Full factorial construction of synthetic microbial communities
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eLife Assessment
This manuscript introduces a new low-cost and accessible method for assembling combinatorially complete microbial consortia using basic laboratory equipment, which is a valuable contribution to the field of microbial ecology and biotechnology. The evidence presented is convincing, demonstrating the method's effectiveness through empirical testing on both synthetic colorants and Pseudomonas aeruginosa strains.
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Abstract
Constructing combinatorially complete species assemblages is often necessary to dissect the complexity of microbial interactions and to find optimal microbial consortia. At the moment, this is accomplished through either painstaking, labor intensive liquid handling procedures, or through the use of state-of-the-art microfluidic devices. Here we present a simple, rapid, low-cost, and highly accessible liquid handling methodology for assembling all possible combinations of a library of microbial strains, which can be implemented with basic laboratory equipment. To demonstrate the usefulness of this methodology, we construct a combinatorially complete set of consortia from a library of eight Pseudomonas aeruginosa strains, and empirically measure the community-function landscape of biomass productivity, identify the highest yield community, and dissect the interactions that lead to its optimal function. This easy to implement, inexpensive methodology will make the assembly of combinatorially complete microbial consortia easily accessible for all laboratories.
Article activity feed
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eLife Assessment
This manuscript introduces a new low-cost and accessible method for assembling combinatorially complete microbial consortia using basic laboratory equipment, which is a valuable contribution to the field of microbial ecology and biotechnology. The evidence presented is convincing, demonstrating the method's effectiveness through empirical testing on both synthetic colorants and Pseudomonas aeruginosa strains.
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Reviewer #1 (Public review):
Summary:
This work develops a simple, rapid, low-cost methodology for assembling combinatorially complete microbial consortia using basic laboratory equipment. The motivation behind this work is to make the study of microbial community interactions more accessible to laboratories that lack specialized equipment such as robotic liquid handlers or microfluidic devices. The method was tested on a library of Pseudomonas aeruginosa strains to demonstrate its practicality and effectiveness. It provided a means to explore the complex functional interactions within microbial communities and identify optimal consortia for specific functions, such as biomass production.
Strengths:
The primary strength of this manuscript lies in its accessibility and practicality. The method proposed by the authors allows any …
Reviewer #1 (Public review):
Summary:
This work develops a simple, rapid, low-cost methodology for assembling combinatorially complete microbial consortia using basic laboratory equipment. The motivation behind this work is to make the study of microbial community interactions more accessible to laboratories that lack specialized equipment such as robotic liquid handlers or microfluidic devices. The method was tested on a library of Pseudomonas aeruginosa strains to demonstrate its practicality and effectiveness. It provided a means to explore the complex functional interactions within microbial communities and identify optimal consortia for specific functions, such as biomass production.
Strengths:
The primary strength of this manuscript lies in its accessibility and practicality. The method proposed by the authors allows any laboratory with standard equipment, such as multichannel pipettes and 96-well plates, to readily construct all possible combinations of microbial consortia from a given set of species. This greatly enhances access to full factorial designs, which were previously limited to labs with advanced technology.
Another strength of the manuscript is the measurement and analysis of the biomass of all possible combinations of 8 strains of P. aeruginosa. This analysis provides a concrete example of how the authors' new methodology can be used to identify the best-performing communities and map pairwise and higher-order functional interactions.
Notably, the authors do exceptionally well in providing a thorough description of the methodology, including detailed protocols and an R script for customizing the method to different experimental needs. This enhances the reproducibility and adaptability of the methodology, making it a valuable resource for researchers wishing to adopt this methodology.
Weaknesses:
While the methodology is robust and well-presented, there are some limitations that should be acknowledged more thoroughly. First, the method's scalability is an important factor. The authors indicate that it should be effective for up to 10-12 species, but there is no discussion of what sets this scale: time, amount of labor, consumables, the likelihood of error, sample volume, etc. Second, this methodology is tailored to construct communities where the abundance of each strain is identical in each combination. Therefore, combinations with a different number of strains also differ in the total initial amount of microbial cells. Second, variations in the initial proportions of the same set of strains cannot be readily explored. Third, the manuscript only discusses how to construct the combinations, and not how to assay them afterward (e.g. for community function, interspecific interactions, etc'). While details on how to achieve these goals are clearly outside the scope of this work, the use of biomass as an example function may obfuscate this caveat, which should be stated more explicitly.
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Reviewer #2 (Public review):
Summary:
A simple and effective method for combinatorial assembly of microbes in synthetic communities of <12 species.
Strengths:
Overall this manuscript is a useful contribution. The efficiency of the method and clarity of the presentation is a strength. It is well-written and easy to follow. The figures are great, the pedagogical narrative is crisp. I can imagine the method being used in lots of other contexts too.
Weaknesses:
The authors could better clarify what HOIs mean. They could address challenges with assaying community function. However, neither of these "weaknesses" affects the primary goal of the paper which is methodological.
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Reviewer #3 (Public review):
The authors developed a useful methodology for generating all combinations of multiple reagents using standard lab equipment. This methodology has clear uses for studying microbial ecology as they demonstrated. The methodology will likely be useful for other types of experiments that require exhaustive testing of all possible combinations of a given set of reagents (e.g., drug-drug antagonism and synergy).
The authors provided a useful R script that generates a detailed experimental protocol for building the desired combination from any number of reagents. The produced document is useful and has clear instructions. The output of the computer script will be strengthened if graphical output is also provided (similar to the one provided in Figure 1C).
The authors show that the error rate of the method doesn't …
Reviewer #3 (Public review):
The authors developed a useful methodology for generating all combinations of multiple reagents using standard lab equipment. This methodology has clear uses for studying microbial ecology as they demonstrated. The methodology will likely be useful for other types of experiments that require exhaustive testing of all possible combinations of a given set of reagents (e.g., drug-drug antagonism and synergy).
The authors provided a useful R script that generates a detailed experimental protocol for building the desired combination from any number of reagents. The produced document is useful and has clear instructions. The output of the computer script will be strengthened if graphical output is also provided (similar to the one provided in Figure 1C).
The authors show that the error rate of the method doesn't go up with the number of combinations using dyes (Figure 2).
The authors demonstrate the value of their methodology for studying interactions within microbial consortia by assembling all possible combinations of eight strains of Pseudomonas aeruginosa. The value of their methodology for this application is well-founded. However, it is also unclear why specific experimental choices were made for this application. It is unclear why authors continue to show the absorbance measurements of strain assemblies over the entire wavelength spectrum and not just for ABS 600 nm (Figures 3 and 4). It is also unclear why the authors provided information on the "sum of the three spectra" as this reference line is meaningless and not a reasonable null model for estimating how well specific strain combinations will grow together.
Figure 5 illustrates the various analysis types that can be performed on the data collected from growing combinations of eight Pseudomonas aeruginosa strains. It is a very informative figure since it provides a "roadmap" on the various ways in which the dataset produced can be explored. The information in Figures 5 and S6 will likely be very useful for a wide audience.
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We have introduced a rapid, simple, and inexpensive protocol for assembling all possible combinations of a given set of species using basic laboratory equipment such as a multichannel pipette and 96-well plates.
Do the authors believe this would still be feasible for communities that need to be grown on solid medium?
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We therefore anticipate that our methodology will find extensive applications and utility across diverse fields such as microbiology, ecology, evolution, and biotechnology.
Thank you for this great work. This seems like a game-changer for assembling microbial communities, and I hope many groups will take advantage of this. The versatility of the approach is really interesting, as the proof of concept with food coloring has illustrated it.
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highest biomass contains only three strains
By 'highest biomass', do the authors mean highest cell density? I wonder if there could be interactions that lead to morphological changes in some strains that could then affect the absorbance reading. In other words, the OD is greater but not because there are more cells but because some cells have weird morphologies.
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Samples were incubated still at 37 °C for 40 h, after which the absorbance spectrum of each sample was quantified in the same plate reader we used before.
I wonder if any biofilm formed at the top or bottom of the wells? Have the cultures been homogenized before absorbance was measured?
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capac-ity
typo
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Pseudomonas aeruginosa strains obtained from a previous experiment
Can the authors give a little more context on the origin of the strains? And if/why a community with these strains could be ecologically relevant?
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Binary numbers are the natural way to denote combina-stance, tions in mathematics, and indeed the correspondence between the two sets is often
used in combinatorics. For inof m species. The same number counts how many binary strings of length m contain n ones (equivalently, n zeros).There seems to be a couple of typos in this section
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thou-sands
This might just be a typo
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