Publications

Selected publications

2024

• Fontana, Jason, et al. "Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling." 

Nature Communications 15.1 (2024): 6341.

• García Martín, Hector, Stanislav Mazurenko, and Huimin Zhao (2024). "Special Issue on Artificial Intelligence for Synthetic Biology."

ACS Synthetic Biology 13.2 (2024): 408-410

• Banerjee, Deepanwita, et al.  (2024). "Genome-scale and pathway engineering for the sustainable aviation fuel precursor isoprenol production in Pseudomonas putida."

       Metabolic Engineering, 82, 157-170 

• Pidatala, Venkataramana R., et al.  (2024) "Feedstocks-to-Fuels Pipeline (F2F)." 

Protocols.io 

2023

• Backman, Tyler WH, et al. "BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale."

PLoS Computational Biology 19.11 (2023): e1011111.

• Roell, G. W., Schenk, C., Anthony, W. E., Carr, R. R., Ponukumati, A., Kim, J., Akhmatskaya, E. , Foston, M., Dantas, G., Moon, T.S., Tang, Y.J., and García Martín, H. (2023). A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism. 

ACS Synthetic Biology 2023, 12, 6, 1632–1644

• Sanders, L. M., Scott, R. T., Yang, J. H., Qutub, A. A., Garcia Martin, H., Berrios, D. C., ... & Costes, S. V. (2023). Biological research and self-driving labs in deep space supported by artificial intelligence. 

Nature Machine Intelligence, 5(3), 208-219.

• Scott, R. T., Sanders, L. M., Antonsen, E. L., Hastings, J. J., Park, S. M., Mackintosh, G., ... & Costes, S. V. (2023). Biomonitoring and precision health in deep space supported by artificial intelligence. 

Nature Machine Intelligence, 5(3), 196-207.

• Garcia Martin, H., Radivojevic, T., Zucker, J., Bouchard, K., Sustarich, J., Peisert, S., Arnold, D., Hillson, N., Babnigg, G., Martin, J.M., Mungall, C.J., Beckham, G.T., Waldburger, L., Carothers, J. , Sundaram, S.S., Agarwal, D., Simmons, B.A., Backman, T.,  Banerjee, D., Tanjore, D., & Singh, A. (2023). Perspectives for self-driving labs in synthetic biology. 

Current Opinion in Biotechnology, 79, 102881.

• Tao, X. B., LaFrance, S., Xing, Y., Nava, A. A., Garcia Martin, H., Keasling, J. D., & Backman, T. W. (2023). ClusterCAD 2.0: an updated computational platform for chimeric type I polyketide synthase and nonribosomal peptide synthetase design. 

Nucleic Acids Research, 51(D1), D532-D538.

2022

• Blay, V., Radivojevic, T., Allen, J. E., Hudson, C. M., & Garcia Martin, H. (2022). MACAW: an accessible tool for molecular embedding and inverse molecular design.

 Journal of Chemical Information and Modeling 62.15 (2022): 3551-3564.

• Eslami, M., Adler, A., Caceres, R. S., Dunn, J. G., Kelley-Loughnane, N., Varaljay, V. A., & Garcia Martin, H.  (2022). Artificial intelligence for synthetic biology. 

Communications of the ACM, 65(5), 88-97

• Iwai, K., Wehrs, M., Garber, M., Sustarich, J., Washburn, L., Costello, Z., Kim, P.W., Ando, D., Gaillard, W.R., Hillson, N.J., Adams, P.D., Mukhopadhyay, A., Garcia Martin, H. & Singh, A. K. (2022). Scalable and automated CRISPR-based strain engineering using droplet microfluidics. 

Microsystems & Nanoengineering, 8(1): 1-10

• Howe, A., Bonito, G., Chou, M.Y., Cregger, M.A., Fedders, A., Field, J.L., Garcia Martin, H., Labbé, J.L., Mechan-Llontop, M.E., Northen, T.R. & Shade, A. (2022). Frontiers and opportunities in bioenergy crop microbiome research networks. 

Phytobiomes Journal: PBIOMES-05

2021

• Keasling, J., Garcia Martin, H., Lee, T. S., Mukhopadhyay, A., Singer, S. W., & Sundstrom, E. (2021). Microbial production of advanced biofuels. 

Nature Reviews Microbiology, 19.11: 701-715.

• Roy, S., Radivojevic, T., Forrer, M., Marti, J. M., Jonnalagadda, V., Backman, T., ... & Garcia Martin, H. (2021). Multiomics data collection, visualization, and utilization for guiding metabolic engineering.

 Frontiers in Bioengineering and Biotechnology, 9, 45.

• Lawson, C., Martí, J. M., Radivojevic, T., Jonnalagadda, S. V. R., Gentz, R., Hillson, N. J., Kim, J., Simmons, B. A., Petzold, C.J. , Singer, S.W., Mukhopadhyay, A., Tanjore, D., Dunn, J.G., Garcia Martin, H. Machine learning for metabolic engineering: A review. 

Metabolic Engineering  63, 34-60 

2020

• Radivojević, T., Costello, Z., Workman, K., Garcia Martin, H. A machine learning Automated Recommendation Tool for synthetic biology. 

Nature Communications 11, 4879 (2020)

• Zhang, J., Petersen, S., Radivojevic, T., Ramirez, A., Pérez-Manríquez, A., Abeliuk, A., Sánchez, B.J., Costello, Z., Chen, Y., Fero, M.J., Garcia Martin, H., Nielsen, J., Keasling, J.D., Jensen, M.K. Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism. 

Nature Communications 11, 4880 (2020). 

• Zargar, A., Lal, R., Valencia, L. E., Wang, J., Backman, T. W. H., Cruz-Morales, P., Kothari, A., Werts, M., Wong, A.R., Bailey C.B., Loubat A., Liu, Y., Chen, Y., Chang, S., Benites, V.T., Hernández, A.C., Barajas, J.F., Thompson, M.G., Barcelos, C., Anayah, R., Garcia Martin, H., Mukhopadhyay, A., Petzold, C.J., Baidoo E.E.K., Katz, L., Keasling, J.D. Chemoinformatic-guided engineering of polyketide synthases. 

Journal of the American Chemical Society (JACS) 142, 22, 9896–9901 (2020).                  

2019

• Thompson, M. G., Costello, Z., Hummel, N. F., Cruz-Morales, P., Blake-Hedges, J. M., Krishna, R. N., Skyrus, W., Pearson, A., Incha, M.R., Shich, P.M., Garcia Martin, H., Keasling, J.D. Robust characterization of two distinct glutarate sensing transcription factors of Pseudomonas putida L-lysine metabolism. 

ACS Synthetic Biology, 8(10), 2385-2396 (2019).

• Thompson, M.G., Pearson, A.N., Barajas, J.F., Cruz-Morales, P., Sedaghatian, N., Costello, Z., Garber, M.E., Incha, M.R., Valencia, L.E., Baidoo, E.E., Garcia Martin, H., Mukhopadhyay, A. and Keasling, J. D. Identification, characterization, and application of a highly sensitive lactam biosensor from Pseudomonas putida. 

ACS Synthetic Biology 9.1: 53-62 (2019).

• Lawson, C.E., Harcombe, W.R., Hatzenpichler, R., Lindemann, S.R., Löffler, F.E., O’Malley, M.A., Martín, H.G., Pfleger, B.F., Raskin, L., Venturelli, O.S., Weissbrodt, D.G., Noguera,  D. R., McMahon, K.D. Common principles and best practices for engineering microbiomes. 

Nature Reviews Microbiology, pp.1-17 (2019).

• Chen, Y., Guenther, J.M., Gin, J.W., Chan, L.J.G., Costello, Z., Ogorzalek, T.L., Tran, H.M., Blake-Hedges, J.M., Keasling, J.D., Adams, P.D.,  Garcia Martin, H., Hillson, N. H., Petzold, C. J.  An automated ‘cells-to-peptides’ sample preparation workflow for high-throughput, quantitative proteomic assays of microbes. 

Journal of Proteome Research, 18: 3752-3761 (2019).

• Carbonell, P., Radivojevic, T. and García Martín, H. Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation. 

ACS Synthetic Biology 1474-1477 (2019)

• Roell, G.W., Carr, R.R., Campbell, T., Shang, Z., Henson, W.R., Czajka, J.J., Martín, H.G., Zhang, F., Foston, M., Dantas, G. and Moon, T.S. A concerted systems biology analysis of phenol metabolism in Rhodococcus opacus PD630. 

Metabolic Engineering (2019).

• Barajas, J.F., McAndrew, R.P., Thompson, M.G., Backman, T.W., Pang, B., de Rond, T., Pereira, J.H., Benites, V.T., Garcia Martín, H., Baidoo, E.E., Hillson, N.J., Adams, P.D., Keasling, J.D. "Structural insights into dehydratase substrate selection for the borrelidin and fluvirucin polyketide synthases". 

Journal of Industrial Microbiology & Biotechnology, pp.1-11 (2019).

• Opgenorth, P., Costello, Z., Okada, T., Goyal, G., Chen, Y., Gin, J., Benites, V., de Raad, M., Northen, T. R., Deng, K.,  Deutsch, S., Baidoo, E. E. K., Petzold, C. J., Hillson, N., Garcia Martin, H., & Beller, H. . "Lessons from two Design-Build-Test-Learn cycles of dodecanol production in Escherichia coli aided by machine learning."  

ACS Synthetic Biology (2019).

• Oyetunde, T., Liu, D., Garcia Martin, H., & Tang, Y. J. "Machine learning framework for assessment of microbial factory performance." 

PloS one 14.1: e0210558 (2019).

• Ando, D., and Garcia Martin, H. "Genome-Scale 13 C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae" 

Microbial Metabolomics. Humana Press, New York, NY: 317-345 (2019).                         

2018

• Goyal, G., Costello, Z., Gutierrez, J. A., Kang, A., Lee, T. S., Garcia Martin, H., & Hillson, N. J. "Parallel Integration and Chromosomal Expansion of Metabolic Pathways".  

ACS Synthetic Biology 7(11): 2566-2576 (2018).

• Costello, Z., and Garcia Martin H. "A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data." 

Nature pj Systems Biology & Applications 4.1: 19 (2018).

•  Oyetunde, T., Bao, F. S., Chen, J. W., Garcia Martin, H., Tang, Y. J. "Leveraging knowledge engineering and machine learning for microbial biomanufacturing." 

Biotechnology Advances 36(4):1308 (2018).

• Iwai, K., Ando, D., Kim, P. W., Gach, P. C., Raje, M., Duncomb, T. A., Heinemann, J., Northen, T., Garcia Martin, H., Hillson, N., Adams, P. D., Singh. A. “Automated flow-based/digital microfluidic platform integrated with onsite electroporation process for multiplex genetic engineering applications.”  

Micro Electro Mechanical Systems (MEMS): IEEE (pp. 1229-1232) (2018).

•  Denby C.M., Li R.A., Vu V.T., Costello Z., Lin W., Chan L.J., Williams J., Donaldson B., Bamforth C.W., Petzold C.J., Scheller H.V., Garcia Martin H. and Keasling, J.D. “Industrial brewing yeast engineered for the production of primary flavor determinants in hopped beer.”  

Nature Communications, 9(1): 965 (2018).

• Backman, T. W. H., Ando, D., Singh, J., Keasling, J.D. and García Martín, H. “Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis.”  

Metabolites, 8(1), p.3 (2018).

• Ando, D., and Garcia Martin, H. "Two-Scale 13C Metabolic Flux Analysis for Metabolic Engineering."   

Synthetic Metabolic Pathways. Humana Press, NY: 333-352 (2018).                          

2017

• Eng, Clara H., Backman, T. W. H., Bailey, C. B., Magnan, C.,  Garcia Martin, H., Katz, L., Baldi, P., Keasling, J. D.  "ClusterCAD: a computational platform for type I modular polyketide synthase design." 

Nucleic acids research 46.D1 (2017): D509-D515.

• Morrell, W., Birkel, G., Forrer, M., Lopez, T., Backman, T. W. H., Dussault, M., Petzold, C.J., Baidoo, E.E.K., Costello, Z., Ando, D., Alonso-Gutierrez, J., George, K., Mukhopadhyay, A., Vaino, I., Keasling, J.D., Adams, P.D., Hillson, N.J., Garcia Martin, H. ”The Experiment Data Depot: a web-based software tool for biological experimental data storage, sharing, and visualization" 

ACS Synthetic Biology DOI: 10.1021/acssynbio.7b00204 (2017).

•  D’Espaux, L., Gosh, A., Runguphan, W., Wehrs, M., Xu, F., Konzock, O., Dev, I., Nhan, M., Gin, J., Reider Apel, A., Petzold, C. J., Singh, S., Simmons, B. A., Mukhopadhyay, A., Garcia Martin, H., Keasling, J.D. "Engineering high-level production of fatty alcohols by Saccharomyces cerevisiae from lignocellulosic feedstocks."   

Metabolic Engineering 42: 115-125 (2017).

• Birkel, G. W., Ghosh, A., Kumar, V.S., Weaver, D., Ando, D., Backman, T.W., Arkin, A.P., Keasling, J.D., Garcia Martin, H. "The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism.” 

BMC bioinformatics 18 (1): 205 (2017).

• Shymansky, C., Wang, G., Baidoo, E.E.K., Gin, J., Reider Apel, A., Mukhopadhyay, A., Garcia Martin, H., Keasling, J.D. "Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism."   

Frontiers in Bioengineering and Biotechnology 5 (2017).

2016

• Ghosh, A., Ando, D., Gin, J., Runguphan, W., Denby, C., Wang, G., Baidoo, E.E.K., Shymansky, C., Keasling, J.D., Garcia Martin, H. "13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids."   

Frontiers in Bioengineering and Biotechnology 4 (2016).

• Hollinshead, W. D., Rodriguez, S., Garcia Martin, H., Wang, G., Baidoo, E.E.K., Sale, K.L., Keasling, J.D., Mukhopadhyay, A., Tang, Y. J. "Examining Escherichia coli glycolytic pathways, catabolite repression, and metabolite channeling using Δ pfk mutants."  

Biotechnology for Biofuels 9 (1): 212 (2016).

•  Brunk, E., George, K.W., Alonso-Gutierrez, J., Thompson, M., Baidoo, E.E.K., Wang, G., Petzold, C.J., McCloskey, D., Monk, J., Yang, L., O'Brien, E.J., Batth, T.S., Garcia Martin, H., Feist, A., Adams, P.D., Keasling, J.D., Palsson, B.O., Lee, T.S. "Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow."  

Cell Systems 2 (5): 335-346 (2016).                                                               

• Chubukov, V., Mukhopadhyay, A., Petzold, C.J., Keasling, J.D., Garcia Martin, H. “Synthetic and systems biology for microbial production of commodity chemicals.” 

Nature pj Systems Biology & Applications 2: 16009 (2016).                             

2015

• Garcia Martin, H., Kumar, V.S., Weaver, D., Ghosh, A., Chubukov, V., Mukhopadhyay, A., Arkin, A., Keasling, J.D. “A method to constrain genome-scale models with 13C labeling data.” 

PLOS Computational Biology 11(9): e1004363 (2015).

• Alonso-Gutierrez, J., Kim E.M., Bath, T.S., Cho, N., Hu, Q., Chan, L.J., Petzold, C.J., Hillson, N.J., Adams, P.D., Keasling, J.D., Garcia Martin, H., Lee, T.S. “Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering.”

Metabolic Engineering 28: 123-133 (2015).                           

2014

• Ghosh, A., Nilmeier, J., Weaver, D., Adams, P.D., Keasling, J.D., Mukhopadhyay, A., Petzold, C.J., Garcia Martin, H.  “A Peptide-Based Method for 13C Metabolic Flux Analysis in Microbial Communities.” 

PLOS Computational Biology 10(9): e1003827 (2014).

• Sarria, S., Wong, B., Garcia Martin, H., Keasling, J.D., Peralta-Yahya, P. “Microbial Synthesis of Pinene.” 

ACS Synthetic Biology 3(7): 466-75 (2014).                     

2013

• Bokinsky, G. Baidoo, E.E.K., Akella, S., Burd, H., Weaver, D., Alonso-Gutierrez, J., Garcia Martin, H., Lee, T.S., Keasling, J.D. "HipA-Triggered Growth Arrest and beta-Lactam Tolerance in Escherichia coli are Mediated by RelA-Dependent ppGpp Synthesis.” 

Journal of Bacteriology 195(14): 3173-82 (2013).                             

2010

•  Garcia Martin, H., Veysey, J., Bonheyo, G.T., Frias-Lopez, J., Goldenfeld, N. and Fouke, B.W.  “Statistical Evaluation of Bacterial 16S rRNA Gene Sequences in Relation to Travertine Mineral Precipitation and Water Chemistry at Mammoth Hot Springs, Yellowstone National Park, USA” 

In Geomicrobiology: molecular and environmental perspective, 11: 239-249 (2010).

• Shaikh, A.S., Tang, Y.J., Mukhopadhyay, A., Garcia Martin, H., Gin, J. Benke, P., Keasling, J.D. “Study of stationary phase metabolism via isotopomer analysis of amino acids from an isolated protein.” 

Biotechnology Progress 26(1):52-6 (2010).                              

2009

• Tang, Y.J., Garcia Martin, H., Deutschbauer, A., Feng, X., Huang, R., Llora, X., Arkin, A., Keasling, J.D. "Invariability of central metabolic flux distribution in Shewanella oneidensis MR-1 under environmental or genetic perturbations." 

Biotechnology Progress 25(5): 1254-1259 (2009).

•  Tang, Y.J.*, Garcia Martin, H.*, Myers, S., Rodriguez, S., Baidoo, E.E.K., Keasling, J.D.  “Advances in analysis of microbial metabolic fluxes via 13C isotopic labeling”  

Mass Spectrometry Reviews, 28(2): 362-375 (2009). 

• Tang, Y.J.*, Garcia Martin, H.*, Dehal, P.S., Deutschbauer, A., Llora, X., Meadows, A., Arkin, A., Keasling, J.D. “Metabolic flux analysis of Shewanella spp. Reveals evolutionary robustness in central carbon metabolism." 

Biotechnology Bioengineering, 102: 1161-1169 (2009).