ABSTRACT Microorganisms can be engineered to sustainably produce a variety of products including fuels, pharmaceuticals, materials, and food. However, highly engineered strains often result

in low production yield, due to undesired effects such as metabolic burden and the toxicity of intermediates. Drawing inspiration from natural ecosystems, the construction of a synthetic

community with division of labor can offer advantages for bioproduction. This approach involves dividing specific tasks among community members, thereby enhancing the functionality of each

member. In this study, we identify six pairs out of fifteen composed of six auxotrophs of _Yarrowia lipolytica_ that spontaneously form robust syntrophic and synergistic communities. We

acid (3-HP) biosynthesis pathway into the syntrophic community by dividing the pathway among different strains. Our results demonstrate improved production of 3-HP in both intra- and

interspecies communities compared to monocultures. Our results show the stable formation of synthetic syntrophic communities, and their potential in improving bioproduction processes.

SIMILAR CONTENT BEING VIEWED BY OTHERS A MOLECULAR TOOLKIT OF CROSS-FEEDING STRAINS FOR ENGINEERING SYNTHETIC YEAST COMMUNITIES Article Open access 07 February 2024 SPONTANEOUSLY ESTABLISHED

SYNTROPHIC YEAST COMMUNITIES IMPROVE BIOPRODUCTION Article Open access 29 May 2023 SYNTHETIC MICROBIAL COMMUNITIES OF HETEROTROPHS AND PHOTOTROPHS FACILITATE SUSTAINABLE GROWTH Article Open

access 30 July 2020 INTRODUCTION The advances in synthetic biology and metabolic engineering have led to improved biotechnology processes using microorganisms for the production of food,

pharmaceuticals, biofuels, and biomaterials. Despite methodological advances in our capacities to improve microbial strains, some commonly found challenges remain, including metabolic burden

due to the high level of pathway engineering, cofactor imbalance, or toxicity of intermediates and/or final products. To overcome the drawbacks of engineering single chassis strain, the

establishment of synthetic microbial communities by engineering multiple strains that cooperate during the bioprocess has been proposed1,2,3. By dividing the labor among multiple strains,

synthetic communities are able to improve the functionality of each member, reduce metabolic burden and engineering complexity, and accomplish high efficiency of production as found in

natural consortia1,2,4. In natural communities, there are various cellular interactions that determine the dynamics of the consortia, such as competition, commensalism, mutualism, or

neutralism5. When it comes to synthetic consortia, designing a proper interaction between members are crucial for constructing a stable and robust synthetic community2,3. A type of

mutualistic interaction, cross-feeding or syntrophy, requires each population that relies on each other for survival, which can provide stable coexistence by tying together the members in

the community5,6. One way to achieve cross-feeding is by using co-auxotrophic strains that exchange essential amino acids to allow each other to grow7,8. It has been generally regarded that

yeast co-cultures were not as effective as bacterial ones in forming co-auxotrophic communities, except for strains engineered to produce higher amount of amino acids8. Recently, we

performed high-throughput screening of syntrophic interactions in the model yeast _Saccharomyces cerevisiae_ by using yeast knockout library9,10. From this study, 49 pairwise auxotroph

combinations which is 3.6% of tested pairs were identified to spontaneously form syntrophic communities and some of them were tested for division of labor, leading to improved

bioproduction10. This finding suggests that cross-feeding-based communities could be formed in other yeast species, including those with high industrial potential. _Yarrowia lipolytica_ has

been gaining interests as a host strain for bioproduction of chemicals, fuels, foods, and pharmaceuticals from both academia and industry11,12. Advantageous industrial features of this yeast

include robustness, stress tolerance, being amenable by synthetic biology tools, and high cell density cultivation. Most research using _Y. lipolytica_ have focused on engineering in a

single strain. The studies on microbial communities using this yeast are so far limited. There are few studies of co-culture using _Y. lipolytica_ with other species for bioremediation or

feedstock utilization with the modulation of inoculation ratio or time among community members13,14,15,16,17,18,19,20. A study has explored division of labor for bioproduction of

amorphadiene with _Y. lipoltyica_ strains. A modular co-culture dividing the pathway for boosting precursor pools and amorphadiene synthesis resulted in the improved titers21. These works

highlight the increasing interest in creating communities of _Y. lipolytica_. However, tools for controlling population dynamics, such as cross-feeding9, to maximize robustness and

efficiency have not yet been developed in _Y. lipolytica_. In this study, we explored the creation of syntrophic communities of _Y. lipolytica_ using auxotrophic strains and identified pairs

exhibiting synergistic growths, which were further characterized. The _Y. lipolytica_ auxotrophic strains were also evaluated for establishing the interspecies syntrophic growth with _S.

cerevisiae_ auxotrophs. We finally developed a division of labor strategy for the production of a bioplastic precursor, 3-hydroxypropionic acid, employing syntrophic intraspecies and

interspecies communities, which resulted in increased bioproduction. RESULTS ESTABLISHING SYNTHETIC _Y. LIPOLYTICA_ COMMUNITIES BY ENGINEERING CROSS-FEEDING BEHAVIORS To evaluate if

auxotrophs of _Y. lipolytica_ could form syntrophic communities by exchanging essential metabolites, we constructed the strains ∆_lys5_, ∆_trp2_, ∆_trp4_, ∆_met5, ∆ura3_ and ∆l_eu2_,

auxotrophic for lysine, tryptophan, methionine, uracil, and leucine. The growth of 15 paired combinations from these six auxotrophs was tested at a 1:1 inoculation ratio in YNBD media

without amino acid supplementation. The observed growth of the tested combinations can be grouped into three categories according to their maximal OD600 during the cultivation (Fig. 1a,

Supplementary Table 1, Supplementary Figs. 1, 2): high (OD600 ≧ 0.55): ∆_ura3_-∆_trp4_, ∆_ura3_-∆_met5_, ∆_leu2_-∆_trp4_, ∆_lys5_-∆_trp4_, and ∆_trp4_-∆_met5_; moderate (0.32 ≦ OD600 < 

0.55): ∆_ura3_-∆_lys5_, ∆_ura3_-∆_trp2_, ∆_leu2_-∆_trp2_, ∆_lys5_-∆_trp2_, ∆_lys5_-∆_met5_, and ∆_trp2_-∆_trp4_; and low (OD600 < 0.32): ∆_ura3_-∆_leu2_, ∆_leu2_-∆_lys5_, ∆_leu2_-∆_met5_,

and ∆_trp2_-∆_met5_. Among the high-growth combinations, three pairs (∆_leu2_-∆_trp4_, ∆_lys5_-∆_trp4_, and ∆_trp4_-∆_met5_) showed a constant increase in growth, while the other two pairs

(∆_ura3_-∆_trp4_ and ∆_ura3_-∆_met5_) exhibited an exponential growth after a certain time of lag phase (40 and 20 hours, respectively) (Fig. 1b, Supplementary Fig. 1). Positive correlation

between growth and glucose consumption depending on the auxotroph pairs was observed (Supplementary Fig. 3). The shortest lag phase, 12 hours, was found in the combination of ∆_trp2_ and

∆_trp4_, and the stationary phase was reached at 36 hours of cultivation. While the final OD600 reached by the ∆_trp2_ and ∆_trp4_ did not rank amongst the top, it exhibited the highest

growth rate compared to other combinations (Supplementary Table 1). The prolonged lag phase in some of the synthetic communities could be originated by the needs of each population to adapt

their metabolism to export metabolites, which is required by its partner, and/or to import metabolites secreted from the partner10. CHARACTERIZATION OF GROWTH DYNAMICS OF SYNTHETIC

CROSS-FEEDING COMMUNITIES We characterized population dynamics of three selected pairs (∆_ura3_-∆_trp4_, ∆_trp4_-∆_met5_, and ∆_trp2_-∆_trp4_) by varying the inoculation ratios from 10:1 to

1:10 (Fig. 2). Changes in inoculation ratios exhibited considerable differences in growth patterns, which suggest that certain population ratios favor syntrophic growth. In the pair of

∆_ura3_-∆_trp4_, the inoculation ratios of 10:1 and 5:1 showed a shorter lag phase than other ratios, suggesting the importance of having more ∆_ura3_ cells at the beginning of the culture

(Fig. 2a). Despite the shorter lag phase for these ratios, all inoculation ratios reached a similar final OD600 at 120 hours. In addition, regardless of the initial ratio, the population

tended to stabilize at the end of the stationary phase, maintaining a ratio of ∆_ura3_:∆_trp4_ between 1:1.2 and1:1.8 (Fig. 2d, g, Supplementary Fig. 5). In the case of ∆_met5_-∆_trp4_ pair,

the coculture with initial ratios of 1:1, 1:5 and 1:10 started growing earlier than those with 10:1 and 5:1 (Fig. 2b). At ratios of 10:1 and 5:1, the cocultures showed a mild growth until

48 hours followed by exponential phase. The final OD600 was correlated with the inoculation ratio from 1:10 to 10:1 which also corresponded to glucose consumption (Supplementary Fig. 4). At

the stationary phase, the population ratio was stabilized in all cases (∆_met5_:∆_trp4_ between 1:1.0 and 1:1.9 (Fig. 2e, h, Supplementary Fig. 6). The pair of ∆trp2-∆_trp4_ showed a faster

growth at all inoculation ratios compared to other combination tested (Fig. 2c). The ratio 1:10 showed the shortest lag followed by 1:5 and 1:1, while the ratios of 5:1 and 10:1 resulted in

a longer lag phase and lower final OD600. Since the mutations ∆_trp2_ and ∆_trp4_ are both mapped in the same tryptophan synthesis pathway, the growth between these two auxotrophs is

achieved by the exchange of intermediates, which are known to be anthranilate and indole/tryptophan in _S. cerevisiae_10. In _S. cerevisiae_, the coculture of ∆_trp2_-∆_trp4_ was naturally

highly enriched in one population, ∆_trp2_ cells, after inoculating at 1:1 ratio. Similarly, a majority of ∆_trp2_ cells were found in the _Y. lipolytica_ coculture at 10:1 and 5:1

inoculation ratios, which showed a slower and lower growth compared to other inoculation ratios (Fig. 2f, Supplementary Fig. 7). However, in _Y. lipolytica_, the ratio resulting in better

growth exhibited different population dynamics, the ratio of ∆_trp2_:∆_trp4_ at the stationary phase was 1:1.5 from the inoculation ratio of 1:5 and 1:10 (Fig. 2i). These considerable

distinct population dynamics between two species suggest differences in metabolite exchange rates or mechanisms between _S. cerevisiae_ and _Y. lipolytica_. ESTABLISHING CROSS-FEEDING

COMMUNITIES BETWEEN TWO YEAST SPECIES, _Y. LIPOLYTICA_ AND _S. CEREVISIAE_ After demonstrating the formation of stable cross-feeding co-cultures between two _Y. lipolytica_ auxotrophs, we

decided to test whether the syntrophic growth could be established between the two species, _Y. lipolytica_ and _S. cerevisiae_. We selected the _Y. lipolytica_ auxotrophs described above

(YL_Δtrp2_, YL_Δtrp4_, YL_Δmet5_, and YL_Δlys5)_ and the _S. cerevisiae_ ones based on our previous study (SC_Δtrp2_, SC_Δtrp4_, SC_Δmet5_, and SC_Δlys5)_10. Three pairs

(YL_Δtrp2_-SC_Δtrp4_, SC_Δtrp2_-YL_Δtrp4_, and SC_Δmet5_-YL_Δtrp4_) showed syntrophic growth in the interspecies coculture (Fig. 3a, Supplementary Fig. 8). The growth dynamics differed

depending on the auxotrophies and species involved. For example, the pair of YL_Δmet5_-SC_Δtrp4_ did not grow while SC_Δmet5_-YL_Δtrp4_ showed higher OD600 than the coculture of

YL_Δmet5_-YL_Δtrp4_. This might be due to the different metabolite exchange rates among species. As SC_Δtrp2-_YL_Δtrp4_ pair showed higher growth compared to other auxotrophic pairs, we

further characterized the population dynamics of SC_Δtrp2-_YL_Δtrp4_ and YL_Δtrp2-_YL_Δtrp4_ by inoculating different ratios (Fig. 3b–e, Supplementary Figs. 9 and 10). Both cocultures showed

better growth at 1:1, 1:5, and 1:10 initial ratios. However, the inoculation ratios of 10:1 and 5:1 in SC_Δtrp2-_YL_Δtrp4_ failed to grow, which could indicate that the exchange of the

intermediate (anthranilate) was not enough for SC_Δtrp2_ to grow in these conditions. The populations of SC_Δtrp2-_YL_Δtrp4_ stabilized between the ratios of 1:0.9 and 1:1.5 at the

stationary phase, which differs from the skewed population distribution of the SC_Δtrp2-_SC_Δtrp4_ coculture. To validate whether different cultivation conditions affect the syntrophic

growth of SC_Δtrp2_-YL_Δtrp4_, especially regarding a potential influence of the Crabtree effect, co-cultures of SC_Δtrp2_-YL_Δtrp4_ with different glucose concentrations (20 and 100 g/L)

and aeration condition (aerobic and semi-anaerobic) were performed (Supplementary Fig. 11). At 20 g/L of glucose, the coculture SC_Δtrp2_ : YL_Δtrp4_ showed growth at 1:1 ratio in

semi-anaerobic conditions, while no growth was observed in aerobic conditions. We observed a higher production of ethanol in the 1:1 ratio than in the 1:10 ratio, suggesting the Crabtree

effect helped the growth of SC_∆trp2_. At a higher glucose concentration (100 g/L), in both aerobic and semi-anaerobic conditions, we generally observed higher growth when there was a higher

presence of the _∆trp4_ strain. In the SC-YL co-culture, we observed the Crabtree effect, as reflected by the ethanol production (100 g/L glucose, semi-anaerobic condition) that seemed to

come from SC_∆trp2_. As expected, a negligible amount of ethanol was observed in YL-YL co-culture in the same condition. DIVISION OF LABOR IN CROSS-FEEDING COMMUNITIES IMPROVES BIOPRODUCTION

Splitting metabolic pathways between strains in communities (division of labor) can be effective for bioproduction as it can reduce metabolic burden and avoid bottlenecks or toxic

intermediates2. As a proof of concept, we aimed to synthesize a value-added molecule by splitting the biosynthesis pathway into a cross-feeding community. We selected the Δ_trp2_-Δ_trp4_

pair because of its shorter lag phase and more rapid growth (Fig. 1). 3-Hydroxypropionic acid (3-HP, C3H6O3) is a desired platform chemical with a wide range of applications, as identified

by the US Department of Energy in 2004. It is a precursor of acrylic acid, 1, 3-propandiol, malonic acid, biodegradable polyesters, and other valuable chemicals22,23. In order to synthesize

3-HP, we selected the biosynthetic pathway through β-alanine and malonic semialdehyde, which has not yet been applied in _Y. lipolytica_. This pathway requires the expression of three

enzymes, aspartate-1-decarboxylase (TcPAND from _Tribolium castaneum_), β-alanine-pyruvate aminotransferase (BcBAPAT from _Bacillus cereus_), and 3-hydroxypropanoate dehydrogenase (EcYDFG

from _Escherichia coli_) (Fig. 4a)23. The 3-HP pathway was split into module P, expressing TcPAND, and module B, expressing BcBAPAT and EcYDFG. Each module is integrated into two distinct

auxotrophic strains, thereby generating a community that relies on the transport of β-alanine from one strain to another for producing 3-HP (Fig. 4b). First, we tested intraspecies _Y.

lipolytica_ communities with division of labor and compared them with two WT controls, monoculture and coculture (Fig. 4, Supplementary Figs. 12 and 15). The WT monoculture bears three

enzymes without division of labor and the WT coculture is composed of two strains, one harboring module P (WT-P) and the other module B (WT-B), thereby implementing division of labor but

without cross-feeding. The growth was comparable between the WT monoculture and the WT coculture (Fig. 4c). The production of 3-HP was two times lower in the WT coculture compared to the WT

monoculture (Fig. 4d), suggesting that division of labor, without cross-feeding, was not beneficial. In the case of the cross-feeding communities, the growth varied depending on the

inoculation ratio of the strains Δ_trp2_ with module B (Δ_trp2-_B) and Δ_trp4_ with module P (Δ_trp4_-P) (Fig. 4c), which is consistent with the result shown in Fig. 3c. When the initial

ratio was 1:10 (Δ_trp2-_B:Δ_trp4_-P), the synthetic community reached a similar OD600 as the WT monoculture after 48 hours of cultivation (Fig. 4c). However, the growth of coculture with

initial ratios of 1:1 and 10:1 resulted in lower growth. The production of metabolites varied significantly with the inoculation ratio. Coculture at the ratio of 1:10 showed a comparable

3-HP production (0.26 mM) to one from the WT monoculture. The coculture of Δ_trp2-_B and Δ_trp4_-P with an initial ratio of 10:1 reached a production of 4.67 mM of 3-HP, which is 19.3 times

higher than the WT monoculture. Instead, WT monoculture produced higher citrate than co-culture (Supplementary Figs. 15 and 16). The higher ratio of module B in the communities showed higher

3-HP production, suggesting that the conversion of β-alanine to 3-HP is more important than the one from L-aspartate to β-alanine for higher production of 3-HP. As cross-feeding communities

were successfully established between _Y. lipolytica_ and _S. cerevisiae_, we then decided to study the division of labor within this interspecies community. The strain pairs

YL_Δtrp2-_SC_Δtrp4_ and SC_Δtrp2-_YL_Δtrp4_, each with different 3-HP synthesis modules, were cultured using different initial inoculation ratios (Fig. 4, Supplementary Fig. 13).

Consistently with what was observed for the corresponding cocultures without 3-HP bioproduction modules (Fig. 3c), different growth and metabolite profiles were observed depending on the

inoculation ratio (Supplementary Fig. 10). The production of 3-HP varied depending on the combination of species and modules used for 3-HP production. Higher 3-HP production was commonly

obtained with the ratio of B:P = 10:1 which is consistent with the result of _Y. lipolytica_ intraspecies communities. This also demonstrates an effective transport of β-alanine from the

_Δtrp2-_P strain to the _Δtrp4-_B strain in the syntrophic community. The highest 3-HP production from interspecies communities was achieved at 10:1 ratio of SC_Δtrp2_-B_:_YL_Δtrp4_-P,

reaching 4.50 mM which is 40.3 and 18.6 times higher than the one from the WT monoculture of _S. cerevisiae_ and _Y. lipolytica_, respectively (Fig. 4d, Supplementary Fig. 14). Therefore,

these results successfully demonstrated an improvement of 3-HP production through pathway split (and likely division of labor) in both types of synthetic cross-feeding communities, the

intraspecies of _Y. lipolytica_ and the interspecies of _Y. lipolytica_ and _S. cerevisiae_. DISCUSSION In nature, many microorganisms are auxotrophs and therefore rely on external nutrients

(including amino acids) for their growth24. This observation has inspired synthetic biologists to design synthetic communities using amino acid or nucleotide auxotrophic strains. The

requirement on essential metabolites exchange promotes cooperative behaviors and beneficial interactions. Recent studies on synthetic communities often require a high level of engineering to

maintain the stability of the coculture and control the population25,26, which limit the applicability and universality of these methods. Auxotrophic-based cross-feeding offers a simpler

alternative to creating stable communities. However, identifying the adequate pairs of auxotrophs able to establish syntrophic interactions is challenging as metabolic costs and energy

requirements for the synthesis of each amino acid or metabolite vary and their transport systems are not fully understood27,28,29. Here, we aimed to uncover spontaneous syntrophic

communities in _Y. lipolytica_. Out of fifteen combinations involving six auxotroph strains, five exhibited robust syntrophic growth, and six demonstrated a slower but still discernible

growth at an initial ratio of 1:1. Further investigation by modulating the initial inoculation ratio could potentially unveil additional auxotrophic pairs capable of establishing syntrophic

communities. Generally, the success of syntrophic interaction is thought to be determined by the rates of import, export, and consumption of the involved metabolites, as the depletion of one

of the metabolites before establishing the syntrophy can lead to the collapse of the community30. Therefore, pairs that failed to establish spontaneous syntrophic interactions might be

attributed to low production or a limited transport system of specific metabolites that need to be provided to the other member of the community. Engineering strains to overproduce specific

metabolites through the regulation of feed-back inhibition or the strengthening carbon flux towards their synthesis could be beneficial in promoting syntrophic interactions, as demonstrated

independently in both _E. coli_ and _S. cerevisiae_8,9,31. At a more fundamental level, it would be beneficial to study the transport mechanisms of metabolites, including amino acids in _Y.

lipolytica_. Understanding the secretion or uptake of metabolites is pivotal in order to improve stable syntrophic interactions. Employing omics approaches, such as metagenomic sequencing7

and exometabolomic analysis32,33 could contribute to unravel some of these transport systems and better understand microbial cross-feeding within synthetic communities. In this work, we also

demonstrated spontaneous syntrophic growth between two yeast species, _Y. lipolytica_ and _S. cerevisiae_. A pair of _Δtrp2_-_Δtrp4_ demonstrated successful syntrophic interaction between

two strains regardless of the combination of the auxotroph pairs and the species. In _S. cerevisiae_ communities, _Δtrp2_-_Δtrp4_ has been described to exhibit an extremely unbalanced

population distribution, with one strain dominating the coculture (over 95% of ∆_trp2_)10. A similar trend was observed in the _Y. lipolytica_ communities at inoculation ratios of 10:1 and

5:1, however, the population was more balanced (∆_trp2_:∆_trp4_ of 1:0.9-1.5) at the ratio of 1:5 and 1:10 (Fig. 2f, i). In the interspecies coculture of _Δtrp2_-_Δtrp4_, a balanced

population was achieved in all tested strains, species, and ratios (Fig. 3e), highlighting the potential of interspecies syntrophic communities to provide an additional level of control. In

specific inoculation ratios (10:1 and 1:1) of the SC_Δtrp2-_YL_Δtrp4_ coculture, growth failed to occur, suggesting an insufficient exchange of metabolites in this experimental condition.

Similarly, the pair of YL_Δmet5_-SC_Δtrp4_ was unable to grow, while SC_Δmet5_-YL_Δtrp4_ grew. This observation might also be explained by different exchange rates of metabolites in

different species7,10. Interdependent cocultures for bioproduction have so far mostly been explored using model microorganisms1,34. Our results suggest a broader applicability of syntrophic

interactions beyond model microorganisms, paving the way for designing synthetic communities of non-conventional yeasts for bioproduction. To study the effect of division of labor and

cross-feeding in bioproduction by synthetic communities, we divided the biosynthetic pathway of 3-HP into two modules. The coculture of YLΔ_trp2-_B and YLΔ_trp4_-P, with an initial ratio of

10:1, produced 19.3 times higher 3-HP (4.67 mM) than the WT monoculture harboring the complete 3-HP synthetic pathway in a single strain. Notably, this synthetic pathway converting β-alanine

into 3-HP was investigated in _Y. lipolytica_ for the first time in this study. The growth and metabolite analysis (Supplementary Fig. 16) suggests that the higher 3-HP production found in

the co-cultures originated from a higher availability of pyruvate, a common precursor of 3-HP and citrate. This result underscores that the division of labor within a synthetic community can

be used to validate undiscovered synthetic pathways, in addition to the traditional approach of embedding the entire pathway in a single strain. The production of 3-HP was further improved

in the interspecies cross-feeding community, YL Δ_trp2-_B and SC Δ_trp4_-P at a 10:1 inoculation ratio, reaching 3.96 mM of 3-HP. This is slightly higher than the reported 0.35 g/L (3.88 mM)

of 3-HP production in _Y. lipolytica_ harboring the alternative pathway from malonyl-CoA22. When it comes to MSA production in _S. cerevisiae_ communities, the coculture of

_Δtrp2_-B:_Δtrp4_-P = 10:1 produced the highest MSA among different inoculation ratios but also outperformed the monoculture, which is consistent with the MSA production in a previous study

of _S. cerevisiae_ communities (Supplementary Table 4 and Supplementary Figs. 14 and 18)10. However, the production of MSA in _S. cerevisiae_ co-culture at _Δtrp2_-B:_Δtrp4_-P = 1:1 and 1:10

was negligible, although it was higher than the monoculture in the previous study. This might be due to the different promoters used for expressing BAPAT in each study, additional gene

expression (YDFG) in this study, and different cultivation scales. In the case of 3-HP production, _S. cerevisiae_ co-culture at specific inoculation ratio (_Δtrp2_-B:_Δtrp4_-P = 1:1)

performed better than the _S. cerevisiae_ monoculture (Supplementary Fig. 14, Supplementary Table 4). The level of total metabolites produced from the _Δtrp2_-B strain (MSA and 3-HP) in the

coculture of _Δtrp2_-B:_Δtrp4_-P = 10:1 is higher than the one from the monoculture (Supplementary Table 4 and Supplementary Fig. 14). In this study, we used the biosynthetic pathway of 3-HP

as a proof of concept, but further modifications can lead to improve titers. Increased production is expected through additional engineering strategies such as promoter engineering,

multi-copy integration, and precursor and/or cofactor supply. Overall, this work demonstrates that the combination of cross-feeding and inoculation ratio to control population dynamics in

synthetic yeast communities with division of labor has the potential to improve the production of valuable molecules. It is worth noting that further research is required to understand the

complex relationship between division of labor and bioproduction and fully correlate them both. The strategy described here could be expanded to multiple organisms (and their combination)

and compounds of interest. In conclusion, we successfully demonstrated the establishment of a stable synthetic cross-feeding yeast community employing auxotrophs of _Y. lipolytica_, an yeast

of high industrial interest. Synthetic communities of _Y. lipolytica_ were characterized in terms of growth and population dynamics, considering different auxotrophic pairs and inoculation

ratios. Our findings confirmed that specific auxotrophs can exchange metabolites with other members, facilitating spontaneous growth in both intraspecies (_Y. lipolytica_) and interspecies

(_Y. lipolytica_ and _S. cerevisiae_) communities. We further explored the division of labor and bioproduction of 3-HP within these syntrophic communities. Notably, we found a 3-HP

production improvement by 19.3 and 18.6 times when labor was divided in intra- and interspecies communities compared to the _Y. lipolytica_ monoculture, respectively. This study represents

the first demonstration of a division of labor for biosynthetic heterologous pathway using syntrophic communities of _Y. lipolytica_. Our findings shed light on the potential of utilizing

non-conventional microorganisms to form enhanced synthetic communities for bioproduction of various value-added molecules. METHODS STRAINS AND MEDIA The _E. coli_ strains DH5α and TOP10 were

used for plasmid construction. _E. coli_ strains were grown at 37 °C in Luria−Bertani (LB) medium (containing 1% tryptone, 0.5% yeast extract, and 1% sodium chloride) or on LB agar with

appropriate antibiotics. PCR amplifications were performed in a PCR ProFlexTM (Applied Biosystems) with Q5 High-Fidelity DNA Polymerase (New England Biolabs). PCR fragments were purified

with a QIAgen Purification Kit (Qiagen). The plasmids used in this study were constructed by Golden Gate Assembly, as described in Yuzbashev et al.35. In brief, each component for GG

assembly was cloned to Lv0 plasmid by using BsmBI. Lv1 plasmid containing the specific overhang for Lv2 plasmid was then constructed by assembling the Lv0 plasmid consisting of promoter,

gene, and terminator using BsaI. Finally, the Lv2 plasmid containing two or three transcription units was constructed by using BsmBI. To verify the correct construction of plasmids, PCR with

GoTaq DNA polymerases (Promega) and digestion by restriction enzyme (New England Biolabs) were carried out. _Y. lipolytica_ was routinely grown at 30 °C in YPD medium which consists of 1%

yeast extract, 2% peptone, and 2% glucose, or yeast synthetic medium (YNBD) which includes 0.17% yeast nitrogen base without amino acids and ammonium sulfate, 0.5% ammonium chloride, 50 mM

phosphate buffer (KH2PO4-Na2HPO4, pH6.8), and 2% glucose. To prepare the solid medium, 1.5% agar was added to the respective liquid medium. To complement auxotrophic processes, uracil,

leucine, lysine, methionine, or tryptophan were added at a concentration of 0.1 g/L, as necessary. To introduce gene expression cassettes into _Y. lipolytica_, NotI-linearized plasmids were

transformed into competent cells by the lithium acetate/DTT method. The gene expression cassettes were randomly integrated into the genome of _Y. lipolytica_. Transformants were selected on

YNBD media containing the appropriate amino acids for their specific genotype. Positive transformants were then confirmed by colony PCR with Phire Plant Direct PCR master mix (Thermo

Fisher). Auxotroph strains were constructed by homologous recombination of promoter and terminator region of marker gene. The resulting auxotroph strains were verified on YNBD media

with/without the corresponding amino acids. The removal of the selection marker was carried out via the Cre-LoxP system. The strains and plasmids used in this study are listed in Table 1.

The primers used for cloning and verification are listed in Supplementary Table 2. The sequence of heterologous genes for 3-HP synthesis are listed in Supplementary Table 3. GROWTH AND

FLUORESCENCE ANALYSIS OF YEAST CO-CULTURE IN 96 WELL PLATE The yeast strains were initially cultured in YPD medium and cultivated overnight at 30 °C and 250 rpm. The cells were then washed

three times with distilled water. Subsequently, the cells were inoculated into a 96-well plate containing 200 μl of YNBD media in triplicate. The initial OD600 of culture, both monoculture

and co-culture, was adjusted to 0.1. The inoculation ratios of the co-culture varied between 10:1, 5:1, 1:1, 1:5, and 1:10. The plate was incubated at 30 °C with continuous shaking for 120 

hours. The growth and fluorescence of each strain were monitored using a Spark Tecan or Biotek instrument every 30 min using the following settings: OD600, absorbance at 600 nm; GFP,

excitation at 485 nm and emission at 535 nm; RFP, excitation at 560 nm and emission at 620 nm; mTAGBFP2, excitation at 400 nm and emission at 465 nm; and mScarlet-I, excitation at 560 nm and

emission at 620 nm. POPULATION ANALYSIS BY FLOW CYTOMETRY Population of each member in the synthetic community was calculated by the different fluorescence of each strain. Cell fluorescence

was measured by an Attune NxT Flow Cytometer (Thermo Scientific) with the following settings: FSC 100 V, SSC 355 V, BL1 345 V, YL2 510 V. Attune Cytometric software was used for data

collection. Fluorescence data was collected from at least 10,000 cells for each experiment with three biological replicates. GROWTH ANALYSIS OF YEAST CO-CULTURE FOR 3-HP PRODUCTION IN FLASK

The strains were initially cultured in YNBD medium with tryptophan and cultivated overnight at 30 °C and 250 rpm. The cells were then washed three times with distilled water. Subsequently,

the cells were inoculated into the flask containing 10 ml of YNBD media at the initial OD of 0.1, for both monoculture and co-culture. The cells were incubated at 30 °C with 250 rpm for 120 

hours. Samples were taken during cultivation to measure the OD600 and quantify metabolites in the pathway of 3-HP. OD600 values from flask samples were measured by using cuvettes in a

UV/Visible spectrophotometer (Biochrom WPA Lightwave II) then normalized by using calibration curve (Supplementary Fig. 17) to compare OD600 values between microplate reader and

spectrophotometer measured in this study. Raw OD600 data from each spectrophotometer are included in Supplementary Table 5. QUANTIFICATION OF METABOLITES Metabolites including glucose,

glycerol, citrate, and ethanol were analyzed by HPLC. The supernatant of cultures at each time point was diluted twenty times with distilled water before the analysis. The HPLC system was

equipped with an Thermo Fisher UltiMate 3000 system and Aminex HPX-87H column (300 mm × 7.8 mm, Bio-RAD, USA) coupled to UV (210 nm) and RI detectors. The mobile phase used was 0.01 N H2SO4

with a flow rate of 0.6 mL/min and the column temperature was T = 35 °C. The raw data from HPLC were processed by Chromeleon software (Thermo Scientific). Concentration of metabolites was

quantified by the calibration curve of each standard. Metabolites in the 3-HP pathway, β-alanine, malonic semialdehyde, and 3-HP, were analyzed by LC-MS. The supernatant of cultures at each

time point was diluted four times with 50% acetonitrile for the analysis. The LC-MS system was equipped with an Agilent 1290 Infinity LC system with an Agilent 6550 quadrupole time-of-flight

mass spectrometer. An Agilent Poroshell 120 HILIC-Z, 2.1 × 100 mm, 1.9 µm, column was used at a temperature of 45 °C with a solvent flow rate of 0.25 ml min−1. LC separation was performed

with buffer A (10 mM ammonium formate in water) and buffer B (10 mM ammonium formate in water:ACN 10:90 (vol:vol)). After 0.5 min at 98% buffer B, the composition was changed to 5% buffer B

over 2.5 min, then held at 5% buffer B for 1 min. Injection volume was 1 μl, and negative ion spectra were recorded over a mass range of 100–1000 m/z at a rate of 1 spectrum per second. All

metabolites were qualified by the functional m/z values. β-Alanine and 3-HP were quantified by the calibration curve of the standards. Malonic semialdehyde was semi-quantified by the

standard curves of β-alanine10. The raw data from LC-MS were processed by Agilent MassHunter Qualitative Analysis software (Supplementary Table 6). STATISTICS AND REPRODUCIBILITY All

experimental data were analyzed using Microsoft Excel 365 and Prism 9.5.0 (GraphPad) software. The error bars in the Figs. 1, 2, and 3 correspond to the standard deviation from _N_ = 3

biologically independent samples as described in figure legend. Statistical analyzes were conducted using one-way ANOVA, followed by Bonferroni’s multiple comparisons test with 95%

confidence intervals, and _p_ values are provided in the source data. The error bars in the Fig. 4 correspond to the standard deviation from _N_ = 2 biologically independent samples as

described in figure legend. REPORTING SUMMARY Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. DATA AVAILABILITY All data

generated or analyzed in this study are included in the manuscript and its supplementary information. Source data are provided with this paper. REFERENCES * Tsoi, R., Dai, Z. & You, L.

Emerging strategies for engineering microbial communities. _Biotechnol. Adv_. 37, 107372 (2019). * McCarty, N. S. & Ledesma-Amaro, R. Synthetic biology tools to engineer microbial

communities for biotechnology. _Trends Biotechnol._ 37, 181–197 (2019). Article  CAS  PubMed  Google Scholar  * Bittihn, P., Din, M. O., Tsimring, L. S. & Hasty, J. Rational engineering

of synthetic microbial systems: from single cells to consortia. _Curr. Opin. Microbiol._ 45, 92–99 (2018). Article  CAS  PubMed  Google Scholar  * Darvishi, F., Rafatiyan, S., Abbaspour

Motlagh Moghaddam, M. H., Atkinson, E. & Ledesma-Amaro, R. Applications of synthetic yeast consortia for the production of native and non-native chemicals. _Crit. Rev. Biotechnol._ 0,

1–16 (2022). Google Scholar  * Bernstein, H. C. & Carlson, R. P. Microbial consortia engineering for cellular factories: In vitro to in silico systems. _Comput. Struct. Biotechnol. J._

3, e201210017 (2012). Article  PubMed  Google Scholar  * Shong, J., Jimenez Diaz, M. R. & Collins, C. H. Towards synthetic microbial consortia for bioprocessing. _Curr. Opin.

Biotechnol._ 23, 798–802 (2012). Article  CAS  PubMed  Google Scholar  * Mee, M. T., Collins, J. J., Church, G. M. & Wang, H. H. Syntrophic exchange in synthetic microbial communities.

_Proc. Natl. Acad. Sci. USA_. 111, E2149–56 (2014). * Shou, W., Ram, S. & Vilar, J. M. G. Synthetic cooperation in engineered yeast populations. _Proc. Natl Acad. Sci. USA._ 104,

1877–1882 (2007). Article  ADS  CAS  PubMed  Google Scholar  * Peng, H. et al. A molecular toolkit of cross-feeding strains for engineering synthetic yeast communities.

https://doi.org/10.1038/s41564-023-01596-4 (2023). * Aulakh, S. K. et al. Spontaneously established syntrophic yeast communities improve bioproduction. _Nat. Chem. Biol._ 19, 951–961 (2023).

Article  CAS  PubMed  Google Scholar  * Abdel-Mawgoud, A. M. et al. Metabolic engineering in the host Yarrowia lipolytica. _Metab. Eng._ 50, 192–208 (2018). Article  CAS  PubMed  Google

Scholar  * Park, Y. K. & Ledesma-Amaro, R. What makes Yarrowia lipolytica well suited for industry? _Trends Biotechnol._ 41, 242–254 (2023). Article  CAS  PubMed  Google Scholar  *

Theerachat, M., Tanapong, P. & Chulalaksananukul, W. The culture or co-culture of candida rugosa and yarrowia lipolytica strain rM-4A, or incubation with their crude extracellular lipase

and laccase preparations, for the biodegradation of palm oil mill wastewater. _Int. Biodeterior. Biodegrad._ 121, 11–18 (2017). Article  CAS  Google Scholar  * Hosseini, F., Hadian, M.,

Lashani, E. & Moghimi, H. Simultaneous bioreduction of tellurite and selenite by Yarrowia lipolytica, Trichosporon cutaneum, and their co-culture along with characterization of

biosynthesized Te–Se nanoparticles. _Microb. Cell Fact._ 22, 1–13 (2023). Article  Google Scholar  * Zhong, Y. et al. Enhanced nitrogen removal via Yarrowia lipolytica-mediated nitrogen and

related metabolism of Chlorella pyrenoidosa from wastewater. _Front. Bioeng. Biotechnol._ 11, 1–12 (2023). Article  Google Scholar  * Koutinas, M., Patsalou, M., Stavrinou, S. & Vyrides,

I. High temperature alcoholic fermentation of orange peel by the newly isolated thermotolerant Pichia kudriavzevii KVMP10. _Lett. Appl. Microbiol._ 62, 75–83 (2016). Article  CAS  PubMed 

Google Scholar  * Liu, X. et al. One-pot fermentation for erythritol production from distillers grains by the co-cultivation of Yarrowia lipolytica and Trichoderma reesei. _Bioresour.

Technol._ 351, 127053 (2022). Article  CAS  PubMed  Google Scholar  * Liu, X., Lv, J., Zhang, T. & Deng, Y. Direct Conversion of Pretreated Straw Cellulose into Citric Acid by

Co-cultures of Yarrowia lipolytica SWJ-1b and Immobilized Trichoderma reesei Mycelium. _Appl. Biochem. Biotechnol._ 173, 501–509 (2014). Article  CAS  PubMed  Google Scholar  * Bai, S. et

al. Mutualistic microbial community of Bacillus amyloliquefaciens and recombinant Yarrowia lipolytica co-produced lipopeptides and fatty acids from food waste. _Chemosphere_ 310, 136864

(2023). Article  CAS  PubMed  Google Scholar  * Ariana, M. & Hamedi, J. Enhanced production of nisin by co-culture of Lactococcus lactis sub sp. lactis and Yarrowia lipolytica in

molasses based medium. _J. Biotechnol._ 256, 21–26 (2017). Article  CAS  PubMed  Google Scholar  * Marsafari, M., Azi, F., Dou, S. & Xu, P. Modular co-culture engineering of Yarrowia

lipolytica for amorphadiene biosynthesis. _Microb. Cell Fact._ 21, 1–10 (2022). Article  Google Scholar  * Liu, S. et al. Engineering 3-Hydroxypropionic Acid Production from Glucose in

Yarrowia lipolytica through Malonyl-CoA Pathway. _J. Fungi_ 9, 573 (2023). * Borodina, I. et al. Establishing a synthetic pathway for high-level production of 3-hydroxypropionic acid in

Saccharomyces cerevisiae via β-alanine. _Metab. Eng._ 27, 57–64 (2015). Article  CAS  PubMed  Google Scholar  * Zengler, K. & Zaramela, L. S. The social network of microorganisms - How

auxotrophies shape complex communities. _Nat. Rev. Microbiol._ 16, 383–390 (2018). Article  CAS  PubMed  Google Scholar  * Zhang, H. & Wang, X. Modular co-culture engineering, a new

approach for metabolic engineering. _Metab. Eng._ 37, 114–121 (2016). Article  PubMed  Google Scholar  * Brenner, K., You, L. & Arnold, F. H. Engineering microbial consortia: a new

frontier in synthetic biology. _Trends Biotechnol._ 26, 483–489 (2008). Article  CAS  PubMed  Google Scholar  * Kaleta, C., Schäuble, S., Rinas, U. & Schuster, S. Metabolic costs of

amino acid and protein production in Escherichia coli. _Biotechnol. J._ 8, 1105–1114 (2013). Article  CAS  PubMed  Google Scholar  * Raiford, D. W. et al. Do amino acid biosynthetic costs

constrain protein evolution in Saccharomyces cerevisiae? _J. Mol. Evol._ 67, 621–630 (2008). Article  ADS  CAS  PubMed  Google Scholar  * Barton, M. D., Delneri, D., Oliver, S. G., Rattray,

M. & Bergman, C. M. Evolutionary systems biology of amino acid biosynthetic cost in yeast. _PLoS One_ 5, e11935 (2010). * Campbell, K. et al. Self-establishing communities enable

cooperative metabolite exchange in a eukaryote. _Elife_ 4, 1–23 (2015). Article  CAS  Google Scholar  * Kerner, A., Park, J., Williams, A. & Lin, X. N. A programmable Escherichia coli

consortium via tunable symbiosis. _PLoS One_ 7, e34032 (2012). Article  ADS  CAS  PubMed  Google Scholar  * Lubbe, A., Bowen, B. P. & Northen, T. Exometabolomic analysis of cross-feeding

metabolites. _Metabolites_ 7, 50 (2017). * Chodkowski, J. L. & Shade, A. Exometabolite dynamics over stationary phase reveal strain-specific responses. _mSystems_ 5, 50 (2020). * Zhou,

K., Qiao, K., Edgar, S. & Stephanopoulos, G. Distributing a metabolic pathway among a microbial consortium enhances production of natural products. _Nat. Biotechnol._ 33, 377–383 (2015).

Article  CAS  PubMed  Google Scholar  * Yuzbashev, T. V. et al. A DNA assembly toolkit to unlock the CRISPR/Cas9 potential for metabolic engineering. _Commun. Biol_. 6, 858 (2023). Download

references ACKNOWLEDGEMENTS R.L-A. received funding from BBSRC (BB/R01602X/1, BB/T013176/1, BB/T011408/1 - 19-ERACoBioTech- 33 SyCoLim, BB/X01911X/1, BB/Y008510/1 – Engineering Biology Hub

for Microbial Foods), EPSRC (AI-4-EB BB/W013770/1, and EEBio Programme Grant EP/Y014073/), Yeast4Bio Cost Action 18229, European Research Council (ERC) (DEUSBIO - 949080), the Bio-based

Industries Joint (PERFECOAT- 101022370) under the European Union’s Horizon 2020 research and innovation programme and the European Innovation Council (EIC) under grant agreement No.

101098826 (SKINDEV). Also Bezos Earth Fund for their support to the Bezos Centre for Sustainable Protein. Imperial College London UKRI Impact Acceleration Account (EPSRC –EP/X52556X/1, BBSRC

-BB/X511055/1). Y.-K.P received funding from the Bio-based Industries Joint (PERFECOAT - 101022370) under the European Union’s Horizon 2020 research and innovation programme. H.P. from the

European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No. 899987. P.H. received funding from BBSRC BB/T013176/1. LSV received funding

from BB/T011408/1 - 19-ERACoBioTech- 33 SyCoLim. Thanks to D. J. Bell for the analytical support from the SynbiCITE Innovation and Knowledge Centre at Imperial College London. AUTHOR

INFORMATION AUTHORS AND AFFILIATIONS * Department of Bioengineering and Centre for Synthetic Biology, Imperial College London, London, UK Young-Kyoung Park, Huadong Peng, Piotr Hapeta, Lara

Sellés Vidal & Rodrigo Ledesma-Amaro * Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, Jouy-en-Josas, France Young-Kyoung Park * Australian Institute of Bioengineering

and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia Huadong Peng Authors * Young-Kyoung Park View author publications You can also search for this author

inPubMed Google Scholar * Huadong Peng View author publications You can also search for this author inPubMed Google Scholar * Piotr Hapeta View author publications You can also search for

this author inPubMed Google Scholar * Lara Sellés Vidal View author publications You can also search for this author inPubMed Google Scholar * Rodrigo Ledesma-Amaro View author publications

You can also search for this author inPubMed Google Scholar CONTRIBUTIONS Y.K.P. and R.L.A. conceived the project. Y.K.P. constructed plasmids and _Y. lipolytica_ strains, characterized the

strains, and analyzed the results. H.P. constructed _S. cerevisiae_ strains. P.H. constructed plasmids. L.S.V. performed preliminary coculture experiments, statistics and edited figures.

R.L.A. supervised the work. Y.K.P. drafted the manuscript. All authors read and edit the manuscript. CORRESPONDING AUTHOR Correspondence to Rodrigo Ledesma-Amaro. ETHICS DECLARATIONS

COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Communications_ thanks the anonymous reviewers for their contribution to the peer

review of this work. A peer review file is available. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and

institutional affiliations. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION REPORTING SUMMARY TRANSPARENT PEER REVIEW FILE SOURCE DATA SOURCE DATA FILE_SUPPLEMENTARY FIG. SOURCE DATA

FILE_FIGURE.ZIP RIGHTS AND PERMISSIONS OPEN ACCESS This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation,

distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and

indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to

the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will

need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Reprints and permissions ABOUT THIS ARTICLE

CITE THIS ARTICLE Park, YK., Peng, H., Hapeta, P. _et al._ Engineered cross-feeding creates inter- and intra-species synthetic yeast communities with enhanced bioproduction. _Nat Commun_ 15,

8924 (2024). https://doi.org/10.1038/s41467-024-53117-4 Download citation * Received: 01 April 2024 * Accepted: 02 October 2024 * Published: 16 October 2024 * DOI:

https://doi.org/10.1038/s41467-024-53117-4 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not

currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative