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1.  Physiological and Proteomic Analysis of Escherichia coli Iron-Limited Chemostat Growth 
Journal of Bacteriology  2014;196(15):2748-2761.
Iron bioavailability is a major limiter of bacterial growth in mammalian host tissue and thus represents an important area of study. Escherichia coli K-12 metabolism was studied at four levels of iron limitation in chemostats using physiological and proteomic analyses. The data documented an E. coli acclimation gradient where progressively more severe iron scarcity resulted in a larger percentage of substrate carbon being directed into an overflow metabolism accompanied by a decrease in biomass yield on glucose. Acetate was the primary secreted organic by-product for moderate levels of iron limitation, but as stress increased, the metabolism shifted to secrete primarily lactate (∼70% of catabolized glucose carbon). Proteomic analysis reinforced the physiological data and quantified relative increases in glycolysis enzyme abundance and decreases in tricarboxylic acid (TCA) cycle enzyme abundance with increasing iron limitation stress. The combined data indicated that E. coli responds to limiting iron by investing the scarce resource in essential enzymes, at the cost of catabolic efficiency (i.e., downregulating high-ATP-yielding pathways containing enzymes with large iron requirements, like the TCA cycle). Acclimation to iron-limited growth was contrasted experimentally with acclimation to glucose-limited growth to identify both general and nutrient-specific acclimation strategies. While the iron-limited cultures maximized biomass yields on iron and increased expression of iron acquisition strategies, the glucose-limited cultures maximized biomass yields on glucose and increased expression of carbon acquisition strategies. This study quantified ecologically competitive acclimations to nutrient limitations, yielding knowledge essential for understanding medically relevant bacterial responses to host and to developing intervention strategies.
doi:10.1128/JB.01606-14
PMCID: PMC4135680  PMID: 24837288
2.  Differentiation of Microbial Species and Strains in Coculture Biofilms by Multivariate Analysis of Laser Desorption Postionization Mass Spectra 
The Analyst  2013;138(22):6844-6851.
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.
doi:10.1039/c3an01389h
PMCID: PMC3833099  PMID: 24067765
3.  Laser Desorption VUV Postionization MS Imaging of a Cocultured Biofilm 
Analytical and bioanalytical chemistry  2012;405(22):6969-6977.
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, 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.
doi:10.1007/s00216-012-6454-0
PMCID: PMC3566334  PMID: 23052888
laser ablation; mass spectrometry; biological samples; bioanalytical methods; interface/surface analysis
4.  Quantitative NMR Metabolite Profiling of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus Discriminates between Biofilm and Planktonic Phenotypes 
Journal of proteome research  2014;13(6):2973-2985.
Wound bioburden in the form of colonizing biofilms is a major contributor to nonhealing wounds. Staphylococcus aureus is a Gram-positive, facultative anaerobe commonly found in chronic wounds; however, much remains unknown about the basic physiology of this opportunistic pathogen, especially with regard to the biofilm phenotype. Transcriptomic and proteomic analysis of S. aureus biofilms have suggested that S. aureus biofilms exhibit an altered metabolic state relative to the planktonic phenotype. Herein, comparisons of extracellular and intracellular metabolite profiles detected by 1H NMR were conducted for methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) S. aureus strains grown as biofilm and planktonic cultures. Principal component analysis distinguished the biofilm phenotype from the planktonic phenotype, and factor loadings analysis identified metabolites that contributed to the statistical separation of the biofilm from the planktonic phenotype, suggesting that key features distinguishing biofilm from planktonic growth include selective amino acid uptake, lipid catabolism, butanediol fermentation, and a shift in metabolism from energy production to assembly of cell-wall components and matrix deposition. These metabolite profiles provide a basis for the development of metabolite biomarkers that distinguish between biofilm and planktonic phenotypes in S. aureus and have the potential for improved diagnostic and therapeutic use in chronic wounds.
doi:10.1021/pr500120c
PMCID: PMC4059261  PMID: 24809402
Staphylococcus aureus; biofilm; NMR metabolomics
5.  Microbial Consortia Engineering for Cellular Factories: in vitro to in silico systems 
This mini-review discusses the current state of experimental and computational microbial consortia engineering with a focus on cellular factories. A discussion of promising ecological theories central to community resource usage is presented to facilitate interpretation of consortial designs. Recent case studies exemplifying different resource usage motifs and consortial assembly templates are presented. The review also highlights in silico approaches to design and to analyze consortia with an emphasis on stoichiometric modeling methods. The discipline of microbial consortia engineering possesses a widely accepted potential to generate highly novel and effective bio-catalysts for applications from biofuels to specialty chemicals to enhanced mineral recovery.
doi:10.5936/csbj.201210017
PMCID: PMC3962199  PMID: 24688677
6.  Synthetic Escherichia coli consortia engineered for syntrophy demonstrate enhanced biomass productivity 
Journal of biotechnology  2011;157(1):159-166.
Synthetic Escherichia coli consortia engineered for syntrophy demonstrated enhanced biomass productivity relative to monocultures. Binary consortia were designed to mimic a ubiquitous, naturally occurring ecological template of primary productivity supported by secondary consumption. The synthetic consortia replicated this evolution-proven strategy by combining a glucose positive E. coli strain, which served as the system’s primary producer, with a glucose negative E. coli strain which consumed metabolic byproducts from the primary producer. The engineered consortia utilized strategic division of labor to simultaneously optimize multiple tasks enhancing overall culture performance. Consortial interactions resulted in the emergent property of enhanced system biomass productivity which was demonstrated with three distinct culturing systems: batch, chemostat and biofilm growth. Glucose-based biomass productivity increased by ~15, 20 and 50% compared to appropriate monoculture controls for these three culturing systems respectively. Interestingly, the consortial interactions also produced biofilms with predictable, self-assembling, laminated microstructures. This study establishes a metabolic engineering paradigm which can be easily adapted to existing E. coli based bioprocesses to improve productivity based on a robust ecological theme.
doi:10.1016/j.jbiotec.2011.10.001
PMCID: PMC3549274  PMID: 22015987
Synthetic biology; Metabolic engineering; Metabolite exchange; Biofilm; Synthetic consortia
7.  Potential role of multiple carbon fixation pathways during lipid accumulation in Phaeodactylum tricornutum 
Background
Phaeodactylum tricornutum is a unicellular diatom in the class Bacillariophyceae. The full genome has been sequenced (<30 Mb), and approximately 20 to 30% triacylglyceride (TAG) accumulation on a dry cell basis has been reported under different growth conditions. To elucidate P. tricornutum gene expression profiles during nutrient-deprivation and lipid-accumulation, cell cultures were grown with a nitrate to phosphate ratio of 20:1 (N:P) and whole-genome transcripts were monitored over time via RNA-sequence determination.
Results
The specific Nile Red (NR) fluorescence (NR fluorescence per cell) increased over time; however, the increase in NR fluorescence was initiated before external nitrate was completely exhausted. Exogenous phosphate was depleted before nitrate, and these results indicated that the depletion of exogenous phosphate might be an early trigger for lipid accumulation that is magnified upon nitrate depletion. As expected, many of the genes associated with nitrate and phosphate utilization were up-expressed. The diatom-specific cyclins cyc7 and cyc10 were down-expressed during the nutrient-deplete state, and cyclin B1 was up-expressed during lipid-accumulation after growth cessation. While many of the genes associated with the C3 pathway for photosynthetic carbon reduction were not significantly altered, genes involved in a putative C4 pathway for photosynthetic carbon assimilation were up-expressed as the cells depleted nitrate, phosphate, and exogenous dissolved inorganic carbon (DIC) levels. P. tricornutum has multiple, putative carbonic anhydrases, but only two were significantly up-expressed (2-fold and 4-fold) at the last time point when exogenous DIC levels had increased after the cessation of growth. Alternative pathways that could utilize HCO3- were also suggested by the gene expression profiles (e.g., putative propionyl-CoA and methylmalonyl-CoA decarboxylases).
Conclusions
The results indicate that P. tricornutum continued carbon dioxide reduction when population growth was arrested and different carbon-concentrating mechanisms were used dependent upon exogenous DIC levels. Based upon overall low gene expression levels for fatty acid synthesis, the results also suggest that the build-up of precursors to the acetyl-CoA carboxylases may play a more significant role in TAG synthesis rather than the actual enzyme levels of acetyl-CoA carboxylases per se. The presented insights into the types and timing of cellular responses to inorganic carbon will help maximize photoautotrophic carbon flow to lipid accumulation.
doi:10.1186/1754-6834-5-40
PMCID: PMC3457861  PMID: 22672912
Algae; Diatom; Lipid-accumulation; Transcriptomics; Biofuel; Carbon fixation; RNA-seq; Bio-oil
8.  Resolution of volatile fuel compound profiles from Ascocoryne sarcoides: a comparison by proton transfer reaction-mass spectrometry and solid phase microextraction gas chromatography-mass spectrometry 
AMB Express  2012;2:23.
Volatile hydrocarbon production by Ascocoryne sacroides was studied over its growth cycle. Gas-phase compounds were measured continuously with a proton transfer reaction-mass spectrometry (PTR-MS) and at distinct time points with gas chromatography-mass spectrometry (GC-MS) using head space solid phase microextraction (SPME). The PTR-MS ion signal permitted temporal resolution of the volatile production while the SPME results revealed distinct compound identities. The quantitative PTR-MS results showed the volatile production was dominated by ethanol and acetaldehyde, while the concentration of the remainder of volatiles consistently reached 2,000 ppbv. The measurement of alcohols from the fungal culture by the two techniques correlated well. Notable compounds of fuel interest included nonanal, 1-octen-3-ol, 1-butanol, 3-methyl- and benzaldehyde. Abiotic comparison of the two techniques demonstrated SPME fiber bias toward higher molecular weight compounds, making quantitative efforts with SPME impractical. Together, PTR-MS and SPME GC-MS were shown as valuable tools for characterizing volatile fuel compound production from microbiological sources.
doi:10.1186/2191-0855-2-23
PMCID: PMC3402149  PMID: 22480438
Biofuel; Solid phase microextraction; Proton transfer reaction-mass spectrometry; Volatile organic compounds; Fungal hydrocarbons; Gas chromatography-mass spectrometry
9.  Molecular-level tradeoffs and metabolic adaptation to simultaneous stressors 
Current opinion in biotechnology  2010;21(5):670-676.
Summary
Life is a dynamic process driven by the complex interplay between physical constraints and selection pressures, ranging from nutrient limitation to inhibitory substances to predators. These stressors are not mutually exclusive; microbes have faced concurrent challenges for eons. Genome-enabled systems biology approaches are adapting economic and ecological concepts like tradeoff curves and strategic resource allocation theory to analyze metabolic adaptations to simultaneous stressors. These methodologies can accurately describe and predict metabolic adaptations to concurrent stresses by considering the tradeoff between investment of limiting resources into enzymatic machinery and the resulting cellular function. The approaches represent promising links between computational biology and well established economic and ecological methodologies for analyzing the interplay between physical constraints and microbial fitness.
doi:10.1016/j.copbio.2010.05.011
PMCID: PMC2952661  PMID: 20637598
10.  Robustness analysis of culturing perturbations on Escherichia coli colony biofilm beta-lactam and aminoglycoside antibiotic tolerance 
BMC Microbiology  2010;10:185.
Background
Biofilms are ubiquitous. For instance, the majority of medical infections are thought to involve biofilms. However even after decades of investigation, the in vivo efficacy of many antimicrobial strategies is still debated suggesting there is a need for better understanding of biofilm antimicrobial tolerances. The current study's goal is to characterize the robustness of biofilm antibiotic tolerance to medically and industrially relevant culturing perturbations. By definition, robust systems will return similar, predictable responses when perturbed while non-robust systems will return very different and potentially unpredictable responses. The predictability of an antibiotic tolerance response is essential to developing, testing, and employing antimicrobial strategies.
Results
The antibiotic tolerance of Escherichia coli colony biofilms was tested against beta-lactam and aminoglycoside class antibiotics. Control scenario tolerances were compared to tolerances under culturing perturbations including 1) different nutritional environments 2) different temperatures 3) interruption of cellular quorum sensing and 4) different biofilm culture ages. Here, antibiotic tolerance was defined in terms of culturable biofilm cells recovered after a twenty four hour antibiotic treatment.
Colony biofilm antibiotic tolerances were not robust to perturbations. Altering basic culturing parameters like nutritional environment or temperature resulted in very different, non-intuitive antibiotic tolerance responses. Some minor perturbations like increasing the glucose concentration from 0.1 to 1 g/L caused a ten million fold difference in culturable cells over a twenty four hour antibiotic treatment.
Conclusions
The current study presents a basis for robustness analysis of biofilm antibiotic tolerance. Biofilm antibiotic tolerance can vary in unpredictable manners based on modest changes in culturing conditions. Common antimicrobial testing methods, which only consider a single culturing condition, are not desirable since slight culturing variations can lead to very different outcomes. The presented data suggest it is essential to test antimicrobial strategies over a range of culturing perturbations relevant to the targeted application. In addition, the highly dynamic antibiotic tolerance responses observed here may explain why some current antimicrobial strategies occasionally fail.
doi:10.1186/1471-2180-10-185
PMCID: PMC2912858  PMID: 20609240
11.  Decomposition of complex microbial behaviors into resource-based stress responses 
Bioinformatics  2008;25(1):90-97.
Motivation: Highly redundant metabolic networks and experimental data from cultures likely adapting simultaneously to multiple stresses can complicate the analysis of cellular behaviors. It is proposed that the explicit consideration of these factors is critical to understanding the competitive basis of microbial strategies.
Results: Wide ranging, seemingly unrelated Escherichia coli physiological fluxes can be simply and accurately described as linear combinations of a few ecologically relevant stress adaptations. These strategies were identified by decomposing the central metabolism of E.coli into elementary modes (mathematically defined biochemical pathways) and assessing the resource investment cost–benefit properties for each pathway. The approach capitalizes on the inherent tradeoffs related to investing finite resources like nitrogen into different pathway enzymes when the pathways have varying metabolic efficiencies. The subset of ecologically competitive pathways represented 0.02% of the total permissible pathways. The biological relevance of the assembled strategies was tested against 10 000 randomly constructed pathway subsets. None of the randomly assembled collections were able to describe all of the considered experimental data as accurately as the cost-based subset. The results suggest these metabolic strategies are biologically significant. The current descriptions were compared with linear programming (LP)-based flux descriptions using the Euclidean distance metric. The current study's pathway subset described the experimental fluxes with better accuracy than the LP results without having to test multiple objective functions or constraints and while providing additional ecological insight into microbial behavior. The assembled pathways seem to represent a generalized set of strategies that can describe a wide range of microbial responses and hint at evolutionary processes where a handful of successful metabolic strategies are utilized simultaneously in different combinations to adapt to diverse conditions.
Contact: rossc@biofilms.montana.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btn589
PMCID: PMC2638933  PMID: 19008248
12.  In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study 
BMC Systems Biology  2009;3:114.
Background
Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and a priori knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange.
Results
The in silico models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions.
Conclusion
The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive a priori information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis.
doi:10.1186/1752-0509-3-114
PMCID: PMC2799449  PMID: 20003240

Results 1-12 (12)