@article{Ning2024,

title = {Environmental stress mediates groundwater microbial community assembly},

author = {Daliang Ning and Yajiao Wang and Yupeng Fan and Jianjun Wang and Joy D. Van Nostrand and Liyou Wu and Ping Zhang and Daniel J. Curtis and Renmao Tian and Lauren Lui and Terry C. Hazen and Eric J. Alm and Matthew W. Fields and Farris Poole and Michael W. W. Adams and Romy Chakraborty and David A. Stahl and Paul D. Adams and Adam P. Arkin and Zhili He and Jizhong Zhou},

doi = {10.1038/s41564-023-01573-x},

issn = {2058-5276},

year  = {2024},

date = {2024-02-00},

urldate = {2024-02-00},

journal = {Nat Microbiol},

volume = {9},

number = {2},

pages = {490--501},

publisher = {Springer Science and Business Media LLC},

keywords = {Applied Microbiology and Biotechnology, Cell Biology, enigma, Genetics, Immunology, Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}

@article{Park2023b,

title = {A bacterial sensor taxonomy across earth ecosystems for machine learning applications},

author = {Helen Park and Marcin P. Joachimiak and Sean P. Jungbluth and Ziming Yang and William J. Riehl and R. Shane Canon and Adam P. Arkin and Paramvir S. Dehal},

editor = {Babak Momeni},

doi = {10.1128/msystems.00026-23},

issn = {2379-5077},

year  = {2023},

date = {2023-12-11},

urldate = {2023-12-11},

journal = {mSystems},

publisher = {American Society for Microbiology},

abstract = {<jats:title>ABSTRACT</jats:title>

          <jats:p>

            Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from

            <jats:italic>Host-associated</jats:italic>

            ,

            <jats:italic>Environmental</jats:italic>

            , and

            <jats:italic>Engineered</jats:italic>

            ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

          </jats:p>

          <jats:sec>

            <jats:title>IMPORTANCE</jats:title>

            <jats:p>Microbes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model’s feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.</jats:p>

          </jats:sec>},

keywords = {Behavior and Systematics, Biochemistry, Computer Science Applications, Ecology, Evolution, Genetics, kbase, Microbiology, Modeling and Simulation, Molecular Biology, Physiology},

pubstate = {published},

tppubtype = {article}

}

@article{Trotter2023,

title = {Large-scale genetic characterization of the model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough},

author = {Valentine V. Trotter and Maxim Shatsky and Morgan N. Price and Thomas R. Juba and Grant M. Zane and Kara B. De León and Erica L.-W. Majumder and Qin Gui and Rida Ali and Kelly M. Wetmore and Jennifer V. Kuehl and Adam P. Arkin and Judy D. Wall and Adam M. Deutschbauer and John-Marc Chandonia and Gareth P. Butland},

doi = {10.3389/fmicb.2023.1095191},

issn = {1664-302X},

year  = {2023},

date = {2023-03-31},

journal = {Front. Microbiol.},

volume = {14},

publisher = {Frontiers Media SA},

abstract = {Sulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.},

keywords = {Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}

@article{Price2022,

title = {Interactive Analysis of Functional Residues in Protein Families},

author = {Morgan N. Price and Adam P. Arkin},

editor = {Marnix Medema},

doi = {10.1128/msystems.00705-22},

issn = {2379-5077},

year  = {2022},

date = {2022-12-20},

journal = {mSystems},

volume = {7},

number = {6},

publisher = {American Society for Microbiology},

abstract = {For most microbes of interest, a genome sequence is available, but the function of its proteins is not known. Instead, proteins' functions are predicted from their similarity to other protein sequences.},

keywords = {Behavior and Systematics, Biochemistry, Computer Science Applications, Ecology, Evolution, Genetics, Microbiology, Modeling and Simulation, Molecular Biology, Physiology},

pubstate = {published},

tppubtype = {article}

}

@article{Goff2022b,

title = {Ecophysiological and genomic analyses of a representative isolate of highly abundant \textit{Bacillus cereus} strains in contaminated subsurface sediments},

author = {Jennifer L. Goff and Elizabeth G. Szink and Michael P. Thorgersen and Andrew D. Putt and Yupeng Fan and Lauren M. Lui and Torben N. Nielsen and Kristopher A. Hunt and Jonathan P. Michael and Yajiao Wang and Daliang Ning and Ying Fu and Joy D. Van Nostrand and Farris L. Poole and John‐Marc Chandonia and Terry C. Hazen and David A. Stahl and Jizhong Zhou and Adam P. Arkin and Michael W. W. Adams},

doi = {10.1111/1462-2920.16173},

issn = {1462-2920},

year  = {2022},

date = {2022-11-00},

journal = {Environmental Microbiology},

volume = {24},

number = {11},

pages = {5546--5560},

publisher = {Wiley},

abstract = {AbstractBacillus cereus strain CPT56D‐587‐MTF (CPTF) was isolated from the highly contaminated Oak Ridge Reservation (ORR) subsurface. This site is contaminated with high levels of nitric acid and multiple heavy metals. Amplicon sequencing of the 16S rRNA genes (V4 region) in sediment from this area revealed an amplicon sequence variant (ASV) with 100% identity to the CPTF 16S rRNA sequence. Notably, this CPTF‐matching ASV had the highest relative abundance in this community survey, with a median relative abundance of 3.77% and comprised 20%–40% of reads in some samples. Pangenomic analysis revealed that strain CPTF has expanded genomic content compared to other B. cereus species—largely due to plasmid acquisition and expansion of transposable elements. This suggests that these features are important for rapid adaptation to native environmental stressors. We connected genotype to phenotype in the context of the unique geochemistry of the site. These analyses revealed that certain genes (e.g. nitrate reductase, heavy metal efflux pumps) that allow this strain to successfully occupy the geochemically heterogenous microniches of its native site are characteristic of the B. cereus species while others such as acid tolerance are mobile genetic element associated and are generally unique to strain CPTF.},

keywords = {Behavior and Systematics, Ecology, Evolution, Microbiology},

pubstate = {published},

tppubtype = {article}

}

@article{deRaad2022,

title = {A Defined Medium for Cultivation and Exometabolite Profiling of Soil Bacteria},

author = {Markus de Raad and Yifan V. Li and Jennifer V. Kuehl and Peter F. Andeer and Suzanne M. Kosina and Andrew Hendrickson and Nicholas R. Saichek and Amber N. Golini and La Zhen Han and Ying Wang and Benjamin P. Bowen and Adam M. Deutschbauer and Adam P. Arkin and Romy Chakraborty and Trent R. Northen},

doi = {10.3389/fmicb.2022.855331},

issn = {1664-302X},

year  = {2022},

date = {2022-05-25},

journal = {Front. Microbiol.},

volume = {13},

publisher = {Frontiers Media SA},

abstract = {Exometabolomics is an approach to assess how microorganisms alter, or react to their environments through the depletion and production of metabolites. It allows the examination of how soil microbes transform the small molecule metabolites within their environment, which can be used to study resource competition and cross-feeding. This approach is most powerful when used with defined media that enable tracking of all metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS). Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse soil bacteria but also is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 108 of the 110 phylogenetically diverse (spanning 36 different families) soil bacterial isolates tested and all of its metabolites were trackable through LC–MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for growing and characterizing diverse microbial isolates and communities.},

keywords = {Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}

@article{McCausland2022,

title = {Global Analysis of Biomineralization Genes in

            \textit{Magnetospirillum magneticum}

            AMB-1},

author = {Hayley C. McCausland and Kelly M. Wetmore and Adam P. Arkin and Arash Komeili},

editor = {Sarah Glaven},

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

issn = {2379-5077},

year  = {2022},

date = {2022-02-22},

journal = {mSystems},

volume = {7},

number = {1},

publisher = {American Society for Microbiology},

abstract = {Magnetotactic bacteria (MTB) are a group of bacteria that can form nano-sized crystals of magnetic minerals. MTB are likely an important part of their ecosystems, because they can account for up to a third of the microbial biomass in an aquatic habitat and consume large amounts of iron, potentially impacting the iron cycle.},

keywords = {Behavior and Systematics, Biochemistry, Computer Science Applications, Ecology, Evolution, Genetics, Microbiology, Modeling and Simulation, Molecular Biology, Physiology},

pubstate = {published},

tppubtype = {article}

}

@article{Kosina2021,

title = {Biofilm Interaction Mapping and Analysis (BIMA) of Interspecific Interactions in Pseudomonas Co-culture Biofilms},

author = {Suzanne M. Kosina and Peter Rademacher and Kelly M. Wetmore and Markus de Raad and Marcin Zemla and Grant M. Zane and Jennifer J. Zulovich and Romy Chakraborty and Benjamin P. Bowen and Judy D. Wall and Manfred Auer and Adam P. Arkin and Adam M. Deutschbauer and Trent R. Northen},

doi = {10.3389/fmicb.2021.757856},

issn = {1664-302X},

year  = {2021},

date = {2021-12-09},

journal = {Front. Microbiol.},

volume = {12},

publisher = {Frontiers Media SA},

abstract = {Pseudomonas species are ubiquitous in nature and include numerous medically, agriculturally and technologically beneficial strains of which the interspecific interactions are of great interest for biotechnologies. Specifically, co-cultures containing Pseudomonas stutzeri have been used for bioremediation, biocontrol, aquaculture management and wastewater denitrification. Furthermore, the use of P. stutzeri biofilms, in combination with consortia-based approaches, may offer advantages for these processes. Understanding the interspecific interaction within biofilm co-cultures or consortia provides a means for improvement of current technologies. However, the investigation of biofilm-based consortia has been limited. We present an adaptable and scalable method for the analysis of macroscopic interactions (colony morphology, inhibition, and invasion) between colony-forming bacterial strains using an automated printing method followed by analysis of the genes and metabolites involved in the interactions. Using Biofilm Interaction Mapping and Analysis (BIMA), these interactions were investigated between P. stutzeri strain RCH2, a denitrifier isolated from chromium (VI) contaminated soil, and 13 other species of pseudomonas isolated from non-contaminated soil. One interaction partner, Pseudomonas fluorescens N1B4 was selected for mutant fitness profiling of a DNA-barcoded mutant library; with this approach four genes of importance were identified and the effects on interactions were evaluated with deletion mutants and mass spectrometry based metabolomics.},

keywords = {Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}

@article{Adler2021,

title = {The genetic basis of phage susceptibility, cross-resistance and host-range in Salmonella},

author = {Benjamin A. Adler and Alexey E. Kazakov and Crystal Zhong and Hualan Liu and Elizabeth Kutter and Lauren M. Lui and Torben N. Nielsen and Heloise Carion and Adam M. Deutschbauer and Vivek K. Mutalik and Adam P. Arkin},

doi = {10.1099/mic.0.001126},

issn = {1465-2080},

year  = {2021},

date = {2021-12-01},

volume = {167},

number = {12},

publisher = {Microbiology Society},

abstract = {Though bacteriophages (phages) are known to play a crucial role in bacterial fitness and virulence, our knowledge about the genetic basis of their interaction, cross-resistance and host-range is sparse. Here, we employed genome-wide screens in 

                     

                        Salmonella enterica

                     

                   serovar Typhimurium to discover host determinants involved in resistance to eleven diverse lytic phages including four new phages isolated from a therapeutic phage cocktail. We uncovered 301 diverse host factors essential in phage infection, many of which are shared between multiple phages demonstrating potential cross-resistance mechanisms. We validate many of these novel findings and uncover the intricate interplay between RpoS, the virulence-associated general stress response sigma factor and RpoN, the nitrogen starvation sigma factor in phage cross-resistance. Finally, the infectivity pattern of eleven phages across a panel of 23 genome sequenced 

                     

                        Salmonella

                     

                   strains indicates that additional constraints and interactions beyond the host factors uncovered here define the phage host range.},

keywords = {Microbiology},

pubstate = {published},

tppubtype = {article}

}

@article{McNulty2021b,

title = {Evaluating the Cost of Pharmaceutical Purification for a Long-Duration Space Exploration Medical Foundry},

author = {Matthew J. McNulty and Aaron J. Berliner and Patrick G. Negulescu and Liber McKee and Olivia Hart and Kevin Yates and Adam P. Arkin and Somen Nandi and Karen A. McDonald},

doi = {10.3389/fmicb.2021.700863},

issn = {1664-302X},

year  = {2021},

date = {2021-10-11},

journal = {Front. Microbiol.},

volume = {12},

publisher = {Frontiers Media SA},

abstract = {There are medical treatment vulnerabilities in longer-duration space missions present in the current International Space Station crew health care system with risks, arising from spaceflight-accelerated pharmaceutical degradation and resupply lag times. Bioregenerative life support systems may be a way to close this risk gap by leveraging in situ resource utilization (ISRU) to perform pharmaceutical synthesis and purification. Recent literature has begun to consider biological ISRU using microbes and plants as the basis for pharmaceutical life support technologies. However, there has not yet been a rigorous analysis of the processing and quality systems required to implement biologically produced pharmaceuticals for human medical treatment. In this work, we use the equivalent system mass (ESM) metric to evaluate pharmaceutical purification processing strategies for longer-duration space exploration missions. Monoclonal antibodies, representing a diverse therapeutic platform capable of treating multiple space-relevant disease states, were selected as the target products for this analysis. We investigate the ESM resource costs (mass, volume, power, cooling, and crew time) of an affinity-based capture step for monoclonal antibody purification as a test case within a manned Mars mission architecture. We compare six technologies (three biotic capture methods and three abiotic capture methods), optimize scheduling to minimize ESM for each technology, and perform scenario analysis to consider a range of input stream compositions and pharmaceutical demand. We also compare the base case ESM to scenarios of alternative mission configuration, equipment models, and technology reusability. Throughout the analyses, we identify key areas for development of pharmaceutical life support technology and improvement of the ESM framework for assessment of bioregenerative life support technologies.},

keywords = {Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}

@article{Cestellos-Blanco2021,

title = {Production of PHB From CO2-Derived Acetate With Minimal Processing Assessed for Space Biomanufacturing},

author = {Stefano Cestellos-Blanco and Skyler Friedline and Kyle B. Sander and Anthony J. Abel and Ji Min Kim and Douglas S. Clark and Adam P. Arkin and Peidong Yang},

doi = {10.3389/fmicb.2021.700010},

issn = {1664-302X},

year  = {2021},

date = {2021-07-28},

journal = {Front. Microbiol.},

volume = {12},

publisher = {Frontiers Media SA},

abstract = {Providing life-support materials to crewed space exploration missions is pivotal for mission success. However, as missions become more distant and extensive, obtaining these materials from in situ resource utilization is paramount. The combination of microorganisms with electrochemical technologies offers a platform for the production of critical chemicals and materials from CO2 and H2O, two compounds accessible on a target destination like Mars. One such potential commodity is poly(3-hydroxybutyrate) (PHB), a common biopolyester targeted for additive manufacturing of durable goods. Here, we present an integrated two-module process for the production of PHB from CO2. An autotrophic Sporomusa ovata (S. ovata) process converts CO2 to acetate which is then directly used as the primary carbon source for aerobic PHB production by Cupriavidus basilensis (C. basilensis). The S. ovata uses H2 as a reducing equivalent to be generated through electrocatalytic solar-driven H2O reduction. Conserving and recycling media components is critical, therefore we have designed and optimized our process to require no purification or filtering of the cell culture media between microbial production steps which could result in up to 98% weight savings. By inspecting cell population dynamics during culturing we determined that C. basilensis suitably proliferates in the presence of inactive S. ovata. During the bioprocess 10.4 mmol acetate L –1 day–1 were generated from CO2 by S. ovata in the optimized media. Subsequently, 12.54 mg PHB L–1 hour–1 were produced by C. basilensis in the unprocessed media with an overall carbon yield of 11.06% from acetate. In order to illustrate a pathway to increase overall productivity and enable scaling of our bench-top process, we developed a model indicating key process parameters to optimize.},

keywords = {Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}

@article{Kothari2021,

title = {Ecogenomics of Groundwater Phages Suggests Niche Differentiation Linked to Specific Environmental Tolerance},

author = {Ankita Kothari and Simon Roux and Hanqiao Zhang and Anatori Prieto and Drishti Soneja and John-Marc Chandonia and Sarah Spencer and Xiaoqin Wu and Sara Altenburg and Matthew W. Fields and Adam M. Deutschbauer and Adam P. Arkin and Eric J. Alm and Romy Chakraborty and Aindrila Mukhopadhyay},

editor = {Ileana M. Cristea},

doi = {10.1128/msystems.00537-21},

issn = {2379-5077},

year  = {2021},

date = {2021-06-29},

urldate = {2021-06-29},

journal = {mSystems},

volume = {6},

number = {3},

publisher = {American Society for Microbiology},

abstract = {<jats:p>To our knowledge, this is the first study to identify the bacteriophage distribution in a groundwater ecosystem shedding light on their prevalence and distribution across metal-contaminated and background sites. Our study is uniquely based on selective sequencing of solely the extrachromosomal elements of a microbiome followed by analysis for viral signatures, thus establishing a more focused approach for phage identifications.</jats:p>},

keywords = {Behavior and Systematics, Biochemistry, biodesign, Computer Science Applications, Ecology, Evolution, Genetics, Microbiology, Modeling and Simulation, Molecular Biology, Physiology},

pubstate = {published},

tppubtype = {article}

}

@article{Lui2021,

title = {Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology},

author = {Lauren M. Lui and Erica L.-W. Majumder and Heidi J. Smith and Hans K. Carlson and Frederick von Netzer and Matthew W. Fields and David A. Stahl and Jizhong Zhou and Terry C. Hazen and Nitin S. Baliga and Paul D. Adams and Adam P. Arkin},

doi = {10.3389/fmicb.2021.642422},

issn = {1664-302X},

year  = {2021},

date = {2021-03-24},

journal = {Front. Microbiol.},

volume = {12},

publisher = {Frontiers Media SA},

abstract = {Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.},

keywords = {Microbiology, Microbiology (medical)},

pubstate = {published},

tppubtype = {article}

}