@article{Sander2023b,

title = {Eliminating genes for a two‐component system increases PHB productivity in \textit{Cupriavidus basilensis} 4G11 under PHB suppressing, nonstress conditions},

author = {Kyle Sander and Anthony J. Abel and Skyler Friedline and William Sharpless and Jeffrey Skerker and Adam Deutschbauer and Douglas S. Clark and Adam P. Arkin},

doi = {10.1002/bit.28532},

issn = {1097-0290},

year  = {2024},

date = {2024-01-00},

urldate = {2024-01-00},

journal = {Biotech & Bioengineering},

volume = {121},

number = {1},

pages = {139--156},

publisher = {Wiley},

abstract = {<jats:title>Abstract</jats:title><jats:p>Species of bacteria from the genus <jats:italic>Cupriavidus</jats:italic> are known, in part, for their ability to produce high amounts of poly‐hydroxybutyrate (PHB) making them attractive candidates for bioplastic production. The native synthesis of PHB occurs during periods of metabolic stress, and the process regulating the initiation of PHB accumulation in these organisms is not fully understood. Screening an RB‐TnSeq transposon library of <jats:italic>Cupriavidus basilensis</jats:italic> 4G11 allowed us to identify two genes of an apparent, uncharacterized two‐component system, which when omitted from the genome enable increased PHB productivity in balanced, nonstress growth conditions. We observe average increases in PHB productivity of 56% and 41% relative to the wildtype parent strain upon deleting each gene individually from the genome. The increased PHB phenotype disappears, however, in nitrogen‐free unbalanced growth conditions suggesting the phenotype is specific to fast‐growing, replete, nonstress growth. Bioproduction modeling suggests this phenotype could be due to a decreased reliance on metabolic stress induced by nitrogen limitation to initiate PHB production in the mutant strains. Due to uncertainty in the two‐component system's input signal and regulon, the mechanism by which these genes impart this phenotype remains unclear. Such strains may allow for the use of single‐stage, continuous bioreactor systems, which are far simpler than many PHB bioproduction schemes used previously, given a similar product yield to batch systems in such a configuration. Bioproductivity modeling suggests that omitting this regulation in the cells may increase PHB productivity up to 24% relative to the wildtype organism when using single‐stage continuous systems. This work expands our understanding of the regulation of PHB accumulation in <jats:italic>Cupriavidus</jats:italic>, in particular the initiation of this process upon transition into unbalanced growth regimes.</jats:p>},

keywords = {Applied Microbiology and Biotechnology, Bioengineering, Biotechnology, cubes},

pubstate = {published},

tppubtype = {article}

}

@article{Adams2023,

title = {Engineering osmolysis susceptibility in Cupriavidus necator and Escherichia coli for recovery of intracellular products},

author = {Jeremy David Adams and Kyle B. Sander and Craig S. Criddle and Adam P. Arkin and Douglas S. Clark},

doi = {10.1186/s12934-023-02064-8},

issn = {1475-2859},

year  = {2023},

date = {2023-12-00},

journal = {Microb Cell Fact},

volume = {22},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {Abstract

                Background

                Intracellular biomacromolecules, such as industrial enzymes and biopolymers, represent an important class of bio-derived products obtained from bacterial hosts. A common key step in the downstream separation of these biomolecules is lysis of the bacterial cell wall to effect release of cytoplasmic contents. Cell lysis is typically achieved either through mechanical disruption or reagent-based methods, which introduce issues of energy demand, material needs, high costs, and scaling problems. Osmolysis, a cell lysis method that relies on hypoosmotic downshock upon resuspension of cells in distilled water, has been applied for bioseparation of intracellular products from extreme halophiles and mammalian cells. However, most industrial bacterial strains are non-halotolerant and relatively resistant to hypoosmotic cell lysis. 

              

                Results

                To overcome this limitation, we developed two strategies to increase the susceptibility of non-halotolerant hosts to osmolysis using Cupriavidus necator, a strain often used in electromicrobial production, as a prototypical strain. In one strategy, C. necator was evolved to increase its halotolerance from 1.5% to 3.25% (w/v) NaCl through adaptive laboratory evolution, and genes potentially responsible for this phenotypic change were identified by whole genome sequencing. The evolved halotolerant strain experienced an osmolytic efficiency of 47% in distilled water following growth in 3% (w/v) NaCl. In a second strategy, the cells were made susceptible to osmolysis by knocking out the large-conductance mechanosensitive channel (mscL) gene in C. necator. When these strategies were combined by knocking out the mscL gene from the evolved halotolerant strain, greater than 90% osmolytic efficiency was observed upon osmotic downshock. A modified version of this strategy was applied to E. coli BL21 by deleting the mscL and mscS (small-conductance mechanosensitive channel) genes. When grown in medium with 4% NaCl and subsequently resuspended in distilled water, this engineered strain experienced 75% cell lysis, although decreases in cell growth rate due to higher salt concentrations were observed.

              

                Conclusions

                Our strategy is shown to be a simple and effective way to lyse cells for the purification of intracellular biomacromolecules and may be applicable in many bacteria used for bioproduction.

              },

keywords = {Applied Microbiology and Biotechnology, Bioengineering, Biotechnology, cubes},

pubstate = {published},

tppubtype = {article}

}

@article{Wu2023,

title = {Distinct Depth-Discrete Profiles of Microbial Communities and Geochemical Insights in the Subsurface Critical Zone},

author = {Xiaoqin Wu and Sara Gushgari-Doyle and Lauren M. Lui and Andrew J. Hendrickson and Yina Liu and Sindhu Jagadamma and Torben N. Nielsen and Nicholas B. Justice and Tuesday Simmons and Nancy J. Hess and Dominique C. Joyner and Terry C. Hazen and Adam P. Arkin and Romy Chakraborty},

editor = {Jennifer B. Glass},

doi = {10.1128/aem.00500-23},

issn = {1098-5336},

year  = {2023},

date = {2023-06-28},

journal = {Appl Environ Microbiol},

volume = {89},

number = {6},

publisher = {American Society for Microbiology},

abstract = {In this study, we explored the links between geochemical parameters, microbial community structure and metabolic potential across the depth of sediment, including the shallow subsurface, vadose zone, capillary fringe, and saturated zone. Our results revealed that microbes in the terrestrial subsurface can be highly localized, with communities rarely being interconnected along the depth.},

keywords = {Applied Microbiology and Biotechnology, Biotechnology, Ecology, Food Science},

pubstate = {published},

tppubtype = {article}

}

@article{Makrygiorgos2023,

title = {Data‐driven flow‐map models for data‐efficient discovery of dynamics and fast uncertainty quantification of biological and biochemical systems},

author = {Georgios Makrygiorgos and Aaron J. Berliner and Fengzhe Shi and Douglas S. Clark and Adam P. Arkin and Ali Mesbah},

doi = {10.1002/bit.28295},

issn = {1097-0290},

year  = {2023},

date = {2023-03-00},

journal = {Biotech & Bioengineering},

volume = {120},

number = {3},

pages = {803--818},

publisher = {Wiley},

abstract = {AbstractComputational models are increasingly used to investigate and predict the complex dynamics of biological and biochemical systems. Nevertheless, governing equations of a biochemical system may not be (fully) known, which would necessitate learning the system dynamics directly from, often limited and noisy, observed data. On the other hand, when expensive models are available, systematic and efficient quantification of the effects of model uncertainties on quantities of interest can be an arduous task. This paper leverages the notion of flow‐map (de)compositions to present a framework that can address both of these challenges via learning data‐driven models useful for capturing the dynamical behavior of biochemical systems. Data‐driven flow‐map models seek to directly learn the integration operators of the governing differential equations in a black‐box manner, irrespective of structure of the underlying equations. As such, they can serve as a flexible approach for deriving fast‐to‐evaluate surrogates for expensive computational models of system dynamics, or, alternatively, for reconstructing the long‐term system dynamics via experimental observations. We present a data‐efficient approach to data‐driven flow‐map modeling based on polynomial chaos Kriging. The approach is demonstrated for discovery of the dynamics of various benchmark systems and a coculture bioreactor subject to external forcing, as well as for uncertainty quantification of a microbial electrosynthesis reactor. Such data‐driven models and analyses of dynamical systems can be paramount in the design and optimization of bioprocesses and integrated biomanufacturing systems.},

keywords = {Applied Microbiology and Biotechnology, Bioengineering, Biotechnology, cubes},

pubstate = {published},

tppubtype = {article}

}

@article{Tao2022,

title = {Development of a Markerless Deletion Mutagenesis System in Nitrate-Reducing Bacterium Rhodanobacter denitrificans},

author = {Xuanyu Tao and Aifen Zhou and Megan L. Kempher and Jiantao Liu and Mu Peng and Yuan Li and Jonathan P. Michael and Romy Chakraborty and Adam M. Deutschbauer and Adam P. Arkin and Jizhong Zhou},

editor = {Arpita Bose},

doi = {10.1128/aem.00401-22},

issn = {1098-5336},

year  = {2022},

date = {2022-07-26},

journal = {Appl Environ Microbiol},

volume = {88},

number = {14},

publisher = {American Society for Microbiology},

abstract = {

            Rhodanobacter denitrificans

            is capable of denitrification and is also resistant to toxic heavy metals and low pH. Accordingly, the presence of

            Rhodanobacter

            species at a particular environmental site is considered an indicator of nitrate and uranium contamination.

          },

keywords = {Applied Microbiology and Biotechnology, Biotechnology, Ecology, Food Science},

pubstate = {published},

tppubtype = {article}

}

@article{Thorgersen2021,

title = {Deciphering Microbial Metal Toxicity Responses via Random Bar Code Transposon Site Sequencing and Activity-Based Metabolomics},

author = {Michael P. Thorgersen and Jingchuan Xue and Erica L. W. Majumder and Valentine V. Trotter and Xiaoxuan Ge and Farris L. Poole and Trenton K. Owens and Lauren M. Lui and Torben N. Nielsen and Adam P. Arkin and Adam M. Deutschbauer and Gary Siuzdak and Michael W. W. Adams},

editor = {Rebecca E. Parales},

doi = {10.1128/aem.01037-21},

issn = {1098-5336},

year  = {2021},

date = {2021-10-14},

journal = {Appl Environ Microbiol},

volume = {87},

number = {21},

publisher = {American Society for Microbiology},

abstract = {

            Studying microbial interactions with their environment can lead to a deeper understanding of biological molecular mechanisms. In the manuscript, two global techniques, RB-TnSeq and activity metabolomics, were successfully used to probe the interactions between a metal-resistant microorganism,

            Pantoea

            sp. strain MT58, and metals contaminating a site where the organism can be located.

          },

keywords = {Applied Microbiology and Biotechnology, Biotechnology, Ecology, Food Science},

pubstate = {published},

tppubtype = {article}

}

@article{McNulty2021,

title = {Molecular pharming to support human life on the moon, mars, and beyond},

author = {Matthew J. McNulty and Yongao (Mary) Xiong and Kevin Yates and Kalimuthu Karuppanan and Jacob M. Hilzinger and Aaron J. Berliner and Jesse Delzio and Adam P. Arkin and Nancy E. Lane and Somen Nandi and Karen A. McDonald},

doi = {10.1080/07388551.2021.1888070},

issn = {1549-7801},

year  = {2021},

date = {2021-08-18},

journal = {Critical Reviews in Biotechnology},

volume = {41},

number = {6},

pages = {849--864},

publisher = {Informa UK Limited},

keywords = {Applied Microbiology and Biotechnology, Biotechnology, General Medicine},

pubstate = {published},

tppubtype = {article}

}