@article{Bernstein2023,

title = {Evaluating \textit{E. coli} genome‐scale metabolic model accuracy with high‐throughput mutant fitness data},

author = {David B Bernstein and Batu Akkas and Morgan N Price and Adam P Arkin},

doi = {10.15252/msb.202311566},

issn = {1744-4292},

year  = {2023},

date = {2023-12-06},

journal = {Molecular Systems Biology},

volume = {19},

number = {12},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractThe Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.},

keywords = {Applied Mathematics, Computational Theory and Mathematics, General Agricultural and Biological Sciences, General Biochemistry, General Immunology and Microbiology, Genetics and Molecular Biology, Information Systems},

pubstate = {published},

tppubtype = {article}

}

@article{Piya2023,

title = {Systematic and scalable genome-wide essentiality mapping to identify nonessential genes in phages},

author = {Denish Piya and Nicholas Nolan and Madeline L. Moore and Luis A. Ramirez Hernandez and Brady F. Cress and Ry Young and Adam P. Arkin and Vivek K. Mutalik},

editor = {Paula Jauregui},

doi = {10.1371/journal.pbio.3002416},

issn = {1545-7885},

year  = {2023},

date = {2023-12-04},

journal = {PLoS Biol},

volume = {21},

number = {12},

publisher = {Public Library of Science (PLoS)},

abstract = {Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage–host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications.},

keywords = {General Agricultural and Biological Sciences, General Biochemistry, General Immunology and Microbiology, General Neuroscience, Genetics and Molecular Biology},

pubstate = {published},

tppubtype = {article}

}

@article{Ascensao2023,

title = {Quantifying the local adaptive landscape of a nascent bacterial community},

author = {Joao A. Ascensao and Kelly M. Wetmore and Benjamin H. Good and Adam P. Arkin and Oskar Hallatschek},

doi = {10.1038/s41467-022-35677-5},

issn = {2041-1723},

year  = {2023},

date = {2023-12-00},

journal = {Nat Commun},

volume = {14},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractThe fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.},

keywords = {General Biochemistry, General Chemistry, General Physics and Astronomy, Genetics and Molecular Biology, Multidisciplinary},

pubstate = {published},

tppubtype = {article}

}

@article{Averesch2023,

title = {Microbial biomanufacturing for space-exploration—what to take and when to make},

author = {Nils J. H. Averesch and Aaron J. Berliner and Shannon N. Nangle and Spencer Zezulka and Gretchen L. Vengerova and Davian Ho and Cameran A. Casale and Benjamin A. E. Lehner and Jessica E. Snyder and Kevin B. Clark and Lewis R. Dartnell and Craig S. Criddle and Adam P. Arkin},

doi = {10.1038/s41467-023-37910-1},

issn = {2041-1723},

year  = {2023},

date = {2023-12-00},

journal = {Nat Commun},

volume = {14},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractAs renewed interest in human space-exploration intensifies, a coherent and modernized strategy for mission design and planning has become increasingly crucial. Biotechnology has emerged as a promising approach to increase resilience, flexibility, and efficiency of missions, by virtue of its ability to effectively utilize in situ resources and reclaim resources from waste streams. Here we outline four primary mission-classes on Moon and Mars that drive a staged and accretive biomanufacturing strategy. Each class requires a unique approach to integrate biomanufacturing into the existing mission-architecture and so faces unique challenges in technology development. These challenges stem directly from the resources available in a given mission-class—the degree to which feedstocks are derived from cargo and in situ resources—and the degree to which loop-closure is necessary. As mission duration and distance from Earth increase, the benefits of specialized, sustainable biomanufacturing processes also increase. Consequentially, we define specific design-scenarios and quantify the usefulness of in-space biomanufacturing, to guide techno-economics of space-missions. Especially materials emerged as a potentially pivotal target for biomanufacturing with large impact on up-mass cost. Subsequently, we outline the processes needed for development, testing, and deployment of requisite technologies. As space-related technology development often does, these advancements are likely to have profound implications for the creation of a resilient circular bioeconomy on Earth.},

keywords = {cubes, General Biochemistry, General Chemistry, General Physics and Astronomy, Genetics and Molecular Biology, Multidisciplinary},

pubstate = {published},

tppubtype = {article}

}

@article{Chivian2022,

title = {Metagenome-assembled genome extraction and analysis from microbiomes using KBase},

author = {Dylan Chivian and Sean P. Jungbluth and Paramvir S. Dehal and Elisha M. Wood-Charlson and Richard S. Canon and Benjamin H. Allen and Mikayla M. Clark and Tianhao Gu and Miriam L. Land and Gavin A. Price and William J. Riehl and Michael W. Sneddon and Roman Sutormin and Qizhi Zhang and Robert W. Cottingham and Chris S. Henry and Adam P. Arkin},

doi = {10.1038/s41596-022-00747-x},

issn = {1750-2799},

year  = {2023},

date = {2023-01-00},

journal = {Nat Protoc},

volume = {18},

number = {1},

pages = {208--238},

publisher = {Springer Science and Business Media LLC},

keywords = {General Biochemistry, Genetics and Molecular Biology},

pubstate = {published},

tppubtype = {article}

}

@article{Chivian2022b,

title = {Publisher Correction: Metagenome-assembled genome extraction and analysis from microbiomes using KBase},

author = {Dylan Chivian and Sean P. Jungbluth and Paramvir S. Dehal and Elisha M. Wood-Charlson and Richard S. Canon and Benjamin H. Allen and Mikayla M. Clark and Tianhao Gu and Miriam L. Land and Gavin A. Price and William J. Riehl and Michael W. Sneddon and Roman Sutormin and Qizhi Zhang and Robert W. Cottingham and Chris S. Henry and Adam P. Arkin},

doi = {10.1038/s41596-022-00794-4},

issn = {1750-2799},

year  = {2022},

date = {2022-11-30},

journal = {Nat Protoc},

publisher = {Springer Science and Business Media LLC},

keywords = {General Biochemistry, Genetics and Molecular Biology},

pubstate = {published},

tppubtype = {article}

}

@article{Liu2021,

title = {Functional genetics of human gut commensal Bacteroides thetaiotaomicron reveals metabolic requirements for growth across environments},

author = {Hualan Liu and Anthony L. Shiver and Morgan N. Price and Hans K. Carlson and Valentine V. Trotter and Yan Chen and Veronica Escalante and Jayashree Ray and Kelsey E. Hern and Christopher J. Petzold and Peter J. Turnbaugh and Kerwyn Casey Huang and Adam P. Arkin and Adam M. Deutschbauer},

doi = {10.1016/j.celrep.2021.108789},

issn = {2211-1247},

year  = {2021},

date = {2021-03-00},

journal = {Cell Reports},

volume = {34},

number = {9},

publisher = {Elsevier BV},

keywords = {General Biochemistry, Genetics and Molecular Biology},

pubstate = {published},

tppubtype = {article}

}

@article{Qi2021,

title = {Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression},

author = {Lei S. Qi and Matthew H. Larson and Luke A. Gilbert and Jennifer A. Doudna and Jonathan S. Weissman and Adam P. Arkin and Wendell A. Lim},

doi = {10.1016/j.cell.2021.01.019},

issn = {0092-8674},

year  = {2021},

date = {2021-02-00},

journal = {Cell},

volume = {184},

number = {3},

publisher = {Elsevier BV},

keywords = {General Biochemistry, Genetics and Molecular Biology},

pubstate = {published},

tppubtype = {article}

}