Vaccination reshapes the virus-specific T cell repertoire in unexposed adults.

We examined how baseline CD4+ T cell repertoire and precursor states impact responses to pathogen infection in humans using primary immunization with yellow fever virus (YFV) vaccine. YFV-specific T cells in unexposed individuals were identified by peptide-MHC tetramer staining and tracked pre- and post-vaccination by tetramers and TCR sequencing. A substantial number of YFV-reactive T cells expressed memory phenotype markers and contained expanded clones in the absence of exposure to YFV. After vaccination, pre-existing YFV-specific T cell populations with low clonal diversity underwent limited expansion, but rare populations with a reservoir of unexpanded TCRs generated robust responses. These altered dynamics reorganized the immunodominance hierarchy and resulted in an overall increase in higher avidity T cells. Thus, instead of further increasing the representation of dominant clones, YFV vaccination recruits rare and more responsive T cells. Our findings illustrate the impact of vaccines in prioritizing T cell responses and reveal repertoire reorganization as a key component of effective vaccination.

BGCFlow: systematic pangenome workflow for the analysis of biosynthetic gene clusters across large genomic datasets.

Genome mining is revolutionizing natural products discovery efforts. The rapid increase in available genomes demands comprehensive computational platforms to effectively extract biosynthetic knowledge encoded across bacterial pangenomes. Here, we present BGCFlow, a novel systematic workflow integrating analytics for large-scale genome mining of bacterial pangenomes. BGCFlow incorporates several genome analytics and mining tools grouped into five common stages of analysis such as: (i) data selection, (ii) functional annotation, (iii) phylogenetic analysis, (iv) genome mining, and (v) comparative analysis. Furthermore, BGCFlow provides easy configuration of different projects, parallel distribution, scheduled job monitoring, an interactive database to visualize tables, exploratory Jupyter Notebooks, and customized reports. Here, we demonstrate the application of BGCFlow by investigating the phylogenetic distribution of various biosynthetic gene clusters detected across 42 genomes of the Saccharopolyspora genus, known to produce industrially important secondary/specialized metabolites. The BGCFlow-guided analysis predicted more accurate dereplication of BGCs and guided the targeted comparative analysis of selected RiPPs. The scalable, interoperable, adaptable, re-entrant, and reproducible nature of the BGCFlow will provide an effective novel way to extract the biosynthetic knowledge from the ever-growing genomic datasets of biotechnologically relevant bacterial species.

Effect of zinc oxide-eugenol endodontic paste on planktonic aggregates and biofilm of Enterococcus faecalis - An atomic force microscopy evaluation.

OBJECTIVE: This work aimed to evaluate the in vitro effect of zinc oxide-eugenol paste (ZOE) on planktonic aggregates (EfPA) and biofilm (EfBio) of Enterococcus faecalis, focusing on their morphological aspects observed and analyzed using atomic force microscopy (AFM). DESIGN: The eugenol and paste were characterized by Gas Chromatography coupled with Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FTIR), respectively. The effect of ZOE on EfPA and EfBio was evaluated by a direct-contact test through colony counting and crystal violet staining protocol. AFM images of untreated and treated EfPA and EfBio growth on bovine dentin were obtained to analyze the morphological damage caused by the treatments. RESULTS: The characterization showed high purity in the eugenol composition and chemical interaction between the components of the paste. A bactericidal effect on aggregates was observed after 6 h of exposure, and on biofilm after 24 h of treatment (p < 0.001). A disruptive effect on the biofilm was also evident. AFM images revealed the formation of EfPA, with a notable presence of an exopolysaccharide matrix. After 6 h of ZOE treatment, there was a significant increase in the size and surface roughness profile of treated cells (p < 0.05). Loss of typical cell morphology was observed after 24 h. The effect on the biofilm showed a tendency towards a less condensed biofilm pattern in the treated group, with no differences in surface roughness. CONCLUSION: ZOE presents bactericidal action on EfPA and EfBio, promoting significant morphological changes after treatment, especially in the aggregates.

Successful large gene augmentation of USH2A with non-viral episomal vectors.

USH2A mutations are a common cause of autosomal recessive retinitis pigmentosa (RP) and Usher syndrome, for which there are currently no approved treatments. Gene augmentation is a valuable therapeutic strategy for treating many inherited retinal diseases; however, conventional adeno-associated virus (AAV) gene therapy cannot accommodate cDNAs exceeding 4.7 kb, such as the 15.6-kb-long USH2A coding sequence. In the present study, we adopted an alternative strategy to successfully generate scaffold/matrix attachment region (S/MAR) DNA plasmid vectors containing the full-length human USH2A coding sequence, a GFP reporter gene, and a ubiquitous promoter (CMV or CAG), reaching a size of approximately 23 kb. We assessed the vectors in transfected HEK293 cells and USH2A patient-derived dermal fibroblasts in addition to ush2au507 zebrafish microinjected with the vector at the one-cell stage. pS/MAR-USH2A vectors drove persistent transgene expression in patient fibroblasts with restoration of usherin. Twelve months of GFP expression was detected in the photoreceptor cells, with rescue of Usher 2 complex localization in the photoreceptors of ush2au507 zebrafish retinas injected with pS/MAR-USH2A. To our knowledge, this is the first reported vector that can be used to express full-length usherin with functional rescue. S/MAR DNA vectors have shown promise as a novel non-viral retinal gene therapy, warranting further translational development.

Mindfulness to enhance quality of life and support advance care planning: a pilot randomized controlled trial for adults with advanced cancer and their family caregivers.

BACKGROUND: Patients with advanced cancer and family caregivers often use avoidant coping strategies, such as delaying advance care planning discussions, which contribute to deterioration in their quality of life. Mindfulness-based interventions have shown promise in improving quality of life in this population but have rarely been applied to advance care planning. This pilot trial examined the preliminary efficacy of a group-based Mindfulness to Enhance Quality of Life and Support Advance Care Planning (MEANING) intervention for patient-caregiver dyads coping with advanced cancer. Primary outcomes were patient and caregiver quality of life or well-being, and secondary outcomes included patient advanced care planning engagement (self-efficacy and readiness) and other psychological and symptom outcomes. METHODS: In this pilot trial, dyads coping with advanced cancer were recruited from five oncology clinics in the midwestern U.S. and randomized to six weekly group sessions of a mindfulness intervention (n = 33 dyads) or usual care (n = 22 dyads). Outcomes were assessed via surveys at baseline, post-intervention, and 1 month post-intervention. All available data were included in the multilevel models assessing intervention efficacy. RESULTS: Patients in the MEANING condition experienced significant increases in existential well-being and self-efficacy for advance care planning across follow-ups, whereas usual care patients did not. Other group differences in outcomes were not statistically significant. These outcomes included other facets of patient well-being, caregiver quality of life, patient readiness for advance care planning, caregiver burden, and patient and caregiver depressive symptoms, anxiety, sleep disturbance, cognitive avoidance, and peaceful acceptance of cancer. However, only MEANING patients showed moderate increases in psychological well-being across follow-ups, and MEANING caregivers showed moderate increases in quality of life at 1-month follow-up. Certain psychological outcomes, such as caregiver burden at 1-month follow-up, also showed moderate improvement in the MEANING condition. Patients in both conditions reported small to moderate increases in readiness to engage in advance care planning. CONCLUSIONS: A mindfulness-based intervention showed promise in improving quality-of-life and advance care planning outcomes in patients and caregivers coping with advanced cancer and warrants further testing. TRIAL REGISTRATION: ClinicalTrials.gov NCT03257007. Registered 22 August 2017, https://clinicaltrials.gov/ct2/show/NCT03257007 .

Laboratory evolution reveals general and specific tolerance mechanisms for commodity chemicals.

Although strain tolerance to high product concentrations is a barrier to the economically viable biomanufacturing of industrial chemicals, chemical tolerance mechanisms are often unknown. To reveal tolerance mechanisms, an automated platform was utilized to evolve Escherichia coli to grow optimally in the presence of 11 industrial chemicals (1,2-propanediol, 2,3-butanediol, glutarate, adipate, putrescine, hexamethylenediamine, butanol, isobutyrate, coumarate, octanoate, hexanoate), reaching tolerance at concentrations 60%-400% higher than initial toxic levels. Sequencing genomes of 223 isolates from 89 populations, reverse engineering, and cross-compound tolerance profiling were employed to uncover tolerance mechanisms. We show that: 1) cells are tolerized via frequent mutation of membrane transporters or cell wall-associated proteins (e.g., ProV, KgtP, SapB, NagA, NagC, MreB), transcription and translation machineries (e.g., RpoA, RpoB, RpoC, RpsA, RpsG, NusA, Rho), stress signaling proteins (e.g., RelA, SspA, SpoT, YobF), and for certain chemicals, regulators and enzymes in metabolism (e.g., MetJ, NadR, GudD, PurT); 2) osmotic stress plays a significant role in tolerance when chemical concentrations exceed a general threshold and mutated genes frequently overlap with those enabling chemical tolerance in membrane transporters and cell wall-associated proteins; 3) tolerization to a specific chemical generally improves tolerance to structurally similar compounds whereas a tradeoff can occur on dissimilar chemicals, and 4) using pre-tolerized starting isolates can hugely enhance the subsequent production of chemicals when a production pathway is inserted in many, but not all, evolved tolerized host strains, underpinning the need for evolving multiple parallel populations. Taken as a whole, this study provides a comprehensive genotype-phenotype map based on identified mutations and growth phenotypes for 223 chemical tolerant isolates.

iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning.

Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (Escherichia coli, Staphylococcus aureus and Bacillus subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.

Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers.

Enzyme turnover numbers (kcats) are essential for a quantitative understanding of cells. Because kcats are traditionally measured in low-throughput assays, they can be inconsistent, labor-intensive to obtain, and can miss in vivo effects. We use a data-driven approach to estimate in vivo kcats using metabolic specialist Escherichia coli strains that resulted from gene knockouts in central metabolism followed by metabolic optimization via laboratory evolution. By combining absolute proteomics with fluxomics data, we find that in vivo kcats are robust against genetic perturbations, suggesting that metabolic adaptation to gene loss is mostly achieved through other mechanisms, like gene-regulatory changes. Combining machine learning and genome-scale metabolic models, we show that the obtained in vivo kcats predict unseen proteomics data with much higher precision than in vitro kcats. The results demonstrate that in vivo kcats can solve the problem of inconsistent and low-coverage parameterizations of genome-scale cellular models.

The Bitome: digitized genomic features reveal fundamental genome organization.

A genome contains the information underlying an organism's form and function. Yet, we lack formal framework to represent and study this information. Here, we introduce the Bitome, a matrix composed of binary digits (bits) representing the genomic positions of genomic features. We form a Bitome for the genome of Escherichia coli K-12 MG1655. We find that: (i) genomic features are encoded unevenly, both spatially and categorically; (ii) coding and intergenic features are recapitulated at high resolution; (iii) adaptive mutations are skewed towards genomic positions with fewer features; and (iv) the Bitome enhances prediction of adaptively mutated and essential genes. The Bitome is a formal representation of a genome and may be used to study its fundamental organizational properties.

Healthy or not? The impact of conflicting health-related information on attentional resources.

Despite its ubiquity, little is known about the impact of exposure to conflicting health information on cognitive efficiency. We hypothesized that it would reduce attentional capacity, as evidenced by (1) increased response errors during the Attention Network Test (ANT), (2) decreased efficiency of each ANT system (alerting, orienting, execute control), and (3) increased self-reported workload, (4) nutritional confusion and (5) nutritional backlash. A sample of 184 online participants were assigned randomly to read an article containing either congruent or conflicting health information. Subsequently, they completed the ANT and self-report measures of workload, nutritional confusion, and backlash at nutritional recommendations and research. Participants in the conflicting health information condition made more errors, had overall slower reaction times, and reported greater workload, nutritional confusion, and backlash. No differences were found for individual ANT systems. These findings suggest that exposure to conflicting health information can degrade attentional mechanisms responsible for accurate and prompt responding to incoming information.

Adaptive evolution reveals a tradeoff between growth rate and oxidative stress during naphthoquinone-based aerobic respiration.

Evolution fine-tunes biological pathways to achieve a robust cellular physiology. Two and a half billion years ago, rapidly rising levels of oxygen as a byproduct of blooming cyanobacterial photosynthesis resulted in a redox upshift in microbial energetics. The appearance of higher-redox-potential respiratory quinone, ubiquinone (UQ), is believed to be an adaptive response to this environmental transition. However, the majority of bacterial species are still dependent on the ancient respiratory quinone, naphthoquinone (NQ). Gammaproteobacteria can biosynthesize both of these respiratory quinones, where UQ has been associated with aerobic lifestyle and NQ with anaerobic lifestyle. We engineered an obligate NQ-dependent γ-proteobacterium, Escherichia coli ΔubiC, and performed adaptive laboratory evolution to understand the selection against the use of NQ in an oxic environment and also the adaptation required to support the NQ-driven aerobic electron transport chain. A comparative systems-level analysis of pre- and postevolved NQ-dependent strains revealed a clear shift from fermentative to oxidative metabolism enabled by higher periplasmic superoxide defense. This metabolic shift was driven by the concerted activity of 3 transcriptional regulators (PdhR, RpoS, and Fur). Analysis of these findings using a genome-scale model suggested that resource allocation to reactive oxygen species (ROS) mitigation results in lower growth rates. These results provide a direct elucidation of a resource allocation tradeoff between growth rate and ROS mitigation costs associated with NQ usage under oxygen-replete condition.

ALEdb 1.0: a database of mutations from adaptive laboratory evolution experimentation.

Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover causal mutations that confer desired phenotypic functions. ALE not only represents a controllable experimental approach to systematically discover genotype-phenotype relationships, but also allows for the revelation of the series of genetic alterations required to acquire the new phenotype. Numerous ALE studies have been published, providing a strong impetus for developing databases to warehouse experimental evolution information and make it retrievable for large-scale analysis. Here, the first step towards establishing this resource is presented: ALEdb (http://aledb.org). This initial release contains over 11 000 mutations that have been discovered from eleven ALE publications. ALEdb (i) is a web-based platform that comprehensively reports on ALE acquired mutations and their conditions, (ii) reports key mutations using previously established trends, (iii) enables a search-driven workflow to enhance user mutation functional analysis through mutation cross-reference, (iv) allows exporting of mutation query results for custom analysis, (v) includes a bibliome describing the databased experiment publications and (vi) contains experimental evolution mutations from multiple model organisms. Thus, ALEdb is an informative platform which will become increasingly revealing as the number of reported ALE experiments and identified mutations continue to expand.

Restructuring of nutrient flows in island ecosystems following human colonization evidenced by isotopic analysis of commensal rats.

The role of humans in shaping local ecosystems is an increasing focus of archaeological research, yet researchers often lack an appropriate means of measuring past anthropogenic effects on local food webs and nutrient cycling. Stable isotope analysis of commensal animals provides an effective proxy for local human environments because these species are closely associated with human activities without being under direct human management. Such species are thus central to nutrient flows across a range of socionatural environments and can provide insight into how they intersected and transformed over time. Here we measure and compare stable carbon and nitrogen isotope data from Pacific rat (Rattus exulans) skeletal remains across three Polynesian island systems [Mangareva, Ua Huka (Marquesas), and the Polynesian Outlier of Tikopia] during one of the most significant cases of human migration and commensal introduction in prehistory. The results demonstrate widespread δ15N declines across these islands that are associated with human land use, intensification, and faunal community restructuring. Local comparison of rat stable isotope data also tracks human activities and resource availability at the level of the settlement. Our results highlight the large-scale restructuring of nutrient flows in island ecosystems that resulted from human colonization and ecosystem engineering activities on Pacific islands. They also demonstrate that stable isotope analysis of often-ignored commensal taxa can provide a tool for tracking human land use and environmental effects.

Augmented Spring Ligament Repair in Pes Planovalgus Reconstruction.

Patients with pes planovalgus deformity often have coexisting spring ligament pathology. A primary repair of the ligament may fail during weightbearing due to chronic degeneration of the ligamentous tissue. Augmentation with a suture tape has been suggested to strengthen the repair. Limited data exist regarding flatfoot reconstruction with augmented spring ligament repair using a suture tape. This is a review of 57 consecutive patients who had flatfoot reconstruction with concomitant spring ligament augmented repair between July 2014 and August 2017. Weightbearing radiographic parameters were obtained preoperatively and compared to radiographs at an average time of 62 ± 46.5 (range 20-220) weeks postoperative. Significant improvements were seen in the radiographic parameters evaluated. Five patients had subsequent operations including one deep infection, 2 hardware removals remote to the spring ligament augmentation, 1 ankle arthrodesis, and 1 triple arthrodesis. Concomitant spring ligament repair augmented with a suture tape was a safe procedure that contributed to radiographic correction in a consecutive series of 57 patients undergoing flatfoot deformity correction.

Causal mutations from adaptive laboratory evolution are outlined by multiple scales of genome annotations and condition-specificity.

BACKGROUND: Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover mutations that confer phenotypic functions of interest. However, the task of finding and understanding all beneficial mutations of an ALE experiment remains an open challenge for the field. To provide for better results than traditional methods of ALE mutation analysis, this work applied enrichment methods to mutations described by a multiscale annotation framework and a consolidated set of ALE experiment conditions. A total of 25,321 unique genome annotations from various sources were leveraged to describe multiple scales of mutated features in a set of 35 Escherichia coli based ALE experiments. These experiments totalled 208 independent evolutions and 2641 mutations. Additionally, mutated features were statistically associated across a total of 43 unique experimental conditions to aid in deconvoluting mutation selection pressures. RESULTS: Identifying potentially beneficial, or key, mutations was enhanced by seeking coding and non-coding genome features significantly enriched by mutations across multiple ALE replicates and scales of genome annotations. The median proportion of ALE experiment key mutations increased from 62%, with only small coding and non-coding features, to 71% with larger aggregate features. Understanding key mutations was enhanced by considering the functions of broader annotation types and the significantly associated conditions for key mutated features. The approaches developed here were used to find and characterize novel key mutations in two ALE experiments: one previously unpublished with Escherichia coli grown on glycerol as a carbon source and one previously published with Escherichia coli tolerized to high concentrations of L-serine. CONCLUSIONS: The emergent adaptive strategies represented by sets of ALE mutations became more clear upon observing the aggregation of mutated features across small to large scale genome annotations. The clarification of mutation selection pressures among the many experimental conditions also helped bring these strategies to light. This work demonstrates how multiscale genome annotation frameworks and data-driven methods can help better characterize ALE mutations, and thus help elucidate the genotype-to-phenotype relationship of the studied organism.

Acceptance and commitment therapy for breast cancer survivors with fear of cancer recurrence: A 3-arm pilot randomized controlled trial.

BACKGROUND: Fear of cancer recurrence (FCR) has a profound negative impact on quality of life (QOL) for many cancer survivors. Breast cancer survivors (BCS) are particularly vulnerable, with up to 70% reporting clinically significant FCR. To the authors' knowledge, evidence-based interventions for managing FCR are limited. Acceptance and commitment therapy (ACT) promotes psychological flexibility in managing life's stressors. The current study examined the feasibility and preliminary efficacy of group-based ACT for FCR in BCS. METHODS: Post-treatment BCS (91 patients with stage I-III disease) with clinical FCR randomly were assigned to ACT (6 weekly 2-hour group sessions), survivorship education (SE; 6 weekly 2-hour group sessions), or enhanced usual care (EUC; one 30-minute group coaching session with survivorship readings). FCR severity (primary outcome) and avoidant coping, anxiety, post-traumatic stress, depression, QOL, and other FCR-related variables (secondary outcomes) were assessed at baseline (T1), after the intervention (T2), 1 month after the intervention (T3), and 6 months after the intervention (T4) using intent-to-treat analysis. RESULTS: Satisfactory recruitment (43.8%) and retention (94.5%) rates demonstrated feasibility. Although each arm demonstrated within-group reductions in FCR severity over time, only ACT produced significant reductions at each time point compared with baseline, with between-group differences at T4 substantially favoring ACT over SE (Cohen d for effect sizes, 0.80; P < .001) and EUC (Cohen d, 0.61; P < .01). For 10 of 12 secondary outcomes, only ACT produced significant within-group reductions across all time points. By T4, significant moderate to large between-group comparisons favored ACT over SE and EUC with regard to avoidant coping, anxiety, depression, QOL, and FCR-related psychological distress. CONCLUSIONS: Group-based ACT is a feasible and promising treatment for FCR and associated outcomes in BCS that warrants testing in larger, fully powered trials.

Adaptive laboratory evolution of Escherichia coli under acid stress.

The ability of Escherichia coli to tolerate acid stress is important for its survival and colonization in the human digestive tract. Here, we performed adaptive laboratory evolution of the laboratory strain E. coli K-12 MG1655 at pH 5.5 in glucose minimal medium. After 800 generations, six independent populations under evolution had reached 18.0 % higher growth rates than their starting strain at pH 5.5, while maintaining comparable growth rates to the starting strain at pH 7. We characterized the evolved strains and found that: (1) whole genome sequencing of isolated clones from each evolved population revealed mutations in rpoC appearing in five of six sequenced clones; and (2) gene expression profiles revealed different strategies to mitigate acid stress, which are related to amino acid metabolism and energy production and conversion. Thus, a combination of adaptive laboratory evolution, genome resequencing and expression profiling revealed, on a genome scale, the strategies that E. coli uses to mitigate acid stress.

A Bayesian framework for high-throughput T cell receptor pairing.

MOTIVATION: The study of T cell receptor (TCR) repertoires has generated new insights into immune system recognition. However, the ability to robustly characterize these populations has been limited by technical barriers and an inability to reliably infer heterodimeric chain pairings for TCRs. RESULTS: Here, we describe a novel analytical approach to an emerging immune repertoire sequencing method, improving the resolving power of this low-cost technology. This method relies upon the distribution of a T cell population across a 96-well plate, followed by barcoding and sequencing of the relevant transcripts from each T cell. Multicell Analytical Deconvolution for High Yield Paired-chain Evaluation (MAD-HYPE) uses Bayesian inference to more accurately extract TCR information, improving our ability to study and characterize T cell populations for immunology and immunotherapy applications. AVAILABILITY AND IMPLEMENTATION: The MAD-HYPE algorithm is released as an open-source project under the Apache License and is available from https://github.com/birnbaumlab/MAD-HYPE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The genetic basis for adaptation of model-designed syntrophic co-cultures.

Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains-with diverse metabolic deficiencies-were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities.