvent A (20 mM sodium acetate) and solvent B (acetonitrile). The elution process runs the following program: 18% B to 57% B (linear gradient, 0–13 min), 57% to 100% (linear gradient, 13–13.3 min), 100% B (isocratic elution, 13.3 to 14.3 min), 100% to 18% (linear gradient, 14.3–15.8 min), 18% B (isocratic elution, 15.8 to 18 min).

Genome-scale metabolic modeling, flux balance analysis, and thermodynamic analysis
The genome-scale metabolic model used for I. orientalis SD108 is iIsor85023, which follows nomenclature of the BiGG database38. To evaluate 3HP production, the model was augmented to separately include seven different 3HP pathways24, as well as the transport of 3HP from the cytosol to the extracellular environment and an exchange flux for extracellular 3HP. The BiGG database38, MetaNetX39, ChEBI40, and PubChem41 were used for information about the metabolites and reactions for pathway intermediates. In general, BiGG nomenclature for metabolite and reaction ids was used when available, with compatible ids created otherwise, as noted in the model files; within BiGG 3-hydroypropionic acid (3HP) has the id 3hpp, which was used in the model and simulations. Marvin was used for characterizing chemical structures including formula and charge information (Marvin 23.17.0, Chemaxon). In agreement with conventions of flux balance modeling, these values for each reaction in each pathway were computed using pH 7.2 for each intracellular species. The added 11 metabolites and 21 reactions are provided in YAML format in Supplementary Data 6, and the accompanying notes field of each reaction includes the associated pathway(s). The reaction set was also updated at the malonic semialdehyde reductase step for YDFG to use NADPH as a cofactor instead of NADH (which was used in previous simulations for S. cerevisiae42). Flux balance analysis (FBA) was used for model predictions43. For the simulation of a given pathway, only the reactions associated with that pathway were added to the model. The glucose substrate uptake rate was set to 10 mmol g/DW/h glucose during simulations. The maximum oxygen uptake rate was limited to no more than 18.18 mmol g/DW/h during all simulations, as this is the minimal oxygen uptake that does not impact the maximum growth rate for a 10 mmol glucose g/DW/h basis. By convention exchange fluxes assume negative values for uptake, thus these constraints were set as vEX_glcDe = −10 and 0 ≥ vEX_o2e ≥ −18.18. Model simulations of growth phenotype or 3HP formation were obtained using FBA with the objective of maximizing the flux of the biomass reaction (vbiomass) or product exchange flux (vEX_3hppe) in the context of the indicated pathway. Yields are presented as carbon yields by normalizing to the carbons from glucose. Specifically, for each pathway yield is computed as

Yp3hpp,glucose = (vEX_3hp / vEX_glcDe) * yc3hpp,glcD (1)

where yc3hpp,glcD is the number of carbons in 3hpp (i.e., three) divided by those in glucose (i.e., six). Since vEX_glcDe is fixed to −10, for maximum yield this expression can be simplified to

Yp3hpp,max = vEX_3hppe,p / 20 (2)

FBA calculations were implemented using GAMS 33.2.0 using IBM ILOG CPLEX solver. Adding non-native reactions and data processing were performed using the COBRApy package (version 0.29.0)44 and pandas45 within Jupyter notebooks46. Thermodynamics analysis of 3HP metabolic pathways was performed by estimating the standard Gibbs energy change (ΔrG'°) of enzymatic reactions using dGPredictor26 and eQuilibrator27, with SMILES from structures determined using Marvin for compounds not available within KEGG47. The evaluations were performed at pH 7 to compare with previous studies and at pH 6 which corresponds as a lower estimate of the intracellular pH in I. orientalis using the value that S. cereivisiae can have in an external environment of pH 425.

3HP biomanufacturing design and simulation
All 3HP biomanufacturing facilities discussed in this study were designed, simulated, and evaluated using BioSTEAM48 and the thermodynamic package utilized was Thermosteam49. Briefly, influent and effluent streams of each unit are simulated in BioSTEAM and coupled with operating parameters and equipment cost algorithms for unit design and cost calculations. Component equipment for major units (Supplementary Data 7), breakdowns of system costs and environmental impacts (Supplementary Tables 7 and 8, and Supplementary Fig. 22), as well as baseline values and uncertainty distributions of key parameters (Supplementary Data 1) are included in the Supplementary Information. Simulations were run based on experimental fermentation performance at 300 mL and for multiple feedstocks (dextrose, corn, sugarcane, and corn stover). All Python scripts for BioSTEAM and the biomanufacturing facilities (including biomanufacturing facilities setup and system analyses) as well as a system report (including detailed process flowsheet, stream composition and cost tables, unit design specifications, and utilities for the baseline simulation) are available in the online repository (Supplementary Data 8)50. The dextrose-accepting biomanufacturing facilities in this study are comprised of three main (inside battery limits) processes (fermentation, separation, and catalytic upgrading) without outside-battery wastewater treatment and miscellaneous facilities (boiler, turbogenerator, cooling utility regeneration, heat exchanger network, clean-in-place, air distribution, fire water distribution, and process water distribution) with all design assumptions consistent with Bhagwat et al.16 other than for fermentation (based on experimental data obtained in this study). As done in previous studies that involved TEA and LCA to assess the production of platform chemicals16,51,52, the designed biomanufacturing facilities included catalytic upgrading of the platform chemical (3HP) to a commodity chemical (acrylic acid) as no established market yet exists for 3HP. Including catalytic upgrading to acrylic acid in the designed biomanufacturing facilities enabled meaningful comparisons to market price ranges and environmental impacts from conventional production of acrylic acid (detailed under Techno-economic analysis and Lifecycle assessment). Further descriptions of design and modeling assumptions for these processes (including catalytic upgrading) and facilities are detailed in Bhagwat et al.16, and all baseline values, references, and uncertainty distributions of key parameters are included in the Supplementary Data 1.

For biomanufacturing facilities in this study designed to accept biomass feedstocks, there were additional processes included inside battery limits: (i) for corn-accepting biomanufacturing facilities, design assumptions for the corn dry grind process were consistent with Cortés-Peña et al.48; (ii) for sugarcane-accepting biomanufacturing facilities in this study, design assumptions for feedstock juicing and clarification were consistent with Bhagwat et al.53; and (iii) for corn stover-accepting biomanufacturing facilities in this study, design assumptions for corn stover pretreatment and saccharification were consistent with Cortés-Peña et al.48. For all biomanufacturing facilities, at each simulation, a heat exchanger network is newly synthesized using the Linnhoff-Hindmarsh pinch-based approach54 to offset heating and cooling utility demands. The production capacity for all biomanufacturing facilities was set to 134,000 metric tons of acrylic acid annually in the baseline case to be consistent with a previous study35. The baseline production capacity was 2% of the global acrylic acid market size and 14% of U.S. capacity for glacial acrylic acid production in 2020, a fraction of the projected growth projected from 2021 to 2025 in the global market for acrylic acid (a growth of approximately 1,230,000 metric ton/y), and comparable to the projected growth in that 5-year period in the U.S. market (approximately 91,000 metric ton/y)35. Further, a triangular distribution with bounds corresponding to ±20% of the baseline value was attributed to the annual production in the uncertainty analysis. Simplified block flow diagrams of the fermentation and separation processes (Supplementary Fig. 14) as well as baseline values and distributions for all parameters included in the uncertainty analysis (Supplementary Data 1) are detailed in the Supplementary Information, and a full process flowsheet is available online50.

Techno-economic analysis (TEA)
We performed TEA for the designed and simulated biomanufacturing facilities using BioSTEAM’s discounted cash flow rate of return analysis to calculate the minimum product selling price (MPSP, $/kg) of acrylic acid to achieve a net present value of zero with a 10% annual internal rate of return (a uniform distribution of 8−12% was assumed; a full list of baseline parameter values, uncertainty distributions, and literature references for the same are provided in Supplementary Data 1. All costs and prices shown are presented in 2019 U.S. dollars. To benchmark the MPSP of the produced acrylic acid, we assumed a market price range of $1.40−1.65/kg from reported 2015−2019 market prices35 to be consistent with Bhagwat et al.16. All biomanufacturing facilities were modeled as nth plant designs (i.e., it is assumed a successful industry has been established with mature technologies). Key construction (e.g., warehouse, site development), fixed operating (e.g., labor burden, property insurance), and financial (e.g., depreciation, taxes) parameters, as well as all parameters used in the cash flow analysis, followed assumptions made by Bhagwat et al.16. Tabulated breakdowns of the estimated revenue and capital and operating expenditures, as well as additional details on the design, utility requirements, purchase costs, and installed equipment costs can be found online50.

Lifecycle assessment (LCA)
We performed LCA in Python using the simulated inventories for streams (input chemicals and output emissions) and utilities from BioSTEAM. The LCA scope included the operational phase of the biomanufacturing, including cradle-to-grave impacts for all raw materials, ancillary processes, and unit processes. The functional unit was set to 1 kg of produced acrylic acid to be consistent with the TEA. The sale of co-produced electricity was assumed to displace the impacts of marginal electricity production. Impacts resulting from infrastructure construction were excluded to be consistent with the U.S. renewable fuel standard (RFS)55. Final characterization and discussion of environmental impacts focused on carbon intensity (CI; quantified as 100-year global warming potential, GWP100) and fossil energy consumption (FEC). The impact assessment methodology used for CI was Intergovernmental Panel on Climate Change (IPCC) 201356. Life cycle inventory data were collected from ecoinvent 3.8 and some unit impacts were gathered from GREET 202036,37, and their sources were noted in the script50. The baseline impacts of feedstock farming (excluding credit for fixed carbon), harvest and collection, transportation, storage, and handling were considered. The amount of carbon fixed in the feedstock is equal to the sum of carbon in the product (acrylic acid) and in the biogenic portion of direct waste emissions from the biomanufacturing facility. To focus on the biomanufacturing facility, we assumed the end-of-life impacts associated with the product (acrylic acid) as well as non-gaseous wastes (e.g., unconsumed and non-combusted sugars and insoluble lignin in the brine, accounting for <0.0002% of the CI) would be exclusively from the oxidation of all carbon into CO2.

Uncertainty and sensitivity analyses
Uncertainty analyses were conducted using Monte Carlo simulation with Latin Hypercube Sampling (6,000 simulations) for 33 uncertain parameters each in the dextrose, corn, sugarcane, and corn stover scenarios. We assigned uncertainty distributions for parameters to be consistent with Bhagwat et al.16, except for the parameters describing the feedstock acquisition, juicing, and clarification processes (consistent with Bhagwat et al.53) and the fermentation process (based on experimental data obtained in this study). The full list of the evaluated parameters, their uncertainty distributions, and literature references are provided in Supplementary Data 1. The sensitivity of MPSP, CI, and FEC to all uncertain inputs was determined via Spearman’s rank order correlation coefficients (Spearman’s ρ) using Monte Carlo simulation results, and only parameters with p<0.05 were discussed to ensure robustness (Supplementary Fig. 15). Files with comprehensive results of all analyses are available online50.

Statistics & reproducibility
No statistical method was used to predetermine sample size. Most experiments were performed with at least three independent biological replicates, and results are presented as mean ± S.D. The 300 mL scale fed-batch fermentation was conducted with two biological replicates, whereas the 3 L scale fed-batch fermentation and qPCR analysis were performed with one biological replicate. No data were excluded from the analyses. The experiments were not randomized, and the investigators were not blinded to allocation during experiments and outcome assessment.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study explored the economically feasible biological production of 3HP. The manuscript consists of two parts: first, fermentation by the recombinant yeast I. orientalis, and second, simulation for TEA and LCA. The authors claim that the developed yeast can produce 3HP at low pH (4.0), and the TEA and LCA analyses, based on experimental results, suggest that the minimum product selling price (MPSP) of acrylic acid (AA) is below 2 USD per kg. The extensive efforts toward the bioproduction of the important chemical 3HP, spanning from strain development, purification, and conversion to the final product (AA), to TEA and LCA, are highly appreciated. However, due to the broad scope of the study, some details were not fully covered and may have been overlooked.\nFurthermore, it would be beneficial to separate the strain development and fermentation section from the simulation section (TEA and LCA) to deepen the scientific and commercial feasibility discussion. In the current format, neither part is fully satisfactory. It is recommended to divide the study into two separate articles and submit them to appropriate journals.\nMajor Comments:\n1. Fermentation proceeded very slowly and took almost 10 days at the 300 L-scale. Is it possible to speed it up?\n2. Is acidic fermentation still beneficial when purification includes both CEX and AEX, and the final product is Na(3HP)? What is the difference in DSP cost between neutral and acidic fermentation?\n3. (L227-9) Is it possible to convert 30 wt% 3HP (sodium salt or acid form?) to acrylic acid using a chemical catalyst?\n4. (L234-5) (1) Is re-acidification after fermentation necessary before starting DSP, given that both AEX and CEX are used and the final product is recovered as a sodium salt? (2) When estimating MPSP for neutral fermentation, the same input parameters for fermentation—especially productivity and titer—were used. This is incorrect, as productivity is likely much higher in neutral fermentation.\n5. (L239-40) It is difficult to validate the MPSP without detailing the conversion process of 3HP (salt or acid form? concentration?) to AA and AA purification etc.\nMinor Comments:\n1. (L93) Indicate the pH for this tolerance experiment.\n2. (L95-98) What do the numbers in Fig. S2 represent? What does \"99.7%\" (in parentheses in L97) mean?\n3. (L106) What do you mean? Compared to what?\n4. (L107) The ΔG of the AAT reaction is not negative at pH 7, unlike at pH 6.\n5. (L135; Supp. Fig. 6) What aldehyde was used in the experiment? In the negative control, was crude cell extract used? Cell-free extracts generally contain various chemicals that can react with the color-forming agent. Did you confirm that no color formed in the absence of aldehyde?\n6. (L167-7) In the PDC wild-type, was EtOH produced at a high level? What about the PDC-deletion mutant? Please show by-product profiles.\n7. (L170-2) What do you mean? The knockouts did not improve the carbon yield and O₂ requirement, yet they were still important?\n8. (L188-) In fed-batch fermentations, show profiles of other metabolites. Also, show cell density profiles.\n9. (L194) Why was the recovery of the ura3 gene necessary for cultivation in CSL?\n10. (L200) What is the major difference between CSM and CSL media? Why was there concern about pyruvate accumulation in CSL medium?\n11. (L209) Do you mean \"between these two time points\" or \"at these two time points\"? If the latter, why does this occur?\n12. (L283-5) The effect of CO₂ supply has not been adequately described in the main text.\n13. (L342) Is MSA stable for one hour under the assay conditions? Did MSA not inactivate the enzyme? What is the specific absorbance of the \"purple\" product?\n14. (L352-3) In this coupled assay experiment, YDFG—not BAPAT—should be rate-limiting. How was this confirmed? What was the activity ratio (range) between the two enzymes in your assay?\n15. (L373) Table 13?\n16. (L374-5) In Fig. 4, glucose feeding started at 24 h.\n17. (L378-9) Did off-gas CO₂ levels increase when glucose was limited? What was the typical off-gas CO₂ concentration when glucose was available versus when it was depleted?\n18. (L382-3) (1) This suggests that broth pH decreased from 4.0 during 3HP production. Why? (2) How much NH₄ (mol) was required for the production of 1 mol of 3HP?\n19. (L494 and elsewhere) The term \"biorefineries\" seems to be used incorrectly. \"Fermentation(s)\" would be more appropriate.\n20. (Supplementary material p.6; Downstream Processing)\n(i) What was the typical NH₃ concentration in the harvested broth?\n(ii) Is this statement correct: \"Cation exchange (CEX) effectively removed 96% of the ammonium ions, from 3 g/L to 78 g/L\"?\n(iii) The sentence \"a reduction in 3HP concentration from 47.2 g/L to 43.1 g/L was observed\" needs clarification. Why was the 3HP concentration in the AEX feed 47.2 g/L? What was the final 3HP concentration in the fermentation broth before centrifugation?\n(iv) In the sentence \"the solution from AEX was neutralized with NaOH to recover 3HP as sodium salt with 69.4% recovery and 87.5% purity of the salt crystals,\" why was the recovery yield 69.4%? Provide details on where losses occurred.\n21. (Supplementary Table 6) Strain names and their backgrounds need careful verification. Using a plasmid name (e.g., pPBY) as a strain name is unconventional and could cause confusion.", "reviewer_2": "This study is original and explores the production of 3-HP using the yeast Issatchenkia orientalis, expanding the range of heterologous hosts available for this compound. It goes beyond most studies in the field by integrating strain development with purification experiments, scale-up studies, and process feasibility analyses, covering all stages of the bioprocess.\nMore specifically, the authors develop a 3-HP production process using a non-conventional yeast capable of tolerating low pH. This approach enables 3-HP production under acidic conditions, reducing downstream processing (DSP) costs and improving the economic feasibility of its production and subsequent conversion to acrylic acid. In addition to supporting acidic pH operation, the engineered yeast achieves high 3-HP titers and yields. The study also presents a purification strategy, a fermentation scale-up to a 300 L reactor, and techno-economic analysis (TEA) and life cycle assessment (LCA) studies, demonstrating the viability of the proposed process.\nThe experimental methodologies are appropriate for the study's objectives, and the results are clearly presented and discussed in the context of relevant literature.\nJust to contribute to the improvement of the work, a few questions are raised below for consideration.\n1) This study presents significant findings that support the industrial production of 3-HP, a promising chemical commodity in the biorefinery sector. However, the economic feasibility of producing chemical commodities through bioprocesses remains challenging due to their relatively low market price. A relevant example is succinic acid, another promising chemical commodity similar to 3-HP. While some companies established industrial-scale production of succinic acid in recent years, many have since either ceased operations or scaled down to serve niche markets, struggling to maintain economic viability. Do the authors have knowledge of any private initiatives that have successfully implemented industrial-scale 3-HP production via bioprocesses? If so, including this information would help contextualize the study.\n2) Like 3-HP, succinic acid production has been developed using both yeasts and bacteria. Yeasts offer the advantage of operating at an acidic pH, reducing purification costs, while bacteria achieve higher volumetric productivity due to their faster growth rates and shorter process times. Combining the high productivity of bacteria with the low pH tolerance of yeasts could improve the economic feasibility of succinic acid production — a concept that also seems applicable to 3-HP.\nThe authors mention a comparison between 3-HP production in yeasts and bacteria in the supplementary material, but further discussion would be valuable. Specifically, what presents a greater cost challenge: extending fermentation time by a few days (reducing volumetric productivity) to operate at an acidic pH with yeasts, or increasing purification costs in a shorter, higher-productivity process using bacteria at a neutral pH? Although the study demonstrates the feasibility of the proposed process, a quantitative comparison of its economic viability against one of the cited bacterial 3-HP production methods would provide valuable insight.\n3) The authors state that in neutral pH production processes, an acidification step is required to recover 3-HP, resulting in gypsum formation. According to the text, this step is eliminated in the yeast-based acidic pH process. However, Figure 12 in the supplementary material still depicts acidification and gypsum formation for the developed process. I recommend revising either the figure or the text to ensure consistency and accurately reflect the process.\n4) In the fed-batch experiment, a microaerobic condition (5% O2) was used and described as favorable for the process. Is there any explanation or hypothesis based on cell metabolism to support this condition as more favorable?\nMinor revision:\nThe authors should include additional methodological details to ensure the reproducibility of the protocols used. Specifically:\n5) Provide a reference or a brief description of the beta-alanine quantification method used in the PAND gene screening assay.\n6) Specify the volume of cell extract used in the BAPAT gene screening assay.\n7) Indicate the amount and production method of the BAPAT protein from Methanosarcina sp. for the YDFG screening assay.\n8) In the DASbox fed-batch fermentation, the text states: “A cascade program was used to maintain DO by changing RPM, O₂ concentration, and then O₂ flow rate.” Shouldn’t this be air flow rate instead of O₂ concentration? Please verify.\n9) For 3-HP recovery, the text states that the product was recovered from 1 L of culture supernatant. What was the mass of recovered 3-HP?", "reviewer_3": "Financially Viable 3-Hydroxypropionic Acid Production Using Issatchenkia orientalis at an Industrially Relevant Scale.\nThe study presents a microbial fermentation process for 3-hydroxypropionic acid (3HP) production at an industrial pilot scale, involving metabolic engineering of Issatchenkia orientalis, scale-up to a 300-L bioreactor using low-cost media, and downstream processing. The reported results include a 3HP titer of 62.3 g/L, a yield of 0.73 g 3HP/g glucose, and 83.2% w/w purity in sodium salt recovery, alongside financial viability and life cycle analyses.\nWhile the research is valuable, the manuscript requires major revisions to improve readability, structure, and data presentation. The writing quality is poor, with inconsistent verb tenses and numerous spelling errors that hinder comprehension. The Methods section lacks clarity and critical details necessary to reproduce the experiments are missing. The Results section requires significant rewording and restructuring to clearly outline the methodology and experimental outcomes. Missing information in Figures makes interpretation challenging. Supplementary materials should be limited to tables, figures, and methods, while results and discussions should be incorporated into the main text.\nSpecific concerns include:\nMain text:\nLine 36: Modify to \"achieving a 3HP titer of 62.3 g/L.\"\nLine 40: Rephrase to \"a more environmentally beneficial production...\" The production has an impact to the environment only this is smaller compared to fossil-based production.\nLine 50: Correct to \"by the United States Department of Energy.\"\nLine 146: Clarify to \"The strain containing an episomal plasmid, harboring the  -alanine pathway...\"\nLines 146-186: Indicate specific column numbers in Figure 3B for easier reference.\nLine 201: Indicate the calculated 3HP yield per g glucose for CSM.\nLine 203: Specify which strain was used in fermentation.\nL203-207: Please clarify if glucose feeding (manually when the level dropped to 12 ± 2 g/L) was performed same for all scales or specify exact feeding in each scale. If yes, justify why glucose was depleted in some sampling points during fed-batch.\nL209-211: Glucose consumption is not plotted in Figure 4. Please add a supplementary Figure with the calculated specific glucose consumption rates. Please clarify what you mean with “which suggests that a detailed process optimization could result in higher 3HP productivity”, what specific strategy would you follow to increase productivity?\nLine 213-214: Justify extended cultivation time in pilot scale and discuss whether increasing lab-scale cultivation time would improve titers.\nL216-L222: Include Supplementary Figure 12D in the main text and provide a clear description of the followed separation process. Provide data supporting the indicated recovery yield and purity.\nLine 220: Move supplementary results and discussions on downstream processing to the main text.\nLine 259: Please clarify to which thermodynamically favorable and unfavorable pathway alternatives you are referring to.\nL260-L262: rephrase to improve clarity\nLine 270: Define \"in two rounds\" and provide numerical values for increase in tirters.\nL280: Please include Supplementary results and discussion to benchmark production in the main text.\nL309: Correct Online Methods to Methods\nL332-L333/ L338-L340/L348-L350/L357-L358/L358-L360/L361-L362/L363-L365: Please indicate incubation conditions\nL333-L334/L340: Please specify cell disruption method by glass beads\nL334: Please specify method for FMOC derivatization and method for amino acid analysis\nL340/L350: Correct In vitro to italics\nL342: Please specify quantity of cell extract used\nL352-L354: Indicate quantity of BAPAT and YDFG protein applied\nL358: Please specify 3HP quantification method\nL366-L365: Modify “A cascade program was used to maintain DO by changing RPM, O2 concentration and then O2 flow rate” to A cascade program was used to maintain DO at 5 % by adjusting stirrer speed between ____-_____rpm, O2 concentration in the gas mix between ____-_____% and aeration rate between ____-_____vvm.\nL367: Indicate concentrations of acid and base\nL368-L369/L376-L378: Explain why, when attempting to maintain DO at 5-15%, pure CO₂ is added to the gas mix instead of pure O₂ when DO drops below this range.\nL371: Correct \"Scaleup\" to \"scale-up\" throughout the manuscript.\nL373: The manuscript states that Supplementary Table 12 contains operational parameters for bioreactor cultivations, but it only includes OD600 data of precultures. Please correct this.\nL357-L369: Specify tube, shake flask and reactor volumes\nL371: Indicate the bioreactor model, brand, and working volume.\nL371-L388: Clarify the cultivation strategy, clearly indicating carbon sources used in each phase and specifying the feeding profile.\nL381: In Line 376, it is stated that when DO values drop below 10%, CO₂ is introduced into the culture, but in Line 381, it is stated that DO was always maintained at 10%. Please clarify the aeration strategy.\nL390: The final titer in g/L must be divided by the total cultivation time to correctly calculate the productivity of the process.\nFigures & Tables:\nFigure 2C: Indicate Malonic-semialdehyde concentration instead of OD540.\nFigure 3B: Clarify differences between strains in columns 1 and 2.\nFigure 4: Please plot feeding profile. For better comparison, please use the same concentration scaling for all three scales. A correction of the legends for the bioreactors to: 100 mL lab-scale, 10 L lab-scale and 300 L pilot-scale is suggested.\nCaption: Please indicate which strain was cultivated including a description of the strain. Please indicate cultivation conditions (DO set to 5%, pH 4, and CO2 gassing) and feeding.\nFigure 5: Improve distinguishability of symbols in 5A and 5B.\nSupplementary material\nL167: the unit of µ is h-1\nL170: V0 should be the culture volume at the end of the batch\nL175: Please specify exact feeding pulses (time and which amount was fed in each pulse)\nL235-L245: Please provide the data supporting these calculations.\nFigures & Tables:\nSupplementary Figure 1: please indicate how you calculate relative OD600\nSupplementary Figures 3, 4 and 5: Please label the genes or indicate in the description which colour corresponds to each gene.\nSupplementary Figure 8: Please include a description of the strains in the Figure caption.\nSupplementary Figure 9: Please include a description of the strains in the Figure caption.\nSupplementary Figure 10: The type of line for each media in the media plot legend is not distinguishable, please modify.\nPlease include a description of the strain in the Figure caption.\nSupplementary Figure 12: Include a modification of Supplementary Figure 12D in the main text to indicate how 3HP was recovered from 300 L scale. Supplementary Figure 12D should then only contain the simulated scenarios.\nSupplementary Table 2: specify conditions for each cultivation. Are fed batch 1-4 biological replicates? How is the increment in 3HP titer calculated? How is the overall yield calculated?\nSupplementary Table 8: Please indicate what bold and underline sequences indicate\nSupplementary Table 12: I cannot understand from the table if the ODs given refer to initial OD at time 0 or final ODs. Please specify volume and bioreactor of primary seed for 300 L.\nSupplementary Table 13: Correct to starting conditions. Correct (C) to (°C). Indicate range of stirring speed. Avoid double use of unit (vvm) in aeration row. Regarding the DO setpoint, indicate time spam for “metabolite accumulation phase” and also indicate what the DO set point for the rest of the cultivation was.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_5": "Many chemicals could be synthesized from the renewable plant biomass, and 3-Hydroxypropionic acid (3HP) is one of the promising chemicals with the great potential for commercial applications. This study developed the cost-effective 3HP biomanufacturing process with the highest titer, yield and productivity among the yeast-based process using low-pH tolerant non-model yeast I. orientalis. The authors proposed a simple downstream processing to recover the high purity of 3HP and a promising strategy to utilize sugar as the feedstock. This study is remarkable in that it analyzed the feasibility of the proposed strategy by performing the 3HP production at both the lab scale and the industrial scale, using the previously developed their own genetic toolbox and revealing the potential for reducing life cycle carbon intensity. However, there are some concerns about assessment methods and results that have an impact on the clarity of the paper. I think this paper with clear novelty can be published in Nature Communications after revision of some major and minor points.\nMajor points\n1)The authors set the functional unit of the developed system as 1 kg of produced acrylic acid, obtaining the minimum product selling price and life cycle carbon intensity of 1 kg of acrylic acid. This assessment obviously emphasizes the importance of 3HP production to be utilized as a raw material of acrylic acid, but it is inconsistent that the overall statement of the paper emphasized the low-pH tolerant non-model yeast-based production of 3HP. If TEA and LCA are performed by setting the functional unit as 3HP, or the detailed explanation of the reason setting the functional unit as 1 kg of acrylic acid is added, it is better to understand the viability of low-pH tolerant non-model yeast-based production of 3HP.\n2)(p.4) Table 1\n→ Table 1 provides Gibbs free energy at pH 6 and 7, but I would like to know if any other values for lower pH are needed. In fed-batch fermentation, pH 4 was maintained.\n3)(p.5) In “Design and construction of a 3HP biosynthetic pathway in I. orientalis” section\n→ In Fig. 2C and 2D, it is understandable that B6 and Y3 were selected for the in vitro test, but in Supplementary Fig. 4 and 5, the in vivo test shows different behaviors for 3HP production for different gene candidates, and the reason for this difference needs to be analyzed.\n4)(p.6) qPCR analysis confirmed that the expression level of PAND increased with increasing copy number (Supplementary Fig. 7, orange bar), but production did not continually increase. Further investigation of the PYC gene revealed its elevated expression levels at three and eight PAND copies (Supplementary Fig. 7, yellow bar), suggesting that integration at the EG6 site activated PYC, boosting production.\n→ In Supplementary Fig. 7, why does PYC have no tendency as the copy number increases, while PAND continues to increase differently?\n5)(p.6) To further enhance 3HP production, we knocked out the PDC gene in the pPBY/8P/ura3Δ strain to generate pPBY/8P/ura3Δ/pdcΔ and the 3HP titer dramatically increased from 8.4 g/L to 17.4 g/L. Next, to further reduce the glycerol byproduct, we knocked out GPD (glycerol-3-phosphate dehydrogenase) in the PDC knock-out strain, leading to a production of 18.6 g/L.\n→ Is there any experimental data or validation for the improved 3HP production and reduced amount of glycerol byproduct?\n6)(p.10) The author mentioned the reported value of CI of fossil-based acrylic acid as 4.07-5.96 kg CO2-eq./kg, but it is also reported as 1.99 – 2.34 kg CO2-eq./kg by the oxidation of propylene process in the ecoinvent database. If some of the life cycle inventory data were collected from ecoinvent database, it is better to include the CI value of fossil-based acrylic acid from ecoinvent database in that range.\n7)(Supplementary Figure 12) For each scenario, provide detailed information of the simulation model, including mass and enthalpy flow, temperature, pressure and composition.\n8)(Supplementary table 3) Provide detailed equipment information (specifications, quantities, prices, etc.) for each scenario. Please refer to the NREL report.\n9)(Supplementary Table 15) Please carefully check the capital cost. The capital cost of the proposed scenario appears excessively high compared to previous feasibility studies on the biorefinery.\nMinor points\n1)(p.4) Systematic evaluation revealed that in context of an I. orientalis background, the β-alanine pathway has both the highest theoretical yield of 3HP (i.e., 99.7%) as well as the most favorable (i.e., lowest) oxygen uptake requirements at high yield (i.e., only 0.018 mmol/mmol glucose) (Supplementary Fig. 2) → In Supplementary Fig. 2, several pathways other than the β-alanine pathway are not named and need clarification.\n2)(p.5) In “Design and construction of a 3HP biosynthetic pathway in I. orientalis” section\n→ When designing an optimal pathway using SSN, only non-native enzymes PAND, BAPAT, and YDFG are mentioned, but maybe PYC and AAT are not because they are native? Especially AAT case has a positive Gibbs free energy, so a specific explanation is needed on whether there is no way to optimize it or not.\n3)(p.6) qPCR analysis confirmed that the expression level of PAND increased with increasing copy number (Supplementary Fig. 7, orange bar), but production did not continually increase. Further investigation of the PYC gene revealed its elevated expression levels at three and eight PAND copies (Supplementary Fig. 7, yellow bar), suggesting that integration at the EG6 site activated PYC, boosting production.\n→ In Supplementary Fig. 7, the text should be corrected to reverse the bar colors for PAND and PYC\n4)Supplementary table order should match the order of the main text. One table is represented by “Supplementary tables”, or both “Supplementary Fig.” and “Supplementary Figure” are mixed.\n5)(p.8) For the simulated dextrose-based 3HP biomanufacturing based on experimental performance at 300 L, the biomanufacturing process could produce acrylic acid at an estimated minimum product selling price (MPSP) of $1.60/kg (baseline) with a range of $1.45−1.85/kg [5th-95th percentiles, hereafter in brackets; Fig. 5] and a CI of 4.74 kg CO2-eq./kg [4.24-5.70 kg CO2-eq./kg] (Supplementary Fig. 13).\n→ Supplementary Fig. 13 shows the graph for FEC impact, not CI. In the main text, only MPSP and CI are mentioned, but Supplementary Fig. 13 is referenced without additional explanation regarding FEC.\n6)(p.16-17) Simplified block flow diagrams of the fermentation and separation processes (Supplementary Figure 13) as well as baseline values and distributions for all parameters included in the uncertainty analysis 7 (Supplementary Table 4) are detailed in the Supplementary Information, and a full process flowsheet is available online.50\n→ Supplementary Figure 13 should be revised to 12.", "reviewer_6": "Major revision\nThis study proposed thes remarkable 3HP biomanufacturing process with the highest titer, yield and productivity among the yeast-based process using low-pH tolerant non-model yeast I. orientalis. The authors developed a simple downstream processing to recover the high purity of 3HP and a promising strategy to utilize sugar as the feedstock. This study also analyzed the economic feasibility and environmental impact of the proposed strategy for 3HP production at both the lab scale and the industrial scale. However, there are still some concerns about assessment methods and results that have an impact on the clarity of the paper. I think this paper can be published in Nature Communications after second revision of some major points.\nMajor points\n1) The authors set the functional unit of the developed system as 1 kg of produced acrylic acid, obtaining the minimum product selling price and life cycle carbon intensity of 1 kg of acrylic acid. This assessment obviously emphasizes the importance of 3HP production to be utilized as a raw material of acrylic acid, but it is inconsistent that the overall statement of the paper emphasized the low-pH tolerant non-model yeast-based production of 3HP. If TEA and LCA are performed by setting the functional unit as 3HP, or the detailed explanation of the reason setting the functional unit as 1 kg of acrylic acid is added, it is better to understand the viability of low-pH tolerant non-model yeast-based production of 3HP.", "reviewer_i": "pyruvate → lactate → lactoyl-CoA → acryloyl-CoA → 3HP-CoA → 3HP; II: pyruvate → acetyl-CoA→ malonyl-CoA → 3-oxopropanoate → 3HP; III: pyruvate → oxaloacetate→ aspartate → β-alanine → 3-oxopropanoate→ 3HP; IV: pyruvate → oxaloacetate→ aspartate → β-alanine → β-alanyl-CoA → acryloyl-CoA→ 3HP-CoA → 3HP; V: pyruvate → succinate → propionyl-CoA → acryloyl-CoA → 3HP-CoA → 3HP; VI: pyruvate → α-alanine → β-alanine → 3-oxopropanoate → 3HP; VII: pyruvate → α-alanine → β-alanine → β-alanyl-CoA → acryloyl-CoA → 3HP-CoA → 3HP. Pathway III corresponds to the β-alanine pathway in the current work. Biomass yield (left) and oxygen uptake (right) envelopes were generated using the genome-scale metabolic model iIsor85047 with reactions added as needed to enable 3HP production by the indicated pathway, and with the indicated gene deletions. Shading in the biomass yield denotes the corresponding minimal oxygen uptake rate.\nSystematic evaluation revealed that in context of an I. orientalis background, the β-alanine pathway has both the highest maximum theoretical yield of 3HP (i.e., carbon yield from glucose of 99.7% or 0.986 g 3HP/g glucose) as well as the most favorable (i.e., lowest) minimal oxygen uptake requirements at high yield (i.e., only 0.018 mmol/mmol glucose)\n3. (L106) What do you mean? Compared to what?\nFor pH 6, two non-native steps are substantially more negative (i.e., favorable) than at pH 7.\n4. (L107) The ΔG of the AAT reaction is not negative at pH 7, unlike at pH 6."}, "author_response": ""}]

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