Heejoon Park’s research while affiliated with University of North Alabama and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (3)


Fig. 2 Biofilm biomass productivity for E. coli (Ec) and C. phytofermentans (Cp) monocultures and binary consortium (Bi) grown under three different cultivation conditions. OX: 10 days of oxic only conditions, AN: 10 days of anoxic only conditions, and AOS: 6 days anoxic and 4 days oxic growth (denoted with gray shading). a C. phytofermentans cell number per monoculture biofilm, b E. coli cell number per monoculture biofilm, c C. phytofermentans cell number per consortium biofilm, d E. coli cell number per consortium biofilm, e Total biofilm mass (biomass + extracellular material) for monoculture and consortium biofilm cultures. Black hashed area represents sum of monoculture data for AOS condition. Data in e collected after 10 days of cultivation. Error bars represent the standard deviation from three biological replicates. Statistical significance at **p < 0.01, T-test.
Fig. 5 E. coli (Ec) and C. phytofermentans (Cp) cell number and biomass concentration as a function of spatial locations in consortium biofilms. a, c Consortium biofilms grown for 10 days anoxically (AN) and b, d consortium biofilms grown anoxically for 6 days followed by 4 days of oxic growth (AOS). Data are from day 10. Cryosectioned biofilms had cells samples excised using laser microdissection from three vertical positions (top, middle, bottom) from four to six radial positions. Cell number was calculated using qPCR. Biomass concentrations were calculated using conversion factors listed in "Materials and methods". Error bars represent the standard deviation of samples.
Fig. 6 Cellobiase activity (cellobiose hydrolysis to glucose) in spent medium from C. phytofermentans (Cp) cultures grown on various carbon sources (5 g L −1 of glucose, cellobiose, or CMC) and C. phytofermentans growth (OD 600 ) with different carbon sources. a Volumetric cellobiase activity represented as liberated glucose concentration plotted as a function of time, b specific cellobiase activity represented as liberated glucose concentration normalized to culture OD 600 plotted as a function of time, c C. phytofermentans growth (OD 600 ) on cellobiose (5 g L −1 ), glucose (5 g L −1 ), and a mixture of sugars (5 g L −1 each), d Cellobiose consumption in C. phytofermentans monocultures with and without the presence of glucose (5 g L −1 ). Error bars represent the standard deviation from three biological replicates.
Fig. 7 E. coli growth on C. phytofermentans (Cp) necromass. a Epifluorescence micrograph of C. phytofermentans cultured anoxically. b Epifluorescence image of lysed C. phytofermentans after 24 h of ambient air exposure. c Aerobic E. coli growth on different amounts of C. phytofermentans necromass, see main text for details. d C. phytofermentans necromass abundance, expressed as qPCR-based cell number, during aerobic E. coli growth on lysed C. phytofermentans biomass. Cp100, Cp50, Cp10, and Cp0 refer the percentage of medium comprised of C. phytofermentans necromass solution, see text for more details. Error bars represent the standard deviation from three biological replicates. Micrograph scale bars = 10 μm.
Summary of growth parameters compared between planktonic monocultures of E. coli (Ec) and C. phytofermentans (Cp) and a planktonic, binary consortium.
Artificial consortium demonstrates emergent properties of enhanced cellulosic-sugar degradation and biofuel synthesis
  • Article
  • Full-text available

December 2020

·

418 Reads

·

24 Citations

npj Biofilms and Microbiomes

Heejoon Park

·

·

·

[...]

·

Planktonic cultures, of a rationally designed consortium, demonstrated emergent properties that exceeded the sums of monoculture properties, including a >200% increase in cellobiose catabolism, a >100% increase in glycerol catabolism, a >800% increase in ethanol production, and a >120% increase in biomass productivity. The consortium was designed to have a primary and secondary-resource specialist that used crossfeeding with a positive feedback mechanism, division of labor, and nutrient and energy transfer via necromass catabolism. The primary resource specialist was Clostridium phytofermentans ( a.k.a. Lachnoclostridium phytofermentans ), a cellulolytic, obligate anaerobe. The secondary-resource specialist was Escherichia coli , a versatile, facultative anaerobe, which can ferment glycerol and byproducts of cellobiose catabolism. The consortium also demonstrated emergent properties of enhanced biomass accumulation when grown as biofilms, which created high cell density communities with gradients of species along the vertical axis. Consortium biofilms were robust to oxic perturbations with E. coli consuming O 2 , creating an anoxic environment for C. phytofermentans . Anoxic/oxic cycling further enhanced biomass productivity of the biofilm consortium, increasing biomass accumulation ~250% over the sum of the monoculture biofilms. Consortium emergent properties were credited to several synergistic mechanisms. E. coli consumed inhibitory byproducts from cellobiose catabolism, driving higher C. phytofermentans growth and higher cellulolytic enzyme production, which in turn provided more substrate for E. coli . E. coli necromass enhanced C. phytofermentans growth while C. phytofermentans necromass aided E. coli growth via the release of peptides and amino acids, respectively. In aggregate, temporal cycling of necromass constituents increased flux of cellulose-derived resources through the consortium. The study establishes a consortia-based, bioprocessing strategy built on naturally occurring interactions for improved conversion of cellulose-derived sugars into bioproducts.

Download

Illustration of classic carbon catabolite repression (cCCR) phenotype with overflow metabolism and reverse carbon catabolite repression (rCCR) phenotype as well as an illustration of the complementary relationship between the two global metabolism regulators. cCCR microorganisms prefer glucose to other substrates, while rCCR microorganisms prefer organic acids to glucose
Molecular components of carbon catabolite repression (CCR). a Major molecular components of classic carbon catabolite repression (cCCR) in Gram-negative E. coli. b Major molecular components of cCCR in Gram-positive B. subtilis. c Major molecular components of reverse carbon catabolite repression (rCCR) found in Pseudomonads. See main text for abbreviations and details
Trade-off between resource investment into enzymes and energetic efficiency of the Embden–Meyerhof–Parnas (EMP) (orange lines) or Entner–Doudoroff (ED) (blue lines) glycolysis pathways. Shared components are colored green. Pseudomonads use the ED pathway to catabolize glucose; the ED pathway requires fewer resources to assemble but also extracts less cellular energy from glucose than the EMP pathway. Reaction numbers map to enzymes, protein subunit compositions, and the resources required to assemble functional enzyme based on E. coli protein sequences. Data from Carlson, 2007 [31], figure modified from Carlson and Taffs, 2010 [2]
Illustration of enhanced functional return on carbon investment in a cross feeding consortium relative to a generalist system. Enzyme flux requires investment into both enzyme and metabolite pools which can be optimized to reduce total cellular investment. Operating enzymes at higher fluxes represents a better functional return on resource investment (e.g., aggregate carbon atoms in enzyme and substrate). Analysis considers Michaelis–Menten-type kinetics, 2 cells using a generalist strategy, or 2 specialist cells cross feeding. The overall glucose flux and glucose transformation are the same for both scenarios. Glycolysis reactions are represented by the enzyme Pgi, while tricarboxylic acid (TCA) cycle enzymes are represented by the enzyme FumA. Enzyme values are from E. coli and obtained from Brenda and EcoCyc. The specialist consortium requires a smaller investment of carbon to attain the same flux and transformation as the generalist system. Specific glucose uptake rate (q1) was set to 1 mmol glucose g cdw⁻¹ h⁻¹. Portion of figure modified from Beck et al. 2016 [200]
Role of byproduct inhibition in cross feeding consortia growing as biofilms. a Schematic of metabolic interactions between cCCR- and rCCR-cell types. b Example of the inhibitory properties of an organic acid as a function of concentration. cIn vitro data for an engineered, cross feeding consortium growing as a biofilm. d In silico prediction of biomass productivity for an engineered consortium growing as a biofilm. e Micrograph of a cryosectioned biofilm comprised of an engineered consortium, rCCR-cell type expressing rfp, cCCR-cell type expressing gfp. fIn silico predictions of cell-type spatial distributions within a biofilm. Portions of the figure are modified from Patel et al. 2019 [204] and Bernstein et al. 2012 [199]
Pseudomonad reverse carbon catabolite repression, interspecies metabolite exchange, and consortial division of labor

February 2020

·

610 Reads

·

39 Citations

Cellular and Molecular Life Sciences

Microorganisms acquire energy and nutrients from dynamic environments, where substrates vary in both type and abundance. The regulatory system responsible for prioritizing preferred substrates is known as carbon catabolite repression (CCR). Two broad classes of CCR have been documented in the literature. The best described CCR strategy, referred to here as classic CCR (cCCR), has been experimentally and theoretically studied using model organisms such as Escherichia coli. cCCR phenotypes are often used to generalize universal strategies for fitness, sometimes incorrectly. For instance, extremely competitive microorganisms, such as Pseudomonads, which arguably have broader global distributions than E. coli, have achieved their success using metabolic strategies that are nearly opposite of cCCR. These organisms utilize a CCR strategy termed ‘reverse CCR’ (rCCR), because the order of preferred substrates is nearly reverse that of cCCR. rCCR phenotypes prefer organic acids over glucose, may or may not select preferred substrates to optimize growth rates, and do not allocate intracellular resources in a manner that produces an overflow metabolism. cCCR and rCCR have traditionally been interpreted from the perspective of monocultures, even though most microorganisms live in consortia. Here, we review the basic tenets of the two CCR strategies and consider these phenotypes from the perspective of resource acquisition in consortia, a scenario that surely influenced the evolution of cCCR and rCCR. For instance, cCCR and rCCR metabolism are near mirror images of each other; when considered from a consortium basis, the complementary properties of the two strategies can mitigate direct competition for energy and nutrients and instead establish cooperative division of labor.


Reverse diauxie phenotype in Pseudomonas aeruginosa biofilm revealed by exometabolomics and label-free proteomics

December 2019

·

84 Reads

·

15 Citations

npj Biofilms and Microbiomes

Microorganisms enhance fitness by prioritizing catabolism of available carbon sources using a process known as carbon catabolite repression (CCR). Planktonically grown Pseudomonas aeruginosa is known to prioritize the consumption of organic acids including lactic acid over catabolism of glucose using a CCR strategy termed “reverse diauxie.” P. aeruginosa is an opportunistic pathogen with well-documented biofilm phenotypes that are distinct from its planktonic phenotypes. Reverse diauxie has been described in planktonic cultures, but it has not been documented explicitly in P. aeruginosa biofilms. Here a combination of exometabolomics and label-free proteomics was used to analyze planktonic and biofilm phenotypes for reverse diauxie. P. aeruginosa biofilm cultures preferentially consumed lactic acid over glucose, and in addition, the cultures catabolized the substrates completely and did not exhibit the acetate secreting “overflow” metabolism that is typical of many model microorganisms. The biofilm phenotype was enabled by changes in protein abundances, including lactate dehydrogenase, fumarate hydratase, GTP cyclohydrolase, L-ornithine N(5)-monooxygenase, and superoxide dismutase. These results are noteworthy because reverse diauxie-mediated catabolism of organic acids necessitates a terminal electron acceptor like O2, which is typically in low supply in biofilms due to diffusion limitation. Label-free proteomics identified dozens of proteins associated with biofilm formation including 16 that have not been previously reported, highlighting both the advantages of the methodology utilized here and the complexity of the proteomic adaptation for P. aeruginosa biofilms. Documenting the reverse diauxic phenotype in P. aeruginosa biofilms is foundational for understanding cellular nutrient and energy fluxes, which ultimately control growth and virulence.

Citations (3)


... In some cases, consortia have been assembled by leveraging the natural capabilities of wild-type microbial species for performing specific tasks. For example, Park et al. used a two-species bacterial co-culture for the production of bioethanol by leveraging the natural ability of C. phytofermentans to hydrolyze cellulose and the potential of E. coli to ferment cellobiose catabolism byproducts into ethanol, respectively (Park et al., 2020). Alternatively, researchers have relied on the genetic manipulation of different member species/strains within a consortium. ...

Reference:

Towards synthetic ecology: strategies for the optimization of microbial community functions
Artificial consortium demonstrates emergent properties of enhanced cellulosic-sugar degradation and biofuel synthesis

npj Biofilms and Microbiomes

... This observation indicates that butanoate is not a preferred carbon source in the presence of a cosubstrate. 59 The specific growth rate (μ) was not affected by butanoate at concentrations <5 g L −1 ( Figure 1C), although we observed an increase (ca. 2 h) in the extension of the lag phase in these cultures. Building on these results, we adopted reducedgenome P. putida SEM1.3 as the host to explore the butanoatedependent biosynthesis of 2-pentanone. ...

Pseudomonad reverse carbon catabolite repression, interspecies metabolite exchange, and consortial division of labor

Cellular and Molecular Life Sciences

... The models were analysed in an in silico extracellular environment defined by CSP chemically defined medium 49 , on which S. aureus and P. aeruginosa can grow as biofilms in vitro 50 . The CSP medium was designed to serve as a simplified analogue of chronic wound exudate. ...

Reverse diauxie phenotype in Pseudomonas aeruginosa biofilm revealed by exometabolomics and label-free proteomics

npj Biofilms and Microbiomes