Costas Maranas

Donald B. Broughton Professor of Chemical Engineering


Costas Maranas

Research Summary

Computational studies of metabolism and gene regulation.

Huck Graduate Students

Huck Affiliations

Links

Most Recent Publications

CatPred: a comprehensive framework for deep learning in vitro enzyme kinetic parameters

Veda Sheersh Boorla, Costas D. Maranas, 2025, Nature Communications

Reframing the role of the objective function in its proper context for metabolic network modeling

Mohammad Mazharul Islam, William Shao, Mariska Batavia, Roseanne M. Ford, Bernhard O. Palsson, Jens Nielsen, Costas D. Maranas, Sang Yup Lee, Jason A. Papin, 2025, Cell Systems

Combining Chemical Catalysis with Enzymatic Steps for the Synthesis of the Artemisinin Precursor Dihydroartemisinic Acid

Vikas Upadhyay, Hongxiang Li, Jiachen He, Blake Edward Ocampo, Silas Cook, Huimin Zhao, Costas D. Maranas, 2025, ACS Synthetic Biology on p. 1112-1120

minChemBio: Expanding Chemical Synthesis with Chemo-Enzymatic Pathways Using Minimal Transitions

Mohit Anand, Vikas Upadhyay, Costas D. Maranas, 2025, ACS Synthetic Biology on p. 756-770

Mitochondrial ATP generation is more proteome efficient than glycolysis

Yihui Shen, Hoang V. Dinh, Edward R. Cruz, Zihong Chen, Caroline R. Bartman, Tianxia Xiao, Catherine M. Call, Rolf Peter Ryseck, Jimmy Pratas, Daniel Weilandt, Heide Baron, Arjuna Subramanian, Zia Fatma, Zong Yen Wu, Sudharsan Dwaraknath, John I. Hendry, Vinh G. Tran, Lifeng Yang, Yasuo Yoshikuni, Huimin Zhao, Costas D. Maranas, Martin Wühr, Joshua D. Rabinowitz, 2024, Nature Chemical Biology on p. 1123-1132

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Wheaton L. Schroeder, Patrick F. Suthers, Thomas C. Willis, Eric J. Mooney, Costas D. Maranas, 2024, Metabolites

Data-driven and physics informed modeling of Chinese Hamster Ovary cell bioreactors

Tianqi Cui, Tom Bertalan, Nelson Ndahiro, Pratik Khare, Michael Betenbaugh, Costas Maranas, Ioannis G. Kevrekidis, 2024, Computers and Chemical Engineering

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Mengqi Hu, Patrick F. Suthers, Costas D. Maranas, 2024, Metabolic Engineering on p. 123-133

Genome streamlining to improve performance of a fast-growing cyanobacterium Synechococcus elongatus UTEX 2973

Annesha Sengupta, Anindita Bandyopadhyay, Debolina Sarkar, John I. Hendry, Max G. Schubert, Deng Liu, George M. Church, Costas D. Maranas, Himadri B. Pakrasi, 2024, mBio

Proteome efficiency of bioenergetic pathways

Yihui Shen, Hoang Dinh, Edward Cruz, Zihong Chen, Caroline Bartman, Yasuo Yoshikuni, Huimin Zhao, Costas Maranas, Martin Wühr, Joshua Rabinowitz, 2024, Biophysical Journal on p. 248a

Most-Cited Papers

Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Laurent Heirendt, Sylvain Arreckx, Thomas Pfau, Sebastián N. Mendoza, Anne Richelle, Almut Heinken, Hulda S. Haraldsdóttir, Jacek Wachowiak, Sarah M. Keating, Vanja Vlasov, Stefania Magnusdóttir, Chiam Yu Ng, German Preciat, Alise Žagare, Siu H.J. Chan, Maike K. Aurich, Catherine M. Clancy, Jennifer Modamio, John T. Sauls, Alberto Noronha, Aarash Bordbar, Benjamin Cousins, Diana C. El Assal, Luis V. Valcarcel, Iñigo Apaolaza, Susan Ghaderi, Masoud Ahookhosh, Marouen Ben Guebila, Andrejs Kostromins, Nicolas Sompairac, Hoai M. Le, Ding Ma, Yuekai Sun, Lin Wang, James T. Yurkovich, Miguel A.P. Oliveira, Phan T. Vuong, Lemmer P. El Assal, Inna Kuperstein, Andrei Zinovyev, H. Scott Hinton, William A. Bryant, Francisco J. Aragón Artacho, Francisco J. Planes, Egils Stalidzans, Alejandro Maass, Santosh Vempala, Michael Hucka, Michael A. Saunders, Costas D. Maranas, Nathan E. Lewis, Thomas Sauter, Bernhard Palsson, Ines Thiele, Ronan M.T. Fleming, 2019, Nature Protocols on p. 639-702

A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

Ali Khodayari, Costas D. Maranas, 2016, Nature Communications

Toward low-cost biological and hybrid biological/catalytic conversion of cellulosic biomass to fuels†

Lee R. Lynd, Gregg T. Beckham, Adam M. Guss, Lahiru N. Jayakody, Eric M. Karp, Costas Maranas, Robert L. McCormick, Daniel Amador-Noguez, Yannick J. Bomble, Brian H. Davison, Charles Foster, Michael E. Himmel, Evert K. Holwerda, Mark S. Laser, Chiam Yu Ng, Daniel G. Olson, Yuriy Román-Leshkov, Cong T. Trinh, Gerald A. Tuskan, Vikas Upadhayay, Derek R. Vardon, Lin Wang, Charles E. Wyman, 2022, Energy and Environmental Science on p. 938-990

SteadyCom: Predicting microbial abundances while ensuring community stability

Siu Hung Joshua Chan, Margaret N. Simons, Costas D. Maranas, 2017, PLoS Computational Biology

Multiple spillovers from humans and onward transmission of SARS-CoV-2 in white-tailed deer

Suresh V. Kuchipudi, Meera Surendran-Nair, R Ruden, M Yon, R Nissly, Kurt J. Vandegrift, R Nelli, Lingling Li, Bhushan Jayarao, Costas D. Maranas, N Levine, K Willgert, Andrew J.K. Conlan, Conlan AJK, R Olsen, J Davis, J Musser, Peter John Hudson, Vivek Kapur, 2022, Proceedings of the National Academy of Sciences of the United States of America

Rational design of a synthetic Entner-Doudoroff pathway for improved and controllable NADPH regeneration

Chiam Yu Ng, Iman Farasat, Costas D. Maranas, Howard M. Salis, 2015, Metabolic Engineering on p. 86-96

Reversing methanogenesis to capture methane for liquid biofuel precursors

Valerie W.C. Soo, Michael J. McAnulty, Arti Tripathi, Fayin Zhu, Limin Zhang, Emmanuel Hatzakis, Philip B. Smith, Saumya Agrawal, Hadi Nazem-Bokaee, Saratram Gopalakrishnan, Howard M. Salis, James G. Ferry, Costas D. Maranas, Andrew D. Patterson, Thomas K. Wood, 2016, Microbial Cell Factories on p. 11

Farnesoid X receptor signaling shapes the gut microbiota and controls hepatic lipid metabolism

Limin Zhang, Cen Xie, Robert G. Nichols, Siu H.J. Chan, Changtao Jiang, Ruixin Hao, Philip B. Smith, Jingwei Cai, Margaret N. Simons, Emmanuel Hatzakis, Costas D. Maranas, Frank J. Gonzalez, Andrew D. Patterson, 2016, mSystems on p. e00070-16

Comparative genomics reveals the molecular determinants of rapid growth of the cyanobacterium Synechococcus elongatus UTEX 2973

Justin Ungerer, Kristen E. Wendt, John I. Hendry, Costas D. Maranas, Himadri B. Pakrasi, 2018, Proceedings of the National Academy of Sciences of the United States of America on p. E11761-E11770

A review of computational tools for design and reconstruction of metabolic pathways

Lin Wang, Satyakam Dash, Chiam Yu Ng, Costas D. Maranas, 2017, Synthetic and Systems Biotechnology on p. 243-252

News Articles Featuring Costas Maranas

Jun 01, 2026

Q&A: Are plants the key to solving energy and food crises worldwide?

Changing market conditions are increasing the need for cost-effective ways to produce biorenewable chemicals, biofuels and materials that can serve as alternatives to oil-based products. According to Costas Maranas, Robert V. & Gloria H. Waltemeyer Chair and Donald B. Broughton Professor of Chemical Engineering at Penn State, solutions to these problems could come from applying tools used in synthetic biology to plants and their microbial partners across the globe.

Full Article

Mar 03, 2025

'Growing Impact' discusses environmental contaminants, human health

The latest episode of Growing Impact discusses how environmental contaminants affect human health, a research focus for Penn State professors Andrew Patterson and Costas Maranas.

Full Article

Nov 03, 2021

Deer may be reservoir for SARS-CoV-2, study finds

The findings of a study by Penn State and Iowa researchers suggest that white-tailed deer may be a reservoir for the SARS-CoV-2 virus to continually circulate, and raises concerns of emergence of new strains that may prove a threat to wildlife and, possibly, to humans.

Full Article

Sep 29, 2021

New tool predicts changes that may make COVID variants more infectious

The first key step in SARS-CoV-2 infection is when the virus’ spike protein binds to the ACE2 receptor on human cells. Researchers at Penn State have created a novel framework that can predict with reasonable accuracy the amino-acid changes in the virus’ spike protein that may improve its binding to human cells and confer increased infectivity to the virus.

Full Article