Automated design of synthetic microbial communities.
Ontology highlight
ABSTRACT:
SUBMITTER: Karkaria BD
PROVIDER: S-EPMC7844305 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
Automated design of synthetic microbial communities.
Karkaria Behzad D BD Fedorec Alex J H AJH Barnes Chris P CP
Nature communications 20210128 1
Microbial species rarely exist in isolation. In naturally occurring microbial systems there is strong evidence for a positive relationship between species diversity and productivity of communities. The pervasiveness of these communities in nature highlights possible advantages for genetically engineered strains to exist in cocultures as well. Building synthetic microbial communities allows us to create distributed systems that mitigate issues often found in engineering a monoculture, especially ...[more]
Similar Datasets
Project description:Microarrays are useful tools for detecting and quantifying specific functional and phylogenetic genes in natural microbial communities. In order to track uncultivated microbial genotypes and their close relatives in an environmental context, we designed and implemented a “genome proxy” microarray that targets microbial genome fragments recovered directly from the environment. Fragments consisted of sequenced clones from large-insert genomic libraries from microbial communities in Monterey Bay, the Hawaii Ocean Time-series station ALOHA, and Antarctic coastal waters. In a prototype array, we designed probe sets to thirteen of the sequenced genome fragments and to genomic regions of the cultivated cyanobacterium Prochlorococcus MED4. Each probe set consisted of multiple 70-mers, each targeting an individual ORF, and distributed along each ~40-160kbp contiguous genomic region. The targeted organisms or clones, and close relatives, were hybridized to the array both as pure DNA mixtures and as additions of cells to a background of coastal seawater. This prototype array correctly identified the presence or absence of the target organisms and their relatives in laboratory mixes, with negligible cross-hybridization to organisms having ≤~75% genomic identity. In addition, the array correctly identified target cells added to a background of environmental DNA, with a limit of detection of ~0.1% of the community, corresponding to ~10^3 cells/ml in these samples. Signal correlated to cell concentration with an R2 of 1.0 across six orders of magnitude. In addition the array could track a related strain (at 86% genomic identity to that targeted) with a linearity of R2=0.9999 and a limit of detection of ~1% of the community. Closely related genotypes were distinguishable by differing hybridization patterns across each probe set. This array’s multiple-probe, “genome-proxy” approach and consequent ability to track both target genotypes and their close relatives is important for the array’s environmental application given the recent discoveries of considerable intra-population diversity within marine microbial communities. Keywords: target addition experiment, proof-of-concept for GPL6012
2007-10-31 | GSE9384 | GEO
Project description:Social interaction among cells is essential for multicellular complexity. But how do molecular networks within individual cells confer the ability to interact? And how do those same networks evolve from the evolutionary conflict between individual- and population-level interests? Recent studies have dissected social interaction at the molecular level by analyzing both synthetic and natural microbial populations. These studies shed new light on the role of population structure for the evolution of cooperative interactions and revealed novel molecular mechanisms that stabilize cooperation among cells. New understanding of populations is changing our view of microbial processes, such as pathogenesis and antibiotic resistance, and suggests new ways to fight infection by exploiting social interaction. The study of social interaction is also challenging established paradigms in cancer evolution and immune system dynamics. Finding similar patterns in such diverse systems suggests that the same 'social interaction motifs' may be general to many cell populations.
| S-EPMC3101950 | biostudies-other
Project description:Microarrays are useful tools for detecting and quantifying specific functional and phylogenetic genes in natural microbial communities. In order to track uncultivated microbial genotypes and their close relatives in an environmental context, we designed and implemented a âgenome proxyâ microarray that targets microbial genome fragments recovered directly from the environment. Fragments consisted of sequenced clones from large-insert genomic libraries from microbial communities in Monterey Bay, the Hawaii Ocean Time-series station ALOHA, and Antarctic coastal waters. In a prototype array, we designed probe sets to thirteen of the sequenced genome fragments and to genomic regions of the cultivated cyanobacterium Prochlorococcus MED4. Each probe set consisted of multiple 70-mers, each targeting an individual ORF, and distributed along each ~40-160kbp contiguous genomic region. The targeted organisms or clones, and close relatives, were hybridized to the array both as pure DNA mixtures and as additions of cells to a background of coastal seawater. This prototype array correctly identified the presence or absence of the target organisms and their relatives in laboratory mixes, with negligible cross-hybridization to organisms having â¤~75% genomic identity. In addition, the array correctly identified target cells added to a background of environmental DNA, with a limit of detection of ~0.1% of the community, corresponding to ~10^3 cells/ml in these samples. Signal correlated to cell concentration with an R2 of 1.0 across six orders of magnitude. In addition the array could track a related strain (at 86% genomic identity to that targeted) with a linearity of R2=0.9999 and a limit of detection of ~1% of the community. Closely related genotypes were distinguishable by differing hybridization patterns across each probe set. This arrayâs multiple-probe, âgenome-proxyâ approach and consequent ability to track both target genotypes and their close relatives is important for the arrayâs environmental application given the recent discoveries of considerable intra-population diversity within marine microbial communities. Keywords: target addition experiment, proof-of-concept for GPL6012 ***Overall Array design*** The prototype microarray targeted thirteen BAC or fosmid genome fragments (20-160kb) from both bacteria and archaea, recovered from a variety of marine habitats, as well as the cyanobacterium Prochlorococcus MED4. These clones were originally sequenced because of the presence of taxonomic marker or specific functional genes. This array consisted of sets of 70-bp oligonucleotides targeting each genome or genome fragment (Fig. 1), dispersed along the target sequences with no more than one probe per gene, and excluding rRNA genes as targets. The probes were selected solely based on theoretical thermodynamic properties and GC content (~40%); that is, probe selection did not focus on specific genes or regions, but simply produced the âoptimalâ probes for each genome proxy based on the probesâ predicted hybridization properties. rRNA genes were excluded, because this probe design approach, which avoids sequence alignments and considerations of RNA secondary structure, would be unlikely to result in useful rRNA probes. Furthermore, rRNA probes of traditional design could not be included on the array because their appropriate hybridization conditions would be very different from those of this arrayâs probes. ***Microarray probe design*** Microarray 70-mer probes were designed using the program ArrayOligoSelector (Zhu et al., 2003) with the following settings: target %GC = 40%, 1 probe/gene, with the ORFs for each genome fragment as both the input and the database file. The output candidate 70mers were then sorted based on their %GC and those closest to 40% were chosen. In the case of more than the target number of probes having 40%GC, the subset with the lowest free energy of hybridization were selected as probes. Generally, 20 probes were selected per organism. Prochlorococcus MED4 was represented by 60 probes total, 20 each for three different 80kb âgenome-proxyâ regions: 0-80kb, 1.29-1.37Mbp, and 1.58 to 1.66Mbp. Using the same method, a set (n=20) of positive control probes were designed to the genome of the halophillic archaeon Halobacterium salinarum NRC-1. Negative control probes (n=28) were designed to a set of 49 random 1000-base sequences (Stothard, 2000). ***Microarray construction and hybridization*** Oligonucleotides were synthesized (Illumina, San Diego, California), suspended in 3XSSC to a concentration of 40pmol/μl, and spotted on homemade poly-L-lysine-coated glass slides using a QArray 2 microarraying robot (Genetix, Hampshire, England). Six replicates of each probe were spotted. ***Microarray data analysis*** Hybridized arrays were scanned using an Axon Instruments 4000B scanner (Foster City, CA) and the data was normalized and filtered using perl scripts written for the purpose, by the following steps. (1) Signal intensities for each spot were calculated by subtracting the local background (mean F532 â median B532, as calculated by GenePix Pro 5.1 software, Axon Instruments). (2) The median value across replicates was calculated for each probe. (3) For each probe set, the number of probes greater than twice the mean negative control signal was calculated, before further processing. (4) Filter I: Arrays with less than half their positive control probes exceeding twice the mean negative control signal were considered poor quality, low dynamic range, arrays and were excluded from further analysis. (5) Each probe signal was corrected for non-specific binding by subtracting the mean negative control spot signal. (6) The data was then normalized for array-to-array variations in brightness by dividing each probe signal by the mean positive control signal. This positive control signal was the mean signal across the Halobacterium salinarum probes in each hybridization, with identical amounts of H. salinarum DNA having been added to each reaction prior to amplification and labeling. (7) Filter II: In order for a genotype to be considered âpresentâ, at least 45% of its probes had to exceed twice the mean negative control signal. (8) Finally, each genotype signal was calculated as either the MEAN or TUKEY BIWEIGHT across its probe set. ***Experimental Design*** The array was hybridized to laboratory mixtures of cloned environmental genomic DNA targeted by the array, in varying ratios. The use of multiple probes to target many genes from each organism helped to normalize probe-to-probe heterogeneity, by averaging across all probes in a set (as described below). The evenness of probe response across each genotypeâs set was also used to evaluate the relatedness of hybridizing DNA. To more precisely define the arrayâs phylogenetic range and specificity, it was tested against DNA from Prochlorococcus MED4 and related strains, spanning the known range of Prochlorococcus phylogenetic diversity. To test the effects of hybridization stringency on the specificity and signal of the MED4 probes, Prochlorococcus strains were hybridized at a range of conditions. To test whether the specificity results for Prochlorococcus were comparable for other targeted clades, two genome fragments recovered from closely related phylotypes within the SAR86 clade of the gamma-proteobacteria were represented on the array, and were tested for specificity. To understand the equivalence of probe sets targeting different regions of the same organismâs genome, we targeted three 80kb âgenome proxyâ regions of the Prochlorococcus MED4 genome. One of the regions fell in a genomic âislandâ where inter-strain variability is concentrated (âISL5â in Coleman et al., 2006). To test the array in a complex environmental context, we collected coastal seawater (lacking detectable Prochlorococcus cells by flow cytometry) and added Prochlorococcus cells from strains MED4, MIT9515, MIT9312 and MIT9313 over a range of concentrations from ~101 â 106 cells/ml (Fig. 3). The seawater was then filtered and the DNA extracted, amplified, labeled, and hybridized to the array.
2010-05-25 | E-GEOD-9384 | biostudies-arrayexpress
Project description:Metabolic crossfeeding is an important process that can broadly shape microbial communities. However, little is known about specific crossfeeding principles that drive the formation and maintenance of individuals within a mixed population. Here, we devised a series of synthetic syntrophic communities to probe the complex interactions underlying metabolic exchange of amino acids. We experimentally analyzed multimember, multidimensional communities of Escherichia coli of increasing sophistication to assess the outcomes of synergistic crossfeeding. We find that biosynthetically costly amino acids including methionine, lysine, isoleucine, arginine, and aromatics, tend to promote stronger cooperative interactions than amino acids that are cheaper to produce. Furthermore, cells that share common intermediates along branching pathways yielded more synergistic growth, but exhibited many instances of both positive and negative epistasis when these interactions scaled to higher dimensions. In more complex communities, we find certain members exhibiting keystone species-like behavior that drastically impact the community dynamics. Based on comparative genomic analysis of >6,000 sequenced bacteria from diverse environments, we present evidence suggesting that amino acid biosynthesis has been broadly optimized to reduce individual metabolic burden in favor of enhanced crossfeeding to support synergistic growth across the biosphere. These results improve our basic understanding of microbial syntrophy while also highlighting the utility and limitations of current modeling approaches to describe the dynamic complexities underlying microbial ecosystems. This work sets the foundation for future endeavors to resolve key questions in microbial ecology and evolution, and presents a platform to develop better and more robust engineered synthetic communities for industrial biotechnology.
| S-EPMC4034247 | biostudies-literature
Project description:Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology.
| S-EPMC6600964 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2014-12-21 | GSE64376 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-12-21 | E-GEOD-64376 | biostudies-arrayexpress
Project description:The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model-guided framework to predict higher-dimensional consortia from time-resolved measurements of lower-order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi-species community dynamics, as opposed to higher-order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history-dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human-associated intestinal species and illuminated design principles of microbial communities.
| S-EPMC6011841 | biostudies-literature
Project description:Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions.
| S-EPMC8079826 | biostudies-literature
Project description:The increased urban pressures are often associated with specialization of microbial communities. Microbial communities being a critical player in the geochemical processes, makes it important to identify key environmental parameters that influence the community structure and its function.In this proect we study the influence of land use type and environmental parameters on the structure and function of microbial communities. The present study was conducted in an urban catchment, where the metal and pollutants levels are under allowable limits. The overall goal of this study is to understand the role of engineered physicochemical environment on the structure and function of microbial communities in urban storm-water canals.
2014-12-22 | GSE64286 | GEO