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102. Shoaie, S.; Nielsen, J. Elucidating the interactions between the human gut microbiota and its host through
metabolic modeling. Front. Genet. 2014, 5, 86. [CrossRef]
103. Thiele, I.; Heinken, A.; Fleming, R.M. A systems biology approach to studying the role of microbes in human
health. Curr. Opin. Biotechnol. 2013, 24, 4–12. [CrossRef][PubMed]
104. Glick-Bauer, M.; Yeh, M.C. The health advantage of a vegan diet: Exploring the gut microbiota connection.
Nutrients 2014, 6, 4822–4838. [CrossRef][PubMed]
105. Swainston, N.; Mendes, P.; Kell, D.B. An analysis of a ‘community-driven’reconstruction of the human
metabolic network. Metabolomics 2013, 9, 757–764. [CrossRef][PubMed]
106. Thiele, I.; Swainston, N.; Fleming, R.M.; Hoppe, A.; Sahoo, S.; Aurich, M.K.; Haraldsdottir, H.; Mo, M.L.;
Rolfsson, O.; Stobbe, M.D.; et al. A community-driven global reconstruction of human metabolism.
Nat. Biotechnol. 2013, 31, 419. [CrossRef][PubMed]
107. Thiele, I.; Sahoo, S.; Heinken, A.; Heirendt, L.; Aurich, M.K.; Noronha, A.; Fleming, R.M. When metabolism
meets physiology: Harvey and Harvetta. bioRxiv 2018..[ CrossRef]
108. Dai, Z.L.; Wu, G.; Zhu, W.Y. Amino acid metabolism in intestinal bacteria: Links between gut ecology and
host health. Front. Biosci. 2011, 16, 1768–1786. [CrossRef]
109. Horn, H.; Lackner, S. Modeling of biofilm systems: A review. In Productive Biofilms; Springer: Cham,
Swizterland, 2014; pp. 53–76.
110. Lawley, T.D.; Clare, S.; Walker, A.W.; Stares, M.D.; Connor, T.R.; Raisen, C.; Goulding, D.; Rad, R.; Schreiber, F.;
Brandt, C.; et al. Targeted restoration of the intestinal microbiota with a simple, defined bacteriotherapy
resolves relapsing Clostridium difficile disease in mice. PLoS Pathog. 2012, 8, e1002995. [CrossRef]
111. Chen, J.; Gomez, J.A.; Höffner, K.; Phalak, P.; Barton, P.I.; Henson, M.A. Spatiotemporal modeling of
microbial metabolism. BMC Syst. Biol. 2016, 10, 21. [CrossRef]
112. Phalak, P.; Chen, J.; Carlson, R.P.; Henson, M.A. Metabolic modeling of a chronic wound biofilm consortium
predicts spatial partitioning of bacterial species. BMC Syst. Biol. 2016, 10, 90. [CrossRef][PubMed]
113. Gomez, J.A.; Hoffner, K.; Barton, P.I. DFBAlab: A fast and reliable MATLAB code for dynamic flux balance
analysis. BMC Bioinform. 2014, 15, 409. [CrossRef][PubMed]
114. Meadows, A.L.; Karnik, R.; Lam, H.; Forestell, S.; Snedecor, B. Application of dynamic flux balance analysis
to an industrial Escherichia coli fermentation. Metab. Eng. 2010, 12, 150–160. [CrossRef][PubMed]
115. Stewart, P.S. A review of experimental measurements of effective diffusive permeabilities and effective
diffusion coefficients in biofilms. Biotechnol. Bioeng. 1998, 59, 261–272. [CrossRef]
116. Stewart, P.S. Diffusion in biofilms. J. Bacteriol. 2003, 185, 1485–1491. [CrossRef][PubMed]
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
40
102. Shoaie, S.; Nielsen, J. Elucidating the interactions between the human gut microbiota and its host through
metabolic modeling. Front. Genet. 2014, 5, 86. [CrossRef]
103. Thiele, I.; Heinken, A.; Fleming, R.M. A systems biology approach to studying the role of microbes in human
health. Curr. Opin. Biotechnol. 2013, 24, 4–12. [CrossRef][PubMed]
104. Glick-Bauer, M.; Yeh, M.C. The health advantage of a vegan diet: Exploring the gut microbiota connection.
Nutrients 2014, 6, 4822–4838. [CrossRef][PubMed]
105. Swainston, N.; Mendes, P.; Kell, D.B. An analysis of a ‘community-driven’reconstruction of the human
metabolic network. Metabolomics 2013, 9, 757–764. [CrossRef][PubMed]
106. Thiele, I.; Swainston, N.; Fleming, R.M.; Hoppe, A.; Sahoo, S.; Aurich, M.K.; Haraldsdottir, H.; Mo, M.L.;
Rolfsson, O.; Stobbe, M.D.; et al. A community-driven global reconstruction of human metabolism.
Nat. Biotechnol. 2013, 31, 419. [CrossRef][PubMed]
107. Thiele, I.; Sahoo, S.; Heinken, A.; Heirendt, L.; Aurich, M.K.; Noronha, A.; Fleming, R.M. When metabolism
meets physiology: Harvey and Harvetta. bioRxiv 2018..[ CrossRef]
108. Dai, Z.L.; Wu, G.; Zhu, W.Y. Amino acid metabolism in intestinal bacteria: Links between gut ecology and
host health. Front. Biosci. 2011, 16, 1768–1786. [CrossRef]
109. Horn, H.; Lackner, S. Modeling of biofilm systems: A review. In Productive Biofilms; Springer: Cham,
Swizterland, 2014; pp. 53–76.
110. Lawley, T.D.; Clare, S.; Walker, A.W.; Stares, M.D.; Connor, T.R.; Raisen, C.; Goulding, D.; Rad, R.; Schreiber, F.;
Brandt, C.; et al. Targeted restoration of the intestinal microbiota with a simple, defined bacteriotherapy
resolves relapsing Clostridium difficile disease in mice. PLoS Pathog. 2012, 8, e1002995. [CrossRef]
111. Chen, J.; Gomez, J.A.; Höffner, K.; Phalak, P.; Barton, P.I.; Henson, M.A. Spatiotemporal modeling of
microbial metabolism. BMC Syst. Biol. 2016, 10, 21. [CrossRef]
112. Phalak, P.; Chen, J.; Carlson, R.P.; Henson, M.A. Metabolic modeling of a chronic wound biofilm consortium
predicts spatial partitioning of bacterial species. BMC Syst. Biol. 2016, 10, 90. [CrossRef][PubMed]
113. Gomez, J.A.; Hoffner, K.; Barton, P.I. DFBAlab: A fast and reliable MATLAB code for dynamic flux balance
analysis. BMC Bioinform. 2014, 15, 409. [CrossRef][PubMed]
114. Meadows, A.L.; Karnik, R.; Lam, H.; Forestell, S.; Snedecor, B. Application of dynamic flux balance analysis
to an industrial Escherichia coli fermentation. Metab. Eng. 2010, 12, 150–160. [CrossRef][PubMed]
115. Stewart, P.S. A review of experimental measurements of effective diffusive permeabilities and effective
diffusion coefficients in biofilms. Biotechnol. Bioeng. 1998, 59, 261–272. [CrossRef]
116. Stewart, P.S. Diffusion in biofilms. J. Bacteriol. 2003, 185, 1485–1491. [CrossRef][PubMed]
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
40