Interaction effects among species in synthetic microbial communities

Interaction effects among species in synthetic microbial communities | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 14 April 2025 V1 Latest version Share on Interaction effects among species in synthetic microbial communities Authors : Jingjing Wang 0000-0001-8147-8441 [email protected] , Liang Tian , Wei Zhao , Song Xu , Xiaoxia Zhang , and Zhiyong Huang Authors Info & Affiliations https://doi.org/10.22541/au.174464507.79042409/v1 169 views 131 downloads Contents Abstract Introduction Classification of interaction effects in simple SMCs Classification of interaction effects in complex SMCs Application of interaction effects Interaction effect is different from interaction Interaction effects in SMCs Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Synthetic microbial community (SMC) hold immense potential for application across various vital fields. However, the rational construction of SMCs still faces considerable challenges. The function of SMC is contingent upon the function of individual species within it and their interactions. But the relationship between the function of the SMC and the functions of the individual species it contains, which we call the ‘interaction effect’, is still unclear. In this study, we categorize the interaction effects of species in SMCs into seven types by comparing the functions of SMCs and their constituent species. These types include linearly related additive effect (AE), non-linearly related synergistic effect (SE), stimulatory effect (STE), strong effect (STRE), interference effect (IE), weak effect (WE), and inhibitory effect (INE). This classification of interaction effect can be used to assess the efficiency of SMC. It is not easy to quickly construct efficient SMC with synergistic effects (SE), although numerous reports document synergistic effects (SE) in SMCs. Moreover, this classification of interaction effect may also apply in other fields such as ecological communities, drug combinations, composite materials. Introduction Microorganisms are widely distributed as communities in the global environment and play an important role in global biogeochemical cycles and in human, animal and plant health. Based on the understanding of microbial communities, humans have constructed a variety of microbial communities with specific functions to maintain life and health, increase crop yields, control environmental pollution, and produce high-value products 1-3 . Currently, ’top-down’ and ’bottom-up’ are the two main strategies for constructing functional microbial communities 4 . The ’bottom-up’ strategy refers to the synthesis of more than two microorganisms into a community to perform a specific function. Therefore, the microbial community constructed using the ’bottom-up’ strategy is called a ’synthetic microbial community (SMC)’ or ’synthetic microbiome’. However, the rational construction of SMCs still faces considerable challenges. When two or more microorganisms are synthesized into an SMC, the function of the SMC rarely matches the cumulative function of the individual members 5 . The function of an SMC depends on the function of the individual members within it and their interactions. The functions of the individual members can be easily determined using biochemical methods, but the function of the SMC is difficult to predict from the functions of the individual members due to the interactions between the members. Therefore, understanding the effects of member interactions on SMC function is crucial for the rational design and manipulation of SMCs. Interactions within communities were categorized as cooperation or mutualism (+/+), commensalism (+/0), neutralism (0/0), amensalism (-/0), exploitation or parasitism (+/-) and competition (-/-), based on potential win, loss and neutral outcomes for the interaction partners 6, 7 . This classification scheme was then broadly divided into antagonistic interactions, synergistic interactions and neutral interactions 8, 9 . Antagonistic interactions include all cases where species harm or kill other species in their vicinity in order to gain a competitive advantage. In contrast, synergistic interactions involve species benefiting from the intentional or unwitting behavior of another individual in their local environment. In neutral interactions, species have no effect on each other 8, 9 . The classification of interactions significantly advances the field of community ecology 10-14 . However, this classification of interactions focuses mainly on the ecological relationship between a pair of organisms living together in a community, and it is difficult to make a link to SMC functions. In this study, we wanted to investigate species interactions in SMCs from a functional perspective. Therefore, we further investigate the relationship between the function of the SMC and the functions of the individual species it contains, which we call the ‘interaction effect’. We categorize the ‘interaction effects’ of species in SMCs by comparing the functions of SMCs and their constituent species. This can be used not only to assess the quality of SMCs and promote the construction, transformation and application of efficient SMCs, but also to improve the understanding of species interactions in communities from a functional perspective. Methods and Results Classification of interaction effects in simple SMCs Assuming that a specific function (e.g. biomass, productivity, promotion, etc) of species a is 1 ( f a = 1) and species b is 2 ( f b = 2), when these two species are combined into an SMC, the function of the SMC ( F ab ) may • be higher than the sum of the functions of the two species (1 + 2 > 3). This is defined as synergistic effect. • be equal to the sum of the functions of the two species (1 + 2 = 3). This is defined as additive effect. • be higher than that of the high-functioning species and lower than the sum of the functions of the two species (2 < 1 + 2 < 3). This is defined as stimulatory effect. • be equal to that of the high-functioning species (1 + 2 = 2). This is defined as strong effect. • be higher than that of the low-functioning species and lower than that of the high-functioning species (1 < 1+2 < 2). This is defined as interference effect. • be equal to that of the low-functioning species (1 + 2 = 1). This is defined as weak effect. • be lower than that of the low-functioning species (1 + 2 < 1). This is defined as inhibitory effect (Fig. 1). Figure 1 Interaction effects of species in the synthetic microbial community under the condition that the function of species A and species B were both greater than 0. Assuming that a specific function of species a is -1 ( f a = -1) and species b is 2 ( f b = 2), when these two species are combined into an SMC, the function of the SMC ( F ab ) may • be higher than that of the high-functioning species (-1 + 2 > 2). This is defined as synergistic effect. • be equal to that of the high-functioning species (-1 + 2 = 2). This is defined as strong effect. • be higher than that of the low-functioning species and lower than that of the high-functioning species (-1 < -1 + 2 < 2). This is defined as interference effect. • be equal to the sum of the functions of the two species ( -1 + 2 = 1). This is defined as additive effect. • be equal to that of the low-functioning species (-1 + 2 = -1). This is defined as weak effect. • be lower than that of the low-functioning species (-1 + 2 < -1). This is defined as inhibitory effect. Assuming that a specific function of species a is -1 ( f a = -1) and species b is -2 ( f b = -2), when these two species are combined into a SMC, the function of the SMC may • be higher than that of the high-functioning species (-1 + -2 > -1). This is defined as synergistic effect. • be equal to that of the high-functioning species (-1 + -2 = -1). This is defined as strong effect. • be higher than that of the low-functioning species and lower than that of the high-functioning species (-2 < -1 + -2 < -1). This is defined as interference effect. • be equal to that of the low-functioning species (-1 + -2 = -2). This is defined as weak effect. • be lower than that of the low-functioning species (-1 + -2 < -2). This is defined as inhibitory effect. • be equal to the sum of the functions of the two species (-1 + -2 = -3). This is defined as additive effect. Assuming that a specific function of species a is 0 ( f a = 0) and species b is 2 ( f b = 2), when these two species are combined into a SMC, the function of the SMC ( F ab ) may • be higher than that of the high-functioning species (0 + 2 > 2). This is defined as synergistic effect. • be equal to that of the high-functioning species (0 + 2 = 2). This is defined as strong effect. • be higher than that of the low-functioning species and lower than that of the high-functioning species (0 < 0 + 2 < 2). This is defined as interference effect. • be equal to the sum of the functions of the two species (0 + 2 = 2). This is defined as additive effect. • be equal to that of the low-functioning species (0 + 2 = 0). This is defined as weak effect. • be lower than that of the low-functioning species (0 + 2 < 0). This is defined as inhibitory effect. Assuming that a specific function of species a is 0 ( f a = 0) and species b is 0 ( f b = 0), when these two species are combined into a SMC, the function of the SMC ( F ab ) may • be higher than 0 (0 + 0 > 0). This is defined as synergistic effect. • be equal to 0 (0 + 0 = 0). This is defined as additive effect. • be lower than 0 (0 + 0 < 0). This is defined as inhibitory effect. In summary, we categorize the interaction effects of species in SMCs into seven types by comparing the functions of SMCs and their constituent species. These types include linearly additive effect (AE), non-linearly synergistic effect (SE), stimulatory effect (STE), strong effect (STRE), interference effect (IE), weak effect (WE), and inhibitory effect (INE) (Table 1). Table 1 Interaction effects in synthetic microbial communities (SMCs) consisting of 2 species Linear Additive effect (AE) f a = 1 f b = 2 F ab = 3 f a = -1 f b = 2 F ab = 1 f a = -1 f b = -2 F ab = -3 f a = 0 f b = 2 F ab = 2 f a = 0 f b = 0 F ab = 0 Non-linear Synergistic effect (SE) f a =1 f b = 2 F ab > 3 f a = -1 f b = 2 F ab > 2 f a = -1 f b = -2 F ab > -1 f a = 0 f b = 2 F ab > 2 f a = 0 f b = 0 F ab > 0 Stimulatory effect (STE) f a = 1 f b = 2 2 < F ab < 3 Strong effect (STE) f a = 1 f b = 2 F ab = 2 f a = -1 f b = 2 F ab = 2 f a = -1 f b = -2 F ab = -1 f a = 0 f b = 2 F ab = 2 Interference effect (IE) f a = 1 f b = 2 1 < F ab < 2 f a = -1 f b = 2 -1 < F ab < 2 f a = -1 f b = -2 -2 < F ab < -1 f a = 0 f b = 2 0 < F ab < 2 Week effect (WE) f a = 1 f b = 2 F ab = 1 f a = -1 f b = 2 F ab = -1 f a = -1 f b = -2 F ab = -2 f a = 0 f b = 2 F ab = 0 Inhibitory effect (INE) f a = 1 f b = 2 F ab < 1 f a = -1 f b = 2 F ab < -1 f a = -1 f b = -2 F ab < -2 f a = 0 f b = 2 F ab < 0 f a = 0 f b = 0 F ab < 0 F , a specific function of a synthetic microbial community; f , a specific function of a species Classification of interaction effects in complex SMCs Apply the interaction effects to multi-species SMCs (Table 2). Defining f ( i ) as a specific function of a species and F n as a specific function of an SMC composed of n species ( n ≥ 2), • When the F n is equal to the sum of the f ( i ) , this is an additive effect ( F n = ∑ f (i= 1, n) ). • When the sum of the f ( i ) is higher than the high-functioning species, if F n is higher than the sum of the f ( i ) , this is a synergistic effect ( F n > ∑ f (i= 1, n) ). • When the sum of the f ( i ) is higher than the high-functioning species, if F n is higher than the high-functioning species but lower than the sum of the f ( i ) , this is a stimulatory effect ( f high < F n ∑ f (i= 1, n) ). • When f ( i ) is not all 0 ( f ( i ) ≠ 0), if the F n is equal to the function of the high-functioning species, this is a stronger effect ( F n = f high ). • When f ( i ) is not all 0 ( f ( i ) ≠ 0), if the F n is higher than the function of the low-functioning species but lower than that of the high-functioning species, this is an interference effect ( f low < F n < f high ). • When f ( i ) is not all 0 ( f ( i ) ≠ 0), if the F n is equal to the function of the low-functioning species, this is a weak effect ( F n = F low ). • If the F n is lower than the function of the low-functioning species, this is an inhibitory effect ( F n < f low ). Application of interaction effects The interaction effect can evaluate the efficiency of SMC from a functional perspective. Synergistic effect (SE) indicates that this SMC is very efficient. For an SMC composed of n ( n ≥2) species, if there is a synergistic effect among these species, it means that the SMC is efficient, and the function of the SMC is already very strong and there is almost no room for improvement, or the room for improvement is very small; if there is a stimulating effect, or a strong effect, or an interference effect, or a weak effect, or an inhibitory effect among these species in turn, it means that the SMC is not efficient enough, and there is room for improvement of the SMC function, and the room for improvement increases successively. The additive effect needs to be analyzed according to the specific situation, because it has different meanings in different situations. For the SMC composed of n species with functions greater than 0, if there is an additive effect between these species, then the function of SMC is second only to the function of SMC composed of synergistic effect species, but higher than the function of SMC composed of other effect species, which shows that there is some room for improvement and optimization of the function of SMC. For an SMC composed of n species with functions less than 0, if these species have additive effects, then the function of SMC is inferior to the function of SMC composed of other effect species, which indicates that there is a lot of room for improvement and optimization of SMC function. For an SMC composed of n species and some of which have functions less than 0, if these species have additive effects, then the function of SMC is inferior to the function of SMC composed of synergistic effect species, and may be higher or lower than the function of SMC composed of other effect species, which indicates that there is room for improvement and optimization of SMC function. For SMCs composed of species with additive effect, stimulatory effect, strong effect, interference effect, weak effect, and inhibitory effect, the functions of SMCs can be enhanced by replacing or engineering species to improve the interaction effects between species. In addition, it is essential to adhere to a specific initial species ratio, culture time and culture condition of the SMCs, as the interaction effect may be different under different factors. Table 2 Interaction effects in synthetic microbial communities Linear Additive effect (AE) \(F_{n}=\sum_{1}^{n}f_{(i)}\) i = 1, 2,……, n ; n ≥ 2 Non-linear Synergistic effect (SE) \(F_{n}>\sum_{1}^{n}f_{(i)}\) i = 1, 2,……, n ; n ≥ 2; f ( i =1, n ) ≥ 0 \(F_{n}>\max{[f_{\text{high}},\ \sum_{1}^{n}f_{(i)}]}\) i = 1, 2,……, n ; n ≥ 2; f ( i ) ＜ 0 Stimulatory effect (STE) \({f_{\text{high}}<F}_{n} 0 Strong effect (STRE) \({F_{n}=f}_{\text{high}}\) n ≥ 2; f ( i ) ≠ 0 Interference effect (IE) \(f_{\text{low}}<F_{n}<f_{\text{high}}\) n ≥ 2; f ( i ) ≠ 0 Weak effect (WE) \({F_{n}=f}_{\text{low}}\) n ≥ 2; f ( i ) ≠ 0 Inhibitory effect (INE) \({F_{n}<f}_{\text{low}}\) n ≥ 2 F n , a specific function of a synthetic microbial community; f ( i ) , a specific function of a species; f high , the function of the high-functioning species; f low , the function of the low-functioning species. Discussion Interaction effect is different from interaction Interaction effects and interactions are very different. Interactions within communities are categorized based on potential win, loss and neutral outcomes for the interaction partners, focusing on individual species. Interaction effects are classified based on the comparison between a function of an SMC and a function of a single species, focusing on SMC. In the definition of interaction, the cell number of co-cultured species is never less than the number of mono-cultured species 7 . However, in practice, the number of co-cultured species may be less than or equal to the number of mono-cultured species, this will be inhibitory effect (INE), interference effect (IE), strong effect (STRE) and weak effect (WE). For example, the number of co-cultured Enterocloster clostridioformis YL32 and Bacteroides caecimuris I48 was significantly lower than the number of both mono-cultured, which was an inhibitory effect (INE) 15 . The number of co-cultured Acutalibacter muris KB18 and Bacteroides caecimuris I48 was higher than the number of mono-cultured Acutalibacter muris KB18, but lower than the number of mono-cultured Bacteroides caecimuris I48, which was an interference effect (IE) 15 . But there are some relationships between the seven interaction effects and the six interactions (Fig. 2). Assuming that a specific function (e.g. biomass, productivity, promotion, etc) of species a is 1 ( f a = 1) and species b is 2 ( f b = 2). • Mutualism (+/+) means that both species benefit ( f a ＞ 1, f b ＞ 2) when co-cultured, which will lead to a synergistic effect (SE) ( F ab ＞ 3). • Commensalism (+/0) means that when these two species are co-cultured, one benefits and the other is not affected ([ f a ＞ 1, f b = 2] or [ f a = 1, f b ＞ 2]). This will also lead to a synergistic effect (SE) ( F ab ＞ 3). • Neutral (0/0) means that when two species are co-cultured, neither is affected ( f a = 1, f b = 2), which will lead to an additive effect (AE) ( F ab = 3). • Amensalism (-/0) is when two species are co-cultured, one is harmed and the other is unaffected ([ f a ＜ 1, f b = 2] or [ f a = 1, f b ＜ 2]). This may lead to stimulatory effect (STE), strong effect (STRE), interference effect (IE), weak effects (WE) or inhibitory effect (INE) ( F ab ＜ 3). • Parasitism (+/-) is when two species are co-cultured, one benefits and the other is victimized ([ f a ＜ 1, f b ＞ 2] or [ f a ＞ 1, f b ＜ 2]). This may lead to synergistic effect (SE), additive effect (AE), stimulatory effect (STE), strong effect (STRE), interference effect (IE), weak effect (WE) or inhibitory effect (INE) ( F ab = ∀). • Competition (-/-) is when two species are co-cultured and both suffer ( f a ＜ 1, f b ＜ 2). This may lead to stimulatory effect (STE), strong effect (STRE), interference effect (IE), weak effect (WE) or inhibitory effect (INE) ( F ab ＜ 3). In summary, species in mutualism, commensalism and partial parasitism may form a synergistic effect (SE) in an SMC, while species in neutralism and partial parasitism may form an additive effect (AE) in an SMC, and species in other interactions may form a stimulatory effect (STE), strong effect (STRE), interference effect (IE), weak effect (WE) or inhibitory effect (INE) in an SMC. Figure 2 The relationship between the interaction effects and the interactions. Interaction effects in SMCs Synergistic effects (SE) represent the primary objective of synthetic microbial communities (SMCs). Numerous studies have documented these effects in SMCs (Table 3). For example, Pseudomonas stutzeri XL272 exhibited significant synergy with Bacillus velezensis SQR9 in biofilm formation, resulting in enhanced biomass production compared to single-species biofilm 16 . An artificial consortium comprising Clostridium phytofermentans and Escherichia coli displayed emergent properties surpassing those of monocultures, including a >200% increase in cellobiose catabolism, a increase in ethanol production and a >120% increase in biomass productivity 17 . A four-species bacterial consortium SPMX ( Stenotrophomonas rhizophila , Xanthomonas retroflexus , Microbacterium oxydans and Paenibacillus amylolyticus ) remarkably enhanced drought tolerance in Arabidopsis , contrasting with the absence of a drought-tolerant effect in individual strains 18 . Additionally, SMCs have been effectively utilized for the discovery of new secondary metabolites 19, 20 . For example, co-cultivation of Alternaria brassicicola and Penicillium granulatum yielded three new ergosterol derivatives (brassisterol A–C) and two new epimeric bicycle-lactones (brassictones A and B) 21 . Furthermore, the coculture fermentation of Penicillium fuscum and P. camembertii / clavigerum resulted in the isolation of new macrolides (berkeleylactones A-H) 22 . Moreover, extensive research has employed genetic engineering techniques to develop co-cultivation systems for biochemical production and organic compound degradation 3, 23, 24 . For example, three Escherichia coli strain were engineered to achieve the highest reported titer of 60.8 mg/L genistein from a glucose and glycerol mixture 25 . Stimulatory effects (STE) are prevalent in SMCs and have been extensively documented. For instance, co-inoculations with Bacillus velezensis FH-1 and Brevundimonas diminuta NYM-3 significantly increased the fresh weight, dry weight, and height of rice seedlings (both shoot and root) compared to single strain inoculations 26 . Similarly, co-culture of Escherichia coli and Pseudomonas aeruginosa resulted in an enhanced power density of 190.44 mW m -2 , whereas E. coli and P. aeruginosa as pure cultures generated lesser power densities of 139.24 and 158.76 mW m -2 respectively 27 . Furthermore, the hydrolysates of sugarcane bagasse were efficiently converted to H 2 by co-culturing Enterobacter aerogenes and Clostridium acetobutylicum , achieving a H 2 production rate of 3.9 mL h -1 . This represented 1.22 and 2.17-fold enhancement in hydrogen production yield over that obtained from pure cultures of Enterobacter aerogenes and Clostridium acetobutylicum , respectively 28 . There are also some reports regarding interference effects (IE). For example, the Vitamin B12 level reached 357 ng/g dry weight in Propionibacterium freudenreichii monoculture. However, in co-fermentation with Propionibacterium freudenreichii and Lactobacillus brevis , a slight lower amount of vitamin B12 (255 ng/g dw) was produced 29 . The co-fermentation of rice straw for ethanol production by Saccharomyces cerevisiae and Candida tropicalis yielded lower results compared to Candida tropicalis mono-culture 30 . The combination Enterococcus RP3 and Enterococcus RP7 for hydrogen production from wheat-straw xylan (WSX) yielded poorer results (14.8 mL/g WSX added ) compared to the Enterococcus RP7 single-species cultures 31 . There are also some reports about the inhibitory effects (INE). The oil removal rate in the co-inoculation of Paenibacillus sp. and Microbacterium sp. was lower compared to that of both single bacteria 32 . The production of acetic acid in the co-culture with Clostridium fermenticellae JN500901 and Novisyntrophococcus fermenticellae JN500902 was lower compared to mono culture 33 . Dual inoculations of Trichoderma harzianum and Brevibacterium halotolerans led to a decrease in carotenoid content in plants compared to monoculture 34 . There are few reports on the additive effect (AE), strong effects (STRE) and weak effect (WE) in SMCs. An example of strong effects (STRE) was observed in the primary root elongation of seedlings inoculated jointly with Arthrobacter CL28 and Variovorax CL14, which was similar to that of Variovorax CL14 inoculation 35 . An example of weak effect (WE) was observed in rice yield when inoculated jointly with Pantoea dispersa and Staphylococcus sp., which was similar to that of Staphylococcus sp. alone. Table 3 Examples of interaction effects in synthetic microbial communities Synergistic effect (SE) Arabidopsis survival rate in drought compare to control (%) ~0 ( Stenotrophomonas rhizophila ) ~0 ( Paenibacillus amylolyticus ) ~0 ( Microbacterium oxydans ) ~0 ( Xanthomonas retroflexus ) ~30 18 Fragaria vesca shoot weight (Fold changes compare to control) ~0.5 ( Rhizophagus irregularis ) ~3 ( Bacillus amyloliquefaciens ) ~7 36 Biofilm biomass (mg) ~210 ( Pseudomonas stutzeri XL272) ~390 ( Bacillus velezensis SQR9) ~690 16 Ethanol (g/L) 63.17 ( Pichia kudriazevii YS201) 0 ( Bacillus subtilis BS38) 86.60 37 Ethanol (mM) 2.41 ( Clostridium phytofermentans) 0.44 ( Escherichia coli ) 26.71 17 H 2 (μmol) ~18 ( Chlamydomonas reinhardtii cc849) ~0 ( Pseudomonas ) ~70 38 Relative quantity of the polyketide gene orsA ~1 ( Aspergillus nidulans ) ~1 ( Streptomyces hygroscopicus ) ~70000 39 Keyicin (Intensity) ~0 ( Micromonospora sp.) ~0 ( Rhodococus sp.) ~2×10 5 40 Berkeleylactones 0 ( Penicillium fuscum ) 0 ( Penicillium camembertii ) >0 22 Brassisterol A (mg) 0 ( Alternaria brassicicola ) 0 ( Penicillium granulatum ) 4.2 21 Bis (2-hydroxyethyl) terephthalate degradation (%) 32% ( Rhodococcus biphenylivorans GA1) 0% ( Burkholderia sp. EG1) 100% 41 Genistein (mg/L) 0 ( Escherichia coli LCA2G) 0 ( Escherichia coli LNR30R) 0 ( Escherichia coli LGN43) 60.8 25 Oxygenated taxanes (mg/L) 0 ( Escherichia coli ) 0 ( Saccharomyces cerevisiae ) 33 42 Additive effect (AE) Stimulatory effect (STE) Cucumber weight (g) ~2.0 ( Pseudomonas stutzeri XL272) ~1.9 ( Bacillus velezensis SQR9) ~2.5 16 Rice shoots dry weight (g) ~0.25 ( Bacillus velezensis FH-1) ~0.26 ( Brevundimonas diminuta NYM-3) ~0.31 26 Tomato weight (mg) ~210 ( Massilia sp. SA087) ~260 ( Enterobacter sp. SA187) ~220 ( Ensifer sp. SA403) ~270 ( Bacillus sp. SA436) ~290 ( Streptomyces sp. SA444) ~330 43 Power generation (mW m -2 ) 139.24 ( Escherichia coli ) 158.76 ( Pseudomonas aeruginosa ) 190.44 27 Power generation (mW m -3 ) 85.41 ( Paenibacillus sp.) 67.78 ( Deinococcus sp.) 102.93 32 Ammonium (g/L) 0.23 ( Penicillium camembertii ) 0.90 ( Geotrichum candidum ) 1.07 44 H 2 production rates (mL h -1 ) 3.2 ( Enterobacter aerogenes ) 1.8 ( Clostridium acetobutylicum ) 3.9 28 Strong effect (STRE) Primary root elongation (cm) ~1.8 ( Arthrobacter CL28) ~6.4 ( Variovorax CL14) ~6.4 35 Interference effect (IE) Vitamin B12 (ng/g) 357 ( Propionibacterium freudenreichii ) ~0 ( Lactobacillus brevis ) 255 29 Ethanol concentration (g/L) 12.17 ( Saccharomyces cerevisiae ) 13.38 ( Candida tropicalis ) 13.00 30 Hydrogen production (mL H 2 /g WSX added ) ~0.2 ( Enterococcus RP3) ~26.7 ( Enterococcus RP7) 14.8 31 Weak effect (WE) Rice yield (t/ha) 6.13 ( Pantoea dispersa ) 6.02 ( Staphylococcus sp.) 6.02 45 Inhibited effect (INE) Oil removal rate (%) 80.52 ( Microbacterium sp.) 84.01 ( Paenibacillus sp.) 65.88 32 Acetic acid (g/L) ~2.8 ( Clostridium fermenticellae JN500901) ~3.2 ( Novisyntrophococcus fermenticellae JN500902) ~2.7 33 Carotenoids (mg/g fresh weight) ~0.03 ( Trichoderma harzianum ) ~0.03 ( Brevibacterium halotolerans ) ~0.02 34 We then analyzed the interaction effects in SMCs constructed from the complete combination of n ( n ≥2) species (C ( n , n )). For example, Guo, Zhan, Chen, Zhao and Guo 32 constructed four SMCs using a complete combination of Paenibacillus sp. (P), Microbacterium sp. (M) and Deinococcus sp. (D) for electricity production. The interaction effects of species in three SMCs (PM, MD and PMD) exhibited inhibitory effect (INE). The interaction effect of species in the fourth SMC (PD) demonstrates a stimulatory effect (STE) (Fig.3). Figure 3 The interaction effects in electricity producing synthetic microbial communities constructed from the complete combination of 3 species. (A), the power produced by single species and synthetic microbial communities consisting of 2 species; (B), the power produced by single species and synthetic microbial communities consisting 3 species; (C), the ratio of interaction effects in all synthetic microbial communities constructed from complete combination of 3 species; P, Paenibacillus sp.; M, Microbacterium sp.; D, Deinococcus sp.; fa , the function of the first species; fb , the function of the second species; Fab , the function of the synthetic microbial communities composed by the first and second species; Fabc , the function of the synthetic microbial communities composed by the first, second and third species; INE, inhibitory effect; STE, stimulatory effect; The data was from figure 2C of 32 . Rawat, Sharma, Shankhdhar and Shankhdhar 45 constructed four SMCs using a complete combination of Bacillus licheniformis (B), Pantoea dispersa (P) and Staphylococcus sp. (S) to promote rice yield under various conditions. The results demonstrated that the interaction effects of species in these four SMCs varied under different phosphate (P) application rates and times (Fig.4 and Fig.5). The stimulatory effect (STE) and inhibitory effect (INE) of species in the SMCs were present in all cases, but their proportion varied with P application rates and time. Inhibitory effect (IE) only appeared at 0% and 50% P treatments, while weak effect (WE) only appeared at 100% P treatment. The proportion of Inhibitory effect (IE) was affected by time. Figure 4 The interaction effects in rice yield promoting synthetic microbial communities under various phosphate application rates (0%, 50%, 75%, and 100% of the recommended dose 45 kg P 2 O 5 ha -1 ) in 2018. (A, D, G, J), the interaction effects in SMCs consisting of 2 species; (B, E, H, K), the interaction effects in SMCs consisting of 2 species; (C, F, I, L), the ratio of interaction effects in all SMCs constructed from complete combination of 3 species; B, Bacillus licheniformis ; P, Pantoea dispersa ; S, Staphylococcus sp.; fa , the function of the first species; fb , the function of the second species; Fab , the function of the synthetic microbial communities composed by the first and second species; Fabc , the function of the synthetic microbial communities composed by the first, second and third species; STE, stimulatory effect; IE, interference effect; WE, weak effects; INE, inhibitory effect; The data was from the Table IV of 45 . Figure 5 The interaction effects in rice yield promoting synthetic microbial communities under various phosphate application rates (0%, 50%, 75%, and 100% of the recommended dose 45 kg P 2 O 5 ha -1 ) in 2019. (A, D, G, J), the interaction effects in SMCs consisting of 2 species; (B, E, H, K), the interaction effects in SMCs consisting of 2 species; (C, F, I, L), the ratio of interaction effects in all SMCs constructed from complete combination of 3 species; B, Bacillus licheniformis ; P, Pantoea dispersa ; S, Staphylococcus sp.; fa , the function of the first species; fb , the function of the second species; Fab , the function of the synthetic microbial communities composed by the first and second species; Fabc , the function of the synthetic microbial communities composed by the first, second and third species; STE, stimulatory effect; IE, interference effect; WE, weak effects; INE, inhibitory effect; The data was from the Table IV of 45 . In another study, 14 bacterial communities were synthesized by combining 9 bacterial communities in pairs to promote Arabidopsis thaliana shoot phosphorus (Pi) content. Although the interaction effects varied under different nutrient conditions, the frequency of interference effects (IE) and inhibitory effects (INE) was higher than that of other effects (Fig.6). Under high phosphorus germination and high phosphorus cultivation conditions, the interference effect (IE) accounted for 57%, the inhibitory effect (INE) accounted for 29%, and the stimulatory effect (STE) accounted for 14%. In the environment of low phosphorus germination and high phosphorus cultivation, the interference effect (IE) accounted for 43%, the inhibitory effect (INE) accounted for 36%, the weak effect (WE) accounted for 14%, and the stimulatory effect (STE) accounted for 7%. In the environment of high phosphorus germination and low phosphorus cultivation, the interference effect (IE) accounted for 57% and the inhibitory effect (INE) accounted for 43%. In the environment of low phosphorus germination and low phosphorus cultivation, the interference effect (IE) accounted for 64% and the inhibitory effect (INE) accounted for 36%. Figure 6 The interaction effects in synthetic microbial communities that modified phosphorus (Pi) accumulation in Arabidopsis thaliana shoot. +Pi, germinated with 1 mM Pi; -Pi, germinated with 5 μM Pi; 100 μM, growth with 100 μM Pi; 30 μM, growth with 30 μM Pi; Positive (P1-P3), indifferent (I1-I3), and negative (N1-N3) Pi accumulation bacteria; fa , the effects on shoot Pi by the first strain; fb , the effects on shoot Pi by the second strain; Fab , the effects on shoot Pi by the synthetic microbial communities composed by the first and second strains; IE, interference effect; INE, inhibitory effect; WE, week effect; SE, synergistic effect. The data was from 46 . This suggests that in SMCs randomly synthesized with specified functional species, the frequency of inhibitory effects (INE), interference effects (IE) and stimulatory effects (STE) is relatively high, whereas the frequency of weak effects (WE) and synergistic effects (SE) is low, and additive effects (AE) and strong effects (STRE) are almost absent. This notion was supported by a recent review. The review indicated that cooperation (+/+) leading to a synergistic effect (SE) was rare in bacterial species 10 . This indicates that it is not easy to construct an efficient SMC with synergistic effect (SE), which is mainly due to the emergence caused by the interaction effects between species within the SMC. Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems they are part of. Emergent properties - patterns or functions that cannot be deduced linearly from the properties of the constituent parts - underlie important ecological characteristic 5 . Clearly, emergent properties are non-linear nature. All interaction effects except additive effects (AE) are emergent properties of SMC. The non-linear nature makes mathematical modelling imperative for establishing the quantitative link between species function and the SMC function 5 . In the future, we should deeply analyze the mechanism of species interaction effects (i.e., emergence) in SMC, so as to lay a theoretical foundation for the design of efficient SMC. How to rationally construct efficient SMCs with synergistic effect (SE), additive effects (AE) or stimulatory effects (STE) should be a key focus for future research. 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Keywords classification function interaction effects synergistic effect synthetic microbial community synthetic microbiome Authors Affiliations Jingjing Wang 0000-0001-8147-8441 [email protected] Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences View all articles by this author Liang Tian Tianjin Chengjian University View all articles by this author Wei Zhao View all articles by this author Song Xu View all articles by this author Xiaoxia Zhang View all articles by this author Zhiyong Huang View all articles by this author Metrics & Citations Metrics Article Usage 169 views 131 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Jingjing Wang, Liang Tian, Wei Zhao, et al. Interaction effects among species in synthetic microbial communities. Authorea . 14 April 2025. 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