Lipidome Plasticity Enables Unusual Photosynthetic Flexibility in Arctic vs. Temperate Diatoms.

The diatom lipidome actively regulates photosynthesis and displays a high degree of plasticity in response to a light environment, either directly as structural modifications of thylakoid membranes and protein-pigment complexes, or indirectly via photoprotection mechanisms that dissipate excess light energy. This acclimation is crucial to maintaining primary production in marine systems, particularly in polar environments, due to the large temporal variations in both the intensity and wavelength distributions of downwelling solar irradiance. This study investigated the hypothesis that Arctic marine diatoms uniquely modify their lipidome, including their concentration and type of pigments, in response to wavelength-specific light quality in their environment. We postulate that Arctic-adapted diatoms can adapt to regulate their lipidome to maintain growth in response to the extreme variability in photosynthetically active radiation. This was tested by comparing the untargeted lipidomic profiles, pigmentation, specific growth rates and carbon assimilation of the Arctic diatom Porosira glacialis vs. the temperate species Coscinodiscus radiatus during exponential growth under red, blue and white light. Here, we found that the chromatic wavelength influenced lipidome remodeling and growth in each strain, with P. glacialis showing effective utilization of red light coupled with increased inclusion of primary light-harvesting pigments and polar lipid classes. These results indicate a unique photoadaptation strategy that enables Arctic diatoms like P. glacialis to capitalize on a wide chromatic growth range and demonstrates the importance of active lipid regulation in the Arctic light environment.

Microbial Community Dynamics during a Harmful Chrysochromulina leadbeateri Bloom in Northern Norway.

A harmful algal bloom occurred in late spring 2019 across multiple, interconnected fjords and bays in northern Norway. The event was caused by the haptophyte Chrysochromulina leadbeateri and led to severe fish mortality at several salmon aquaculture facilities. This study reports on the spatial and temporal succession dynamics of the holistic marine microbiome associated with this bloom by relating all detectable 18S and 16S rRNA gene amplicon sequence variants to the relative abundance of the C. leadbeateri focal taxon. A k-medoid clustering enabled inferences on how the causative focal taxon cobloomed with diverse groups of bacteria and microeukaryotes. These coblooming patterns showed high temporal variability and were distinct between two geographically separated time series stations during the regional harmful algal bloom. The distinct blooming patterns observed with respect to each station were poorly connected to environmental conditions, suggesting that other factors, such as biological interactions, may be at least as important in shaping the dynamics of this type of harmful algal bloom. A deeper understanding of microbiome succession patterns during these rare but destructive events will help guide future efforts to forecast deviations from the natural bloom cycles of the northern Norwegian coastal marine ecosystems that are home to intensive aquaculture activities. IMPORTANCE The 2019 Chrysochromulina leadbeateri bloom in northern Norway had a major impact on the local economy and society through its devastating effect on the aquaculture industry. However, many fail to remember that C. leadbeateri is, in fact, a common member of the seasonal marine microbiome and the same spring phytoplankton blooms that support the marine ecosystem. It is challenging to draw any conclusions about exact causation behind the harmful bloom of 2019, especially since the natural bloom cycles of C. leadbeateri are not well understood. This study begins to fill major knowledge gaps that may lead to future forecasting abilities, by providing a molecular-based investigation of the destructive 2019 bloom that presents new insights into a seasonal marine microbial ecosystem during one of these sporadically reoccurring events.

Systems biology: current status and challenges.

We put together a special issue on current approaches in systems biology with a focus on mathematical modeling of metabolic networks. Mathematical models have increasingly been used to unravel molecular mechanisms of complex dynamic biological processes. We here provide a short introduction into the topics covered in this special issue, highlighting current developments and challenges.

Structure Dependent Determination of Organophosphate Targets in Mammalian Tissues Using Activity-Based Protein Profiling.

Acute and chronic exposures to organophosphates (OPs), including agricultural pesticides, industrial chemicals, and chemical warfare agents, remain a significant worldwide health risk. The mechanisms by which OPs alter development and cognition in exposed individuals remain poorly understood, in part due to the large number of structurally diverse OPs and the wide range of affected proteins and signaling pathways. To investigate the influence of structure on OP targets in mammalian systems, we have developed a series of probes for activity-based protein profiling (ABPP) featuring two distinct reactive groups that mimic OP chemical reactivity. FOP features a fluorophosphonate moiety, and PODA and CODA utilize a dialkynyl phosphate ester; both reactive group types target serine hydrolase activity. As the oxon represents the highly reactive and toxic functional group of many OPs, the new probes described herein enhance our understanding of tissue-specific reactivity of OPs. Chemoproteomic analysis of mouse tissues treated with the probes revealed divergent protein profiles, demonstrating the influence of probe structure on protein targeting. These targets also vary in sensitivity toward different OPs. The simultaneous use of multiple probes in ABPP experiments may therefore offer more comprehensive coverage of OP targets; FOP consistently labeled more targets in both brain and liver than PODA or CODA, suggesting the dialkyne warhead is more selective for enzymes in major signaling pathways than the more reactive fluorophosphonate warhead. Additionally, the probes can be used to assess reactivation of OP-inhibited enzymes by N-oximes and may serve as diagnostic tools for screening of therapeutic candidates in a panel of protein targets. These applications will help clarify the short- and long-term effects of OP toxicity beyond acetylcholinesterase inhibition, investigate potential points of convergence for broad spectrum therapeutic development, and support future efforts to screen candidate molecules for efficacy in various model systems.

Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction.

Metabolic network modeling of microbial communities provides an in-depth understanding of community-wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high-quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community-level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph-heterotroph consortium that was used to provide data needed for a community-level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources. J. Cell. Physiol. 231: 2339-2345, 2016. © 2016 Wiley Periodicals, Inc.

Dinitrogenase-Driven Photobiological Hydrogen Production Combats Oxidative Stress in Cyanothece sp. Strain ATCC 51142.

Photobiologically synthesized hydrogen (H2) gas is carbon neutral to produce and clean to combust, making it an ideal biofuel. Cyanothece sp. strain ATCC 51142 is a cyanobacterium capable of performing simultaneous oxygenic photosynthesis and H2 production, a highly perplexing phenomenon because H2 evolving enzymes are O2 sensitive. We employed a system-level in vivo chemoproteomic profiling approach to explore the cellular dynamics of protein thiol redox and how thiol redox mediates the function of the dinitrogenase NifHDK, an enzyme complex capable of aerobic hydrogenase activity. We found that NifHDK responds to intracellular redox conditions and may act as an emergency electron valve to prevent harmful reactive oxygen species formation in concert with other cell strategies for maintaining redox homeostasis. These results provide new insight into cellular redox dynamics useful for advancing photolytic bioenergy technology and reveal a new understanding for the biological function of NifHDK. IMPORTANCE: Here, we demonstrate that high levels of hydrogen synthesis can be induced as a protection mechanism against oxidative stress via the dinitrogenase enzyme complex in Cyanothece sp. strain ATCC 51142. This is a previously unknown feature of cyanobacterial dinitrogenase, and we anticipate that it may represent a strategy to exploit cyanobacteria for efficient and scalable hydrogen production. We utilized a chemoproteomic approach to capture the in situ dynamics of reductant partitioning within the cell, revealing proteins and reactive thiols that may be involved in redox sensing and signaling. Additionally, this method is widely applicable across biological systems to achieve a greater understanding of how cells navigate their environment and how redox chemistry can be utilized to alter metabolism and achieve homeostasis.

Microsensor and transcriptomic signatures of oxygen depletion in biofilms associated with chronic wounds.

Biofilms have been implicated in delayed wound healing, although the mechanisms by which biofilms impair wound healing are poorly understood. Many species of bacteria produce exotoxins and exoenzymes that may inhibit healing. In addition, oxygen consumption by biofilms and by the responding leukocytes, may impede wound healing by depleting the oxygen that is required for healing. In this study, oxygen microsensors to measure oxygen transects through in vitro cultured biofilms, biofilms formed in vivo within scabs from a diabetic (db/db) mouse wound model, and ex vivo human chronic wound specimens was used. The results showed that oxygen levels within mouse scabs had steep gradients that reached minima ranging from 17 to 72 mmHg on live mice and from 6.4 to 1.1 mmHg on euthanized mice. The oxygen gradients in the mouse scabs were similar to those observed for clinical isolates cultured in vitro and for human ex vivo specimens. To characterize the metabolic activities of the bacteria in the mouse scabs, transcriptomics analyses of Pseudomonas aeruginosa biofilms associated with the db/db mice wounds was performed. The results demonstrated that the bacteria expressed genes for metabolic activities associated with cell growth. Interestingly, the transcriptome results also indicated that the bacteria within the wounds experienced oxygen-limitation stress. Among the bacterial genes that were expressed in vivo were genes associated with the Anr-mediated hypoxia-stress response. Other bacterial stress response genes highly expressed in vivo were genes associated with stationary-phase growth, osmotic stress, and RpoH-mediated heat shock stress. Overall, the results supported the hypothesis that bacterial biofilms in chronic wounds promote chronicity by contributing to the maintenance of localized low oxygen tensions, through their metabolic activities and through their recruitment of cells that consume oxygen for host defensive processes.

Iron induces bimodal population development by Escherichia coli.

Bacterial biofilm formation is a complex developmental process involving cellular differentiation and the formation of intricate 3D structures. Here we demonstrate that exposure to ferric chloride triggers rugose biofilm formation by the uropathogenic Escherichia coli strain UTI89 and by enteric bacteria Citrobacter koseri and Salmonella enterica serovar typhimurium. Two unique and separable cellular populations emerge in iron-triggered, rugose biofilms. Bacteria at the air-biofilm interface express high levels of the biofilm regulator csgD, the cellulose activator adrA, and the curli subunit operon csgBAC. Bacteria in the interior of rugose biofilms express low levels of csgD and undetectable levels of matrix components curli and cellulose. Iron activation of rugose biofilms is linked to oxidative stress. Superoxide generation, either through addition of phenazine methosulfate or by deletion of sodA and sodB, stimulates rugose biofilm formation in the absence of high iron. Additionally, overexpression of Mn-superoxide dismutase, which can mitigate iron-derived reactive oxygen stress, decreases biofilm formation in a WT strain upon iron exposure. Not only does reactive oxygen stress promote rugose biofilm formation, but bacteria in the rugose biofilms display increased resistance to H(2)O(2) toxicity. Altogether, we demonstrate that iron and superoxide stress trigger rugose biofilm formation in UTI89. Rugose biofilm development involves the elaboration of two distinct bacterial populations and increased resistance to oxidative stress.

In situ analysis of oxygen consumption and diffusive transport in high-temperature acidic iron-oxide microbial mats.

The role of dissolved oxygen as a principal electron acceptor for microbial metabolism was investigated within Fe(III)-oxide microbial mats that form in acidic geothermal springs of Yellowstone National Park (USA). Specific goals of the study were to measure and model dissolved oxygen profiles within high-temperature (65-75°C) acidic (pH = 2.7-3.8) Fe(III)-oxide microbial mats, and correlate the abundance of aerobic, iron-oxidizing Metallosphaera yellowstonensis organisms and mRNA gene expression levels to Fe(II)-oxidizing habitats shown to consume oxygen. In situ oxygen microprofiles were obtained perpendicular to the direction of convective flow across the aqueous phase/Fe(III)-oxide microbial mat interface using oxygen microsensors. Dissolved oxygen concentrations dropped from ∼ 50-60 µM in the bulk-fluid/mat surface to below detection (< 0.3 µM) at a depth of ∼ 700 µm (∼ 10% of the total mat depth). Net areal oxygen fluxes into the microbial mats were estimated to range from 1.4-1.6 × 10(-4) µmol cm(-2) s(-1) . Dimensionless parameters were used to model dissolved oxygen profiles and establish that mass transfer rates limit the oxygen consumption. A zone of higher dissolved oxygen at the mat surface promotes Fe(III)-oxide biomineralization, which was supported using molecular analysis of Metallosphaera yellowstonensis 16S rRNA gene copy numbers and mRNA expression of haem Cu oxidases (FoxA) associated with Fe(II)-oxidation.

Differentiation of microbial species and strains in coculture biofilms by multivariate analysis of laser desorption postionization mass spectra.

7.87 to 10.5 eV vacuum ultraviolet (VUV) photon energies were used in laser desorption postionization mass spectrometry (LDPI-MS) to analyze biofilms comprised of binary cultures of interacting microorganisms. The effect of photon energy was examined using both tunable synchrotron and laser sources of VUV radiation. Principal components analysis (PCA) was applied to the MS data to differentiate species in Escherichia coli-Saccharomyces cerevisiae coculture biofilms. PCA of LDPI-MS also differentiated individual E. coli strains in a biofilm comprised of two interacting gene deletion strains, even though these strains differed from the wild type K-12 strain by no more than four gene deletions each out of approximately 2000 genes. PCA treatment of 7.87 eV LDPI-MS data separated the E. coli strains into three distinct groups, two "pure" groups, and a mixed region. Furthermore, the "pure" regions of the E. coli cocultures showed greater variance by PCA at 7.87 eV photon energies compared to 10.5 eV radiation. This is consistent with the expectation that the 7.87 eV photoionization selects a subset of low ionization energy analytes while 10.5 eV is more inclusive, detecting a wider range of analytes. These two VUV photon energies therefore give different spreads via PCA and their respective use in LDPI-MS constitute an additional experimental parameter to differentiate strains and species.

Laser desorption VUV postionization MS imaging of a cocultured biofilm.

Laser desorption postionization mass spectrometry (LDPI-MS) imaging is demonstrated with a 10.5 eV photon energy source for analysis and imaging of small endogenous molecules within intact biofilms. Biofilm consortia comprised of a synthetic Escherichia coli K12 coculture engineered for syntrophic metabolite exchange are grown on membranes and then used to test LDPI-MS analysis and imaging. Both E. coli strains displayed many similar peaks in LDPI-MS up to m/z 650, although some observed differences in peak intensities were consistent with the appearance of byproducts preferentially expressed by one strain. The relatively low mass resolution and accuracy of this specific LDPI-MS instrument prevented definitive assignment of species to peaks, but strategies are discussed to overcome this shortcoming. The results are also discussed in terms of desorption and ionization issues related to the use of 10.5 eV single-photon ionization, with control experiments providing additional mechanistic information. Finally, 10.5 eV LDPI-MS was able to collect ion images from intact, electrically insulating biofilms at ~100 µm spatial resolution. Spatial resolution of ~20 µm was possible, although a relatively long acquisition time resulted from the 10 Hz repetition rate of the single-photon ionization source.

Revealing the Host-Dependent Nature of an Engineered Genetic Inverter in Concordance with Physiology.

Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to "model status," synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the "chassis effect." It remains a major challenge to uncover which genome-encoded and biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of genetic circuit performance. This was accomplished using a comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis effect and characterize the performance dynamics of a genetic inverter circuit operating within 6 Gammaproteobacteria. Our results solidify the notion that genetic devices are strongly impacted by the host context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar performance of the genetic inverter, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.

Daylight-driven carbon exchange through a vertically structured microbial community.

Interactions between autotrophs and heterotrophs are central to carbon (C) exchange across trophic levels in essentially all ecosystems and metabolite exchange is a frequent mechanism for distributing C within spatially structured ecosystems. Yet, despite the importance of C exchange, the timescales at which fixed C is transferred in microbial communities is poorly understood. We employed a stable isotope tracer combined with spatially resolved isotope analysis to quantify photoautotrophic uptake of bicarbonate and track subsequent exchanges across a vertical depth gradient in a stratified microbial mat over a light-driven diel cycle. We observed that C mobility, both across the vertical strata and between taxa, was highest during periods of active photoautotrophy. Parallel experiments with 13C-labeled organic substrates (acetate and glucose) showed comparably less exchange of C within the mat. Metabolite analysis showed rapid incorporation of 13C into molecules that can both comprise a portion of the extracellular polymeric substances in the system and serve to transport C between photoautotrophs and heterotrophs. Stable isotope proteomic analysis revealed rapid C exchange between cyanobacterial and associated heterotrophic community members during the day with decreased exchange at night. We observed strong diel control on the spatial exchange of freshly fixed C within tightly interacting mat communities suggesting a rapid redistribution, both spatially and taxonomically, primarily during daylight periods.

Diversity and Selection of Surface Marine Microbiomes in the Atlantic-Influenced Arctic.

Arctic marine environments are experiencing rapid changes due to the polar amplification of global warming. These changes impact the habitat of the cold-adapted microbial communities, which underpin biogeochemical cycles and marine food webs. We comparatively investigated the differences in prokaryotic and microeukaryotic taxa between summer surface water microbiomes sampled along a latitudinal transect from the ice-free southern Barents Sea and into the sea-ice-covered Nansen Basin to disentangle the dominating community (ecological) selection processes driving phylogenetic diversity. The community structure and richness of each site-specific microbiome were assessed in relation to the physical and biogeochemical conditions of the environment. A strong homogeneous deterministic selection process was inferred across the entire sampling transect via a phylogenetic null modeling approach. The microbial species richness and diversity were not negatively influenced by northward decreasing temperature and salinity. The results also suggest that regional phytoplankton blooms are a major prevalent factor in governing the bacterial community structure. This study supports the consideration that strong homogeneous selection is imposed across these cold-water marine environments uniformly, regardless of geographic assignments within either the Nansen Basin or the Barents Sea.

Flashing lights affect the photophysiology and expression of carotenoid and lipid synthesis genes in Nannochloropsis gaditana.

Nannochloropsis gaditana is a promising microalga for biotechnology. One of the strategies to stimulate its full potential in metabolite production is exposure to flashing lights. Here, we report how N. gaditana adapts to different flashing light regimes (5, 50, and 500 Hz) by changing its cellular physiology and the relative expression of genes related to critical cellular functions. We analyzed the differential mRNA abundance of genes related to photosynthesis, nitrogen assimilation and biosynthesis of chlorophyll, carotenoids, lipids, fatty acids and starch. Analysis of photosynthetic efficiency and high mRNA abundance of photoprotection genes supported the inference that excess excitation energy provided by light absorbance during photosynthesis was produced under low frequency flashing lights and was dissipated by photopigments via the xanthophyll-cycle. Increased relative expression levels of genes related to the synthesis of carotenoids and chlorophyll confirmed the accumulation of photopigments previously observed at low frequency flashing lights. Higher differential mRNA abundance of genes related to the triacylglycerol biosynthesis were observed at lower frequency flashing lights, possibly triggered by a poor nitrogen assimilation caused by low mRNA abundance of a nitrate reductase gene. This study advances a new understanding of algal physiology and metabolism leading to improved cellular performance and metabolite production.

Environment Constrains Fitness Advantages of Division of Labor in Microbial Consortia Engineered for Metabolite Push or Pull Interactions.

Fitness benefits from division of labor are well documented in microbial consortia, but the dependency of the benefits on environmental context is poorly understood. Two synthetic Escherichia coli consortia were built to test the relationships between exchanged organic acid, local environment, and opportunity costs of different metabolic strategies. Opportunity costs quantify benefits not realized due to selecting one phenotype over another. The consortia catabolized glucose and exchanged either acetic or lactic acid to create producer-consumer food webs. The organic acids had different inhibitory properties and different opportunity costs associated with their positions in central metabolism. The exchanged metabolites modulated different consortial dynamics. The acetic acid-exchanging (AAE) consortium had a "push" interaction motif where acetic acid was secreted faster by the producer than the consumer imported it, while the lactic acid-exchanging (LAE) consortium had a "pull" interaction motif where the consumer imported lactic acid at a comparable rate to its production. The LAE consortium outperformed wild-type (WT) batch cultures under the environmental context of weakly buffered conditions, achieving a 55% increase in biomass titer, a 51% increase in biomass per proton yield, an 86% increase in substrate conversion, and the complete elimination of by-product accumulation all relative to the WT. However, the LAE consortium had the trade-off of a 42% lower specific growth rate. The AAE consortium did not outperform the WT in any considered performance metric. Performance advantages of the LAE consortium were sensitive to environment; increasing the medium buffering capacity negated the performance advantages compared to WT. IMPORTANCE Most naturally occurring microorganisms persist in consortia where metabolic interactions are common and often essential to ecosystem function. This study uses synthetic ecology to test how different cellular interaction motifs influence performance properties of consortia. Environmental context ultimately controlled the division of labor performance as shifts from weakly buffered to highly buffered conditions negated the benefits of the strategy. Understanding the limits of division of labor advances our understanding of natural community functioning, which is central to nutrient cycling and provides design rules for assembling consortia used in applied bioprocessing.

Reconciling Ecological and Engineering Design Principles for Building Microbiomes.

Simplified microbial communities, or "benchtop microbiomes," enable us to manage the profound complexity of microbial ecosystems. Widespread activities aiming to design and control communities result in novel resources for testing ecological theories and also for realizing new biotechnologies. There is much to be gained by reconciling engineering design principles with ecological processes that shape microbiomes in nature. In this short Perspective, I will address how natural processes such as environmental filtering, the establishment of priority effects, and community "blending" (coalescence) can be harnessed for engineering microbiomes from complex starting materials. I will also discuss how future microbiome architects may draw inspiration from modern practices in synthetic biology. This topic is based on an important overarching research goal, which is to understand how natural forces shape microbial communities and interspecies interactions such that new engineering design principles can be extracted to promote human health or energy and environmental sustainability.

Forfeiting the priority effect: turnover defines biofilm community succession.

Microbial community succession is a fundamental process that affects underlying functions of almost all ecosystems; yet the roles and fates of the most abundant colonizers are often poorly understood. Does early abundance spur long term persistence? How do deterministic and stochastic processes influence the ecological contribution of colonizers? We performed a succession experiment within a hypersaline ecosystem to investigate how different processes contributed to the turnover of founder species. Bacterial and eukaryotic colonizers were identified during primary succession and tracked through a defined, 79-day biofilm maturation period using 16S and 18S rRNA gene sequencing in combination with high resolution imaging that utilized stable isotope tracers to evaluate successional patterns of primary producers and nitrogen fixers. The majority of the founder species did not maintain high abundance throughout succession. Species replacement (versus loss) was the dominant process shaping community succession. We also asked if different ecological processes acted on bacteria versus Eukaryotes during succession and found deterministic and stochastic forces corresponded more with microeukaryote and bacterial colonization, respectively. Our results show that taxa and functions belonging to different kingdoms, which share habitat in the tight spatial confines of a biofilm, were influenced by different ecological processes and time scales of succession.

Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities.

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that - in many cases - adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future.