Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions
Open accessAbstract
Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
S. elongatus PCC 7942 has a well-characterised circadian clock system, which regulates a variety of physiological processes, including photosynthesis, metabolism, and cell division.
“One of the most significant features of S. elongatus PCC 7942 is its well-characterised circadian clock system, which regulates a variety of physiological processes, including photosynthesis, metabolism, and cell division.”
From Cyanobacteria as a Photosynthetic Chassis for Metabolic Pathway Engineering with Heterologous Gene Expression (2026) · cites this paper as [62]
The Introduction describes S. elongatus PCC 7942 as a model for circadian regulation and says circadian control affects photosynthesis and day–night metabolism. The Results also refer to its well-characterized circadian rhythms. Our copy does not say that the clock regulates cell division (searched: “cell division” and “division”), so that part of the claim is unsupported. (LLM, conf=0.88)
Experimental — accuracy not yet measuredEndogenous circadian regulation in S. elongatus PCC 7942 can affect the timing and efficiency of engineered metabolic pathways.
“From a biotechnological standpoint, this endogenous circadian regulation has also garnered interest in the metabolic engineering, as it can affect the timing and efficiency of engineered metabolic pathways [62].”
From Cyanobacteria as a Photosynthetic Chassis for Metabolic Pathway Engineering with Heterologous Gene Expression (2026) · cites this paper as [62]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430 · see citing works
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077 · see citing works
Centrality in social networks conceptual clarification
Freeman, L. C. (1978) · Social Networks · doi:10.1016/0378-8733(78)90021-7 · Cited by 17,062 · see citing works
A set of measures of centrality based upon betweenness
Freeman, L. (1977) · Sociometry · doi:10.2307/3033543 · Cited by 10,557 · see citing works
NCBI GEO: archive for functional genomics data sets—update
Barrett, T., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., Tomashevsky, M., Marshall, K. A., Phillippy, K. H., Sherman, P. M., Holko, M., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1193 · Cited by 10,418 · see citing works
Pfam: The protein families database in 2021
Mistry, J., Chuguransky, S., Williams, L., Qureshi, M., Salazar, G. A., Sonnhammer, E. L. L., Tosatto, S. C. E., Paladin, L., Raj, S., Richardson, L. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa913 · Cited by 7,452 · see citing works
UniProt: the Universal Protein Knowledgebase in 2023
The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., Bye-A-Jee, H., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1052 · Cited by 7,210 · see citing works
Inferring Regulatory Networks from Expression Data Using Tree-Based Methods
Huynh-Thu, V. A., Irrthum, A., Wehenkel, L., & Geurts, P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012776 · Cited by 2,131 · see citing works
The COG database: new developments in phylogenetic classification of proteins from complete genomes
Tatusov, R. L. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.22 · Cited by 1,873 · see citing works
Wisdom of crowds for robust gene network inference
The DREAM5 Consortium, Marbach, D., Costello, J. C., Küffner, R., Vega, N. M., Prill, R. J., Camacho, D. M., Allison, K. R., Kellis, M., Collins, J. J., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2016 · Cited by 1,667 · see citing works
Multi-Omics Factor Analysis—a framework for unsupervised integration of multi-omics data sets
Argelaguet, R., Velten, B., Arnol, D., Dietrich, S., Zenz, T., Marioni, J. C., Buettner, F., Huber, W., & Stegle, O. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178124 · Cited by 1,510 · see citing works
The BioCyc collection of microbial genomes and metabolic pathways
Karp, P. D., Billington, R., Caspi, R., Fulcher, C. A., Latendresse, M., Kothari, A., Keseler, I. M., Krummenacker, M., Midford, P. E., Ong, Q., et al. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbx085 · Cited by 1,005 · see citing works
The genome portal of the Department of Energy Joint Genome Institute: 2014 updates
Nordberg, H. P., Cantor, M. N., Dusheyko, S., Hua, S., Poliakov, A., Shabalov, I., Smirnova, T., Grigoriev, I. V., & Dubchak, I. L. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1069 · Cited by 775 · see citing works
Expression of a Gene Cluster kaiABC as a Circadian Feedback Process in Cyanobacteria
Ishiura, M., Kutsuna, S., Aoki, S., Iwasaki, H., Andersson, C. R., Tanabe, A., Golden, S. S., Johnson, C. H., & Kondo, T. (1998) · Science · doi:10.1126/science.281.5382.1519 · Cited by 760 · see citing works
Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
Cao, Z.-J., & Gao, G. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01284-4 · Cited by 616 · see citing works
Systems strategies for developing industrial microbial strains
Lee, S. Y., & Kim, H. U. (2015) · Nature Biotechnology · doi:10.1038/nbt.3365 · Cited by 589 · see citing works
Choi, K. R., Jang, W. D., Yang, D., Cho, J. S., Park, D., & Lee, S. Y. (2019) · Trends in biotechnology · doi:10.1016/j.tibtech.2019.01.003 · Cited by 565 · see citing works
Ko, Y., Kim, J. W., Lee, J. A., Han, T., Kim, G. B., Park, J. E., & Lee, S. Y. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00155d · Cited by 475 · see citing works
The Sequence Read Archive: a decade more of explosive growth
Katz, K., Shutov, O., Lapoint, R., Kimelman, M., Brister, J. R., & O’Sullivan, C. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1053 · Cited by 424 · see citing works
Sierro, N., Makita, Y., de Hoon, M., & Nakai, K. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm910 · Cited by 412 · see citing works
Dirk Koschützki, A., & Schreiber, F. (2008) · Gene Regulation and Systems Biology · doi:10.4137/grsb.s702 · Cited by 344 · see citing works
DBD––taxonomically broad transcription factor predictions: new content and functionality
Wilson, D. A., Charoensawan, V., Kummerfeld, S., & Teichmann, S. A. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm964 · Cited by 296 · see citing works
Gründel, M., Scheunemann, R., Lockau, W., & Zilliges, Y. (2012) · Microbiology · doi:10.1099/mic.0.062950-0 · Cited by 282 · see citing works
Greenfield, A., Madar, A., Ostrer, H., & Bonneau, R. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013397 · Cited by 255 · see citing works
Molecular mechanism for the operation of nitrogen control in cyanobacteria.
Luque, I., Flores, E., & Herrero, A. (1994) · The EMBO Journal · doi:10.1002/j.1460-2075.1994.tb06580.x · Cited by 223 · see citing works
Role of KaiC phosphorylation in the circadian clock system of Synechococcus elongatus PCC 7942
Nishiwaki, T., Satomi, Y., Nakajima, M., Lee, C., Kiyohara, R., Kageyama, H., Kitayama, Y., 実央子, 手., Yamaguchi, A., Hijikata, A., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0403906101 · Cited by 218 · see citing works
RegulonDB: a database on transcriptional regulation in Escherichia coli
Huerta, A. (1998) · Nucleic Acids Research · doi:10.1093/nar/26.1.55 · Cited by 200 · see citing works
Oscillations in supercoiling drive circadian gene expression in cyanobacteria
Vijayan, V., Zuzow, R., & O’Shea, E. K. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0912673106 · Cited by 196 · see citing works
Abdulrehman, D., Monteiro, P. T., Teixeira, M. C., Mira, N. P., Lourenço, A. B., dos Santos, S. C., Cabrito, T. R., Francisco, A. P., Madeira, S. C., Aires, R. S., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq964 · Cited by 188 · see citing works
Circadian Control of Global Gene Expression by the Cyanobacterial Master Regulator RpaA
Markson, J. S., Piechura, J. R., Puszynska, A. M., & O’Shea, E. K. (2013) · Cell · doi:10.1016/j.cell.2013.11.005 · Cited by 183 · see citing works
Teixeira, M. C., Monteiro, P. T., Palma, M., Costa, C., Godinho, C. P., Pais, P., Cavalheiro, M., Antunes, M., Lemos, A., Pedreira, T., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx842 · Cited by 182 · see citing works
k -core: Theories and applications
Kong, Y.-X., Shi, G.-Y., Wu, R.-J., & Zhang, Y. (2019) · Physics Reports · doi:10.1016/j.physrep.2019.10.004 · Cited by 181 · see citing works
Morby, A. P., Turner, J. S., Huckle, J. W., & Robinson, N. J. (1993) · Nucleic Acids Research · doi:10.1093/nar/21.4.921 · Cited by 173 · see citing works
Maus, I., Koeck, D. E., Cibis, K., Hahnke, S., Kim, Y. S., Langer, T., Kreubel, J., Erhard, M., Bremges, A., Off, S., et al. (2016) · Biotechnology for Biofuels · doi:10.1186/s13068-016-0581-3 · Cited by 167 · see citing works
Jothi, R., Balaji, S., Wüster, A., Grochow, J. A., Gsponer, J. A., Przytycka, T. M., Aravind, L., & Babu, M. M. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.52 · Cited by 162 · see citing works
Domenzain, I., Sánchez, B. J., Anton, M., Kerkhoven, E. J., Millán-Oropeza, A., Henry, C., Siewers, V., Morrissey, J. P., Sonnenschein, N., & Nielsen, J. (2022) · Nature Communications · doi:10.1038/s41467-022-31421-1 · Cited by 154 · see citing works
Xu, Y. Q., Mori, T., Pattanayek, R., Pattanayek, S., Egli, M., & Johnson, C. H. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0404768101 · Cited by 150 · see citing works
Making Sense of Transcription Networks
Sorrells, T. R., & Johnson, A. D. (2015) · Cell · doi:10.1016/j.cell.2015.04.014 · Cited by 143 · see citing works
DeepTFactor: A deep learning-based tool for the prediction of transcription factors
Kim, G. B., Gao, Y., Palsson, B. Ø., & Lee, S. Y. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2021171118 · Cited by 141 · see citing works
Two Antagonistic Clock-Regulated Histidine Kinases Time the Activation of Circadian Gene Expression
Gutu, A., & O’Shea, E. K. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.02.022 · Cited by 131 · see citing works
RegulonDB v12.0: a comprehensive resource of transcriptional regulation in E. coli K-12
Salgado, H., Gama‐Castro, S., Lara, P., Mejía-Almonte, C., Alarcón-Carranza, G., López-Almazo, A. G., Betancourt-Figueroa, F., Peña-Loredo, P., Alquicira-Hernández, S., Ledezma-Tejeida, D., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1072 · Cited by 131 · see citing works
A comprehensive overview and critical evaluation of gene regulatory network inference technologies
Zhao, M., He, W., Tang, J., Zou, Q., & Guo, F. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab009 · Cited by 130 · see citing works
Circadian clock‐protein expression in cyanobacteria: rhythms and phase setting
Xu, Y., Mori, T., & Johnson, C. H. (2000) · The EMBO Journal · doi:10.1093/emboj/19.13.3349 · Cited by 128 · see citing works
Global gene repression by KaiC as a master process of prokaryotic circadian system
Nakahira, Y., Katayama, M., Miyashita, H., Kutsuna, S., Iwasaki, H., Oyama, T., & Kondo, T. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307411100 · Cited by 124 · see citing works
A Hard Day’s Night: Cyanobacteria in Diel Cycles
Welkie, D. G., Rubin, B. E., Diamond, S., Hood, R. D., Savage, D. F., & Golden, S. S. (2018) · Trends in Microbiology · doi:10.1016/j.tim.2018.11.002 · Cited by 124 · see citing works
Electron transport and light-harvesting switches in cyanobacteria
Mullineaux, C. W. (2014) · Frontiers in Plant Science · doi:10.3389/fpls.2014.00007 · Cited by 117 · see citing works
Chen, Y., Gustafsson, J., Rangel, A. E. T., Anton, M., Domenzain, I., Kittikunapong, C., Li, F., Yuan, L., Nielsen, J., & Kerkhoven, E. J. (2024) · Nature Protocols · doi:10.1038/s41596-023-00931-7 · Cited by 117 · see citing works
Fang, X. D., Sastry, A. V., Mih, N., Kim, D., Tan, J., Yurkovich, J. T., Lloyd, C. J., Gao, Y., Yang, L., & Palsson, B. Ø. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1702581114 · Cited by 114 · see citing works
García‐Domínguez, M., Reyes, J. C., & Florencio, F. J. (2000) · Molecular Microbiology · doi:10.1046/j.1365-2958.2000.01789.x · Cited by 107 · see citing works
Topology of molecular interaction networks
Winterbach, W., Mieghem, P. V., Reinders, M. J. T., Wang, H., & de Ridder, D. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-90 · Cited by 106 · see citing works
Circadian rhythms of superhelical status of DNA in cyanobacteria
Woelfle, M. A., Xu, Y. Q., Qin, X., & Johnson, C. H. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706069104 · Cited by 105 · see citing works
Yousef, N., Pistorius, E. K., & Michel, K. (2003) · Archives of Microbiology · doi:10.1007/s00203-003-0618-4 · Cited by 104 · see citing works
Control of electron transport routes through redox-regulated redistribution of respiratory complexes
Liu, L., Bryan, S. J., Huang, F., Yu, J., Nixon, P. J., Rich, P. R., & Mullineaux, C. W. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1120960109 · Cited by 103 · see citing works
Tierrafría, V. H., Rioualen, C., Salgado, H., Lara, P., Gama-Castro, S., Lally, P., Gómez-Romero, L., Peña-Loredo, P., López-Almazo, A. G., Alarcón-Carranza, G., et al. (2022) · Microbial Genomics · doi:10.1099/mgen.0.000833 · Cited by 103 · see citing works
Shinde, S., Singapuri, S. P., Zhang, X., Kalra, I., Liu, X., Morgan‐Kiss, R. M., & Wang, X. (2019) · PLANT PHYSIOLOGY · doi:10.1104/pp.19.01184 · Cited by 102 · see citing works
How to identify essential genes from molecular networks?
del Rio, G., Dirk Koschützki, A., & Coello, G. (2009) · BMC Systems Biology · doi:10.1186/1752-0509-3-102 · Cited by 98 · see citing works
Teixeira, M. C., Viana, R., Palma, M., Oliveira, J. S., Galocha, M., Mota, M. N., Couceiro, D., Pereira, M. G., Antunes, M., Costa, I. V., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1041 · Cited by 96 · see citing works
Colclough, A. L., Scadden, J., & Blair, J. M. A. (2019) · BMC Genomics · doi:10.1186/s12864-019-6075-5 · Cited by 89 · see citing works
Cyanobacterial Hydrogenases and Hydrogen Metabolism Revisited: Recent Progress and Future Prospects
Khanna, N., & Lindblad, P. C. (2015) · International Journal of Molecular Sciences · doi:10.3390/ijms160510537 · Cited by 86 · see citing works
Schwarz, D., Nodop, A., Hüge, J., Purfürst, S., Forchhammer, K., Michel, K., Bauwe, H., Kopka, J., & Hagemann, M. (2011) · PLANT PHYSIOLOGY · doi:10.1104/pp.110.170225 · Cited by 85 · see citing works
Miao, X., Wu, Q., Wu, G., & Zhao, N. (2003) · FEMS Microbiology Letters · doi:10.1111/j.1574-6968.2003.tb11500.x · Cited by 83 · see citing works
Bhardwaj, N., Yan, K., & Gerstein, M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0910867107 · Cited by 81 · see citing works
Hickman, J. W., Kotovic, K. M., Miller, C. R., Warrener, P., Kaiser, B. K., Jurista, T., Budde, M. W., Cross, F., Roberts, J. M., & Carleton, M. O. (2013) · Algal Research · doi:10.1016/j.algal.2013.01.008 · Cited by 79 · see citing works
P2TF: a comprehensive resource for analysis of prokaryotic transcription factors
Ortet, P., Luca, G. D., Whitworth, D. E., & Barakat, M. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-628 · Cited by 79 · see citing works
Taniguchi, Y., Takai, N., Katayama, M., Kondo, T., & Oyama, T. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0909924107 · Cited by 68 · see citing works
Increased Photochemical Efficiency in Cyanobacteria via an Engineered Sucrose Sink
Abramson, B. W., Kachel, B., Kramer, D., & Ducat, D. C. (2016) · Plant and Cell Physiology · doi:10.1093/pcp/pcw169 · Cited by 67 · see citing works
Altaf-Ul-Amine, M., Nishikata, K., Korna, T., Miyasato, T., Shinbo, Y., Arifuzzaman, M., Wada, C., Maeda, M., Oshima, T., Mori, H., et al. (2003) · Proceedings Genome Informatics Workshop/Genome informatics · doi:10.11234/gi1990.14.498 · Cited by 63 · see citing works
Hanaoka, M., Takai, N., Hosokawa, N., Fujiwara, M., Akimoto, Y., Kobori, N., Iwasaki, H., Kondo, T., & Tanaka, K. (2012) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.338251 · Cited by 63 · see citing works
Seki, A., Hanaoka, M., Akimoto, Y., Masuda, S., Iwasaki, H., & Tanaka, K. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m707582200 · Cited by 62 · see citing works
Puszynska, A. M., & O’Shea, E. K. (2017) · eLife · doi:10.7554/elife.23210 · Cited by 59 · see citing works
Oxidation of Translation Factor EF-Tu Inhibits the Repair of Photosystem II
Jimbo, H., Yutthanasirikul, R., Nagano, T., Hisabori, T., Hihara, Y., & Nishiyama, Y. (2018) · PLANT PHYSIOLOGY · doi:10.1104/pp.18.00037 · Cited by 59 · see citing works
Riediger, M., Kadowaki, T., Nagayama, R., Georg, J., Hihara, Y., & Hess, W. R. (2019) · iScience · doi:10.1016/j.isci.2019.04.033 · Cited by 54 · see citing works
Towards next-generation cell factories by rational genome-scale engineering
Yilmaz, S., Nyerges, Á., John van der, O. O. S. T., Church, G. M., & Claassens, N. J. (2022) · Nature Catalysis · doi:10.1038/s41929-022-00836-w · Cited by 54 · see citing works
Nakamura, K., & Hihara, Y. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m606797200 · Cited by 48 · see citing works
Guerra, T., Xu, Y., Bennette, N. B., McNeely, K., Bryant, D. A., & Dismukes, G. C. (2013) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2013.04.005 · Cited by 47 · see citing works
Razaghi‐Moghadam, Z., & Nikoloski, Z. (2020) · npj Systems Biology and Applications · doi:10.1038/s41540-020-0140-1 · Cited by 47 · see citing works
Localized network centrality and essentiality in the yeast–protein interaction network
Park, K., & Kim, D. (2009) · PROTEOMICS · doi:10.1002/pmic.200900357 · Cited by 45 · see citing works
Lee, S., Ryu, J.-Y., Kim, S. Y., Jeon, J.-H., Song, J. Y., Cho, H., Choi, S., Choi, D., de Marsac, N. T., & Park, Y. (2007) · PLANT PHYSIOLOGY · doi:10.1104/pp.107.105023 · Cited by 45 · see citing works
Horiuchi, M., Nakamura, K., Kojima, K., Nishiyama, Y., Hatakeyama, W., Hisabori, T., & Hihara, Y. (2010) · Biochemical Journal · doi:10.1042/bj20100789 · Cited by 43 · see citing works
Piechura, J. R., Amarnath, K., & O’Shea, E. K. (2017) · eLife · doi:10.7554/elife.32032 · Cited by 41 · see citing works
Bolay, P., Muro-Pastor, M. I., Rozbeh, R., Timm, S., Hagemann, M., Florencio, F. J., Forchhammer, K., & Klähn, S. (2021) · mBio · doi:10.1128/mbio.00229-21 · Cited by 39 · see citing works
The Circadian Clock-Related Gene pex Regulates a Negative cis Element in the kaiA Promoter Region
Kutsuna, S., Kondo, T., Ikegami, H., Uzumaki, T., Katayama, M., & Ishiura, M. (2007) · Journal of Bacteriology · doi:10.1128/jb.00835-07 · Cited by 37 · see citing works
The Calvin Benson cycle in bacteria: New insights from systems biology
Hudson, E. P. (2023) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2023.03.007 · Cited by 36 · see citing works
An ATP-sensitive phosphoketolase regulates carbon fixation in cyanobacteria
Lu, K., Chang, C.-W. M., Wang, C.-H., Chen, F. Y.-H., Huang, I. Y., Huang, P.-H., Yang, C., Wu, H.-Y., Wu, W., Hsu, K., et al. (2023) · Nature Metabolism · doi:10.1038/s42255-023-00831-w · Cited by 36 · see citing works
Kato, H., Chibazakura, T., & Yoshikawa, H. (2008) · Bioscience Biotechnology and Biochemistry · doi:10.1271/bbb.70816 · Cited by 35 · see citing works
Schumann, C., Méndez, J. F., Berggren, G., & Lindblad, P. C. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1179607 · Cited by 35 · see citing works
Grund, M., Jakob, T., Wilhelm, C., Bühler, B., & Schmid, A. (2019) · Biotechnology for Biofuels · doi:10.1186/s13068-019-1378-y · Cited by 34 · see citing works
Bolay, P., Schlüter, S., Grimm, S., Riediger, M., Hess, W. R., & Klähn, S. (2022) · New Phytologist · doi:10.1111/nph.18139 · Cited by 34 · see citing works
Labella, J. I. V., Obrebska, A. A., Espinosa, J., Salinas, P., Forcada‐Nadal, A., Tremiño, L., Rubio, V., & Contreras, A. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.01677 · Cited by 31 · see citing works
Fleming, K. E., & O’Shea, E. K. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.11.049 · Cited by 31 · see citing works
KBoost: a new method to infer gene regulatory networks from gene expression data
Iglesias-Martinez, L. F., Kegel, B. D., & Kölch, W. (2021) · Scientific Reports · doi:10.1038/s41598-021-94919-6 · Cited by 29 · see citing works
Gärtner, K., Klähn, S., Watanabe, S., Mikkat, S., Scholz, I., Hess, W. R., & Hagemann, M. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.01233 · Cited by 28 · see citing works
Ribosome Profiling of Synechocystis Reveals Altered Ribosome Allocation at Carbon Starvation
Karlsen, J., Asplund‐Samuelsson, J., Thomas, Q. A., Jahn, M., & Hudson, E. P. (2018) · mSystems · doi:10.1128/msystems.00126-18 · Cited by 23 · see citing works
Proteome allocation is linked to transcriptional regulation through a modularized transcriptome
Patel, A., McGrosso, D., Hefner, Y., Campeau, A., Sastry, A. V., Maurya, S. R., Rychel, K., Gonzalez, D. J., & Palsson, B. Ø. (2024) · Nature Communications · doi:10.1038/s41467-024-49231-y · Cited by 22 · see citing works
Network inference with ensembles of bi-clustering trees
Pliakos, K., & Vens, C. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3104-y · Cited by 21 · see citing works
Hoffmann, U. A., Heyl, F., Rogh, S. N., Wallner, T., Backofen, R., Hess, W. R., Steglich, C., & Wilde, A. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab1161 · Cited by 19 · see citing works
Escorcia-Rodríguez, J. M., Gaytan-Nuñez, E., Hernandez-Benitez, E. M., Zorro-Aranda, A., Tello-Palencia, M. A., & Freyre-González, J. A. (2023) · bioRxiv · doi:10.3389/fgene.2023.1143382 · Cited by 18 · see citing works
Fast and accurate inference of gene regulatory networks through robust precision matrix estimation
Passemiers, A., Moreau, Y., & Raimondi, D. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac178 · Cited by 16 · see citing works
Assessing regulatory features of the current transcriptional network of Saccharomyces cerevisiae
Monteiro, P. T., Pedreira, T., Galocha, M., Teixeira, M. C., & Chaouiya, C. (2020) · Scientific Reports · doi:10.1038/s41598-020-74043-7 · Cited by 15 · see citing works
A nitrogen stress-inducible small RNA regulates CO2 fixation in Nostoc
Brenes‐Álvarez, M., Olmedo‐Verd, E., Vioque, A., & Muro-Pastor, A. M. (2021) · PLANT PHYSIOLOGY · doi:10.1093/plphys/kiab309 · Cited by 13 · see citing works
Zorro-Aranda, A., Escorcia-Rodríguez, J. M., González-Kise, J. K., & Freyre-González, J. A. (2022) · Scientific Reports · doi:10.1038/s41598-022-06658-x · Cited by 13 · see citing works
Santos‐Merino, M., Sakkos, J. K., Singh, A. K., & Ducat, D. C. (2023) · Metabolic Engineering · doi:10.1016/j.ymben.2023.11.001 · Cited by 13 · see citing works
Shin, J., Zielinski, D. C., & Palsson, B. Ø. (2024) · Metabolic Engineering · doi:10.1016/j.ymben.2024.05.007 · Cited by 12 · see citing works
Cantrell, M., Cano, M., Sebesta, J., Paddock, T., Xiong, W., Chou, K., & Yu, J. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1124274 · Cited by 11 · see citing works
Gilliam, A., Sadler, N., Li, X., García-Jiménez, M. G., Johnson, Z., Veličković, M., Kim, Y., Feng, S., Qian, W., Cheung, M. S., et al. (2025) · Microbial Cell Factories · doi:10.1186/s12934-025-02665-5 · Cited by 7 · see citing works
Self-citationPrediction of DNA-Binding Transcription Factors in Bacteria and Archaea Genomes
Ledesma, L., Hernandez-Guerrero, R., & Pérez‐Rueda, E. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2413-5_7 · Cited by 6 · see citing works
Chen, C., Lu, D., Sun, H., Zhang, K., Yin, L., Luan, G., Liu, Y., Ma, H., & Lü, X. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.133632 · Cited by 4 · see citing works
Saito, M., Watanabe, S., Nimura-Matsune, K., Yoshikawa, H., & Nakamoto, H. (2020) · The Journal of General and Applied Microbiology · doi:10.2323/jgam.2020.02.001 · Cited by 3 · see citing works
Cheung, M. S., Mejı́a-Rodrı́guez, D., Kim, H. S., Sadler, N., Li, X., Bohutskyi, P., Valiev, M., & Qian, W. (2024) · Biophysical Journal · doi:10.1016/j.bpj.2023.11.2147 · Cited by 2 · see citing works
Self-citationEnhancing gene regulatory networks inference through hub-based data integration
Naseri, A., Sharghi, M., & Hasheminejad, S. M. H. (2021) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2021.107589 · Cited by 1 · see citing works
Correlations reveal the hierarchical organization of biological networks with latent variables
Häusler, S. (2024) · Communications Biology · doi:10.1038/s42003-024-06342-y · Cited by 1 · see citing works
Johnson, C., Johnson, Z., Mackey, L. S., et al. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2410.09346
Self-citation
Flagged first, then by citations
Research works printed but not linked: 2
- Ghamrawi N. Mccallum A. (2005). Collective multi-label classification. Proceedings of the 14th Acm international conference on information and knowledge management. Bremen, Germany: Association for Computing Machinery.
- Newman M. E. (2008). The mathematics of networks. The new palgrave encyclopedia of economics, no. 2, pp. 1–12.
Cited by
Sorted by citations
Sarkar, S., Fossen, E. M. V., Li, X., Zhang, T., Feng, S., Prozapas, V. N., Ludovico, I. D., Shouaib, A., Hutchinson, C., Sadler, N., et al. (2025) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2025.101443 · Cited by 6 · see citing works
Self-citationJohnson, C., Johnson, Z., Mackey, L. S., Li, X., Sadler, N., Zhang, T., Qian, W., Bohutskyi, P., Feng, S., & Cheung, M. S. (2025) · PRX Life · doi:10.1103/l2dp-kw2t · Cited by 6 · see citing works
Self-citationInterfacing solar energy with bacterial metabolism for sustainable chemical synthesis
Trotter, C. L., Clouston, K., Steele, J. F. C., Marlow, L., & Wallace, S. C. (2026) · Nature Reviews Clean Technology · doi:10.1038/s44359-025-00141-2 · Cited by 5 · see citing works
From photosynthetic electron flow to gene regulation: redox signal transduction in cyanobacteria
Johnson, Z., Yang, B., & Bohutskyi, P. (2026) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuag030 · Cited by 2 · see citing works
Self-citationModular cyanobacterial regulatory architecture enables dynamic graded responses to oxidative stressPreprint
Johnson, Z., Sadler, N., García-Jiménez, M. G., Gilliam, A., Hill, E. A., Qian, W., Cheung, M. S., & Bohutskyi, P. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.21.665879 · Cited by 2 · see citing works
Self-citationJohnson, Z., Sadler, N., Garcia, M., Li, X., Rozum, J. C., Anderson, L. N., Zhang, T., Feng, S., Qian, W., Cheung, M. S., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.15.718746 · Cited by 2 · see citing works
Self-citationWalshe, J., & Saha, S. K. (2026) · Current Issues in Molecular Biology · doi:10.3390/cimb48060638 · Cited by 1 · see citing works
“From a biotechnological standpoint, this endogenous circadian regulation has also garnered interest in the metabolic engineering, as it can affect the timing and efficiency of engineered metabolic pathways [62].”
Jakkula, B. K., & Shyam, P. (2026) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2026.109012 · Cited by 1 · see citing works
Bohutskyi, P., DiMura, R., Johnson, Z., Li, R., Anderson, D., & Cheung, M. S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.09.731130 · Cited by 1 · see citing works
Self-citationFadhal, E. (2025) · OBM Genetics · doi:10.21926/obm.genet.2504312
Keerthi, G. M., Mallikarjuna, M. G., Lohithaswa, H. C., Kumar, M. B. A., Jha, S. K., Mudhale, A., Bisht, D. S., & Chinnusamy, V. (2026) · Functional Plant Biology · doi:10.1071/fp26030
Johnson, Z., Sadler, N., Garcia, M., Gilliam, A., Hill, E. A., Li, X., Trejo, J. B., Qian, W., Cheung, M. S., & Bohutskyi, P. (2026) · iScience · doi:10.1016/j.isci.2026.117861
Self-citation
- Authors
- Johnson, Z., Anderson, D., Cheung, M. S., & Bohutskyi, P.
- Affiliations
- Pacific Northwest National Laboratory (US)
- Corresponding author
- Bohutskyi, Pavlo
- Venue
- Frontiers in Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2025-03-26
- Volume
- 16
- Pages
- 1569559-1569559
- ISSN
- 1664-302X (ISSN-L)
- PMC
- PMC11979508
- OpenAlex
- W4408843983
- Cited by
- 12
- References
- 111
- Citations by year
- 2026: 8 · 2025: 4
- FWCI
- 5.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Microbiology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Energy (DE-AC05–76RL01830, 76RL01830, AC05-76RL01830)
- Battelle (AC05-76RL01830, DE- AC05-76RL01830, DE-AC05, 76RL01830)
- Office of Science (DE‐AC05‐76 RL01830)
- Workforce Development for Teachers and Scientists (DE-AC05-76RL01830)
- Pacific Northwest National Laboratory (DEAC0576RL01830, 76RL01830, AC05-76RL01830)
- Topics
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- Synechococcus elongatus PCC 7942, circadian regulation, gene regulatory networks, network centrality, transcription factors, HIMA, TetR, photosynthesis, carbon and nitrogen metabolism, glycogen mobilization, redox metabolism, cyanobacteria, CO2 conversion
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
