Transcriptome-Proteome Correlations and Modeling of Multi-Stressor

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Transcriptome-Proteome Correlations and Modeling of Multi-Stressor bioRxiv preprint doi: https://doi.org/10.1101/2021.06.22.449505; this version posted June 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 2 3 Why Environmental Biomarkers Work: Transcriptome-Proteome Correlations and 4 Modeling of Multi-Stressor Experiments in the Marine Bacterium Trichodesmium 5 Nathan G. Walworth1+, Mak A. Saito2+*, Michael D. Lee3,4, Matthew R. McIlvin2, Dawn M. 6 Moran2, Riss M. Kellogg2, Fei-Xue Fu1, David A. Hutchins1, and Eric A. Webb1* 7 8 1 Marine and Environmental Biology, Department of Biological Sciences, University of Southern 9 California, Los Angeles, CA, 90089, USA. 10 2Marine Chemistry and Geochemistry Department, Woods Hole Oceanographic Institution, 11 Woods Hole, MA 02543, USA 12 3Blue Marble Space Institute of Science, Seattle, WA, 98104, USA 13 14 4Exobiology Branch, NASA Ames Research Center, Moffett Field, CA, 94035, USA 15 16 +Co-First Authors 17 18 19 20 *Corresponding authors: Mak Saito [email protected] and Eric A. Webb [email protected]; 21 June 22, 2021 22 23 24 Keywords: 25 Transcriptome-proteome, environmental biomarkers, marine microbes, 26 Trichodesmium, metaproteomics 27 28 bioRxiv preprint doi: https://doi.org/10.1101/2021.06.22.449505; this version posted June 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 29 30 31 Abstract 32 Ocean microbial communities are important contributors to the global biogeochemical reactions 33 that sustain life on Earth. The factors controlling these communities are being increasingly 34 explored through the use of metatranscriptomic and metaproteomic environmental biomarkers, 35 despite ongoing uncertainty about the coherence between RNA and protein signals. Using 36 published proteomes and transcriptomes from the abundant colony-forming cyanobacterium 37 Trichodesmium (strain T. erythraeum IMS101) grown under varying Fe and/or P limitation 38 and/or co-limitation in low and high CO2, we observed robust correlations of stress induced 39 proteins and RNAs (i.e., those involved in transport and homeostasis) that can yield useful 40 information on nutrient status under low and/or high CO2. Conversely, transcriptional and 41 translational correlations of many other central metabolism pathways exhibit broad discordance. 42 A cellular RNA and protein production/degradation model demonstrates how biomolecules with 43 small initial inventories, such as environmentally responsive proteins, can achieve large 44 increases in fold-change units, as opposed to those with higher basal expression and inventory 45 such as metabolic systems. Microbial cells, due to their close proximity to the environment, tend 46 to show large adaptive responses to environmental stimuli in both RNA and protein that result in 47 transcript-protein correlations. These observations and model results demonstrate a multi-omic 48 coherence for environmental biomarkers and provide the underlying mechanism for those 49 observations, supporting the promise for global application in detecting responses to 50 environmental stimuli in a changing ocean. 51 52 53 bioRxiv preprint doi: https://doi.org/10.1101/2021.06.22.449505; this version posted June 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 54 Introduction 55 A recurring question in the interpretation of transcriptome and proteome datasets is the 56 extent to which they co-vary. Messenger RNA (mRNA) and protein levels have been reported to 57 generally be uncorrelated within a single cell, and only modestly correlated in populations of 58 cells, due to differences in half lives and degradation rates or phase variation within a population, 59 respectively 1. It has also been shown that genes and their corresponding proteins associated with 60 different cellular processes (e.g., core central vs stress metabolism) may retain varying degrees 61 of correlation 2. While observation of correlations in larger organisms may be challenging due to 62 internal tissues being more remote environmental signals, microbes due to their small size and 63 immersion within the environment often maintain multiple adaptive response capabilities to 64 common environmental stimuli. Microbial datasets with transcriptomic and proteomic methods 65 applied to the same experiment(s) are becoming more common and hence could aid in detection 66 and interpretation of key environmental processes. In recent years, concurrent measurements of 67 transcripts and proteins have been conducted in marine microbes such as Pelagibacter 3, 68 Prochlorococcus 4, the marine diatom Thalassiosira pseudonana 5, the brown alga Aureococcus 69 anophagefferens 6, the polar alga Phaeocystis antarctica 7, and the diazotrophic cyanobacterium 70 Trichodesmium 8. These studies also observed varying extents of transcriptome-proteome 71 coupling, with correlations observed particularly for genes involved in responding to 72 environmental stresses, such as P, Fe, or vitamin B12 limitation. Despite these efforts, there is 73 arguably a lack of consensus in the marine ecology community regarding the extent that RNA 74 transcripts and proteins should correlate, with many having the opinion that correlations do not 75 occur. 76 In this study we synthesize the results from a number of Trichodesmium transcriptome- 77 proteome datasets across a spectrum of conditions to understand their transcriptional and 78 translational responses on a mechanistic level. Trichodesmium spp. are filamentous, buoyant 79 microorganisms that can commonly grow in macroscopic colonies in close association with other 80 microbes and have the capability to form massive blooms 9. Given their ability to fix both carbon 81 and nitrogen, Trichodesmium spp. have relevance to both global productivity and 82 biogeochemistry 10,11. Together with other marine microbes, they can impact both ecosystem 83 stability and climate feedbacks 12. Trichodesmium is among one of several oceanic cyanobacteria 84 that are globally significant sources of N 10,13, as well as unicellular forms (Crocosphaera spp., bioRxiv preprint doi: https://doi.org/10.1101/2021.06.22.449505; this version posted June 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 85 Candidatus Atelocyanobacterium thalassa and Cyanothece) and other heterocystous, symbiotic 86 forms 11, that can have relatively high cell numbers 14 and biogeochemical importance 15,16. 87 Trichodesmium is considered one of the most important diazotrophs in many tropical and 88 subtropical regimes 10,17. As a result, research emphasis has been placed on developing field- 89 ready, nutrient-limitation/stress markers to define the factors that control growth and N2 fixation 90 in this important genus. These combined efforts have shown that iron (Fe) and phosphorus (P) 91 primarily limit Trichodesmium across much of the global oceans 10,11,18,19. However, 92 comparatively fewer studies have been conducted examining the interactions among future high 93 CO2 concentrations, Fe, and P in the context of holistic, molecular physiology. 94 A motivation in understanding the dynamics of RNA and protein responses is the 95 interpretation of natural microbial populations, and in particular the expression of genes that can 96 provide clues to ecological or biogeochemical processes at play. Advances in sequencing (e.g., 97 metagenomics/metatranscriptomics) and mass spectrometry (e.g., proteomics) technologies have 98 enabled worldwide microbial characterizations from different biogeochemical regimes (e.g., 99 Global Ocean Sampling Dataset 20). While these data have revolutionized how we think about 100 microbially mediated processes, extrapolating biogeochemistry from relative abundances in 101 metagenome data may result in biased interpretation. For example, it is now recognized that 102 globally abundant microbial species initially identified via metagenomics may not necessarily be 103 dominant members of the transcriptionally active microbial community that is primarily 104 responsible for biogeochemical turnover 21. While metagenomics studies serve as powerful 105 hypothesis-generating datasets and have unmasked previously underappreciated ecosystem 106 processes (e.g., proteorhodopsin diversity 20,22), they have also underscored the need to 107 understand the dynamics of intracellular molecular processes in the context of organismal 108 physiology both in the laboratory and field. Thus, it is important to investigate molecular 109 dynamics of biogeochemically-important microbes under differing nutrient and temporal regimes 110 to resolve mRNA-protein dynamics that ultimately drive important biogeochemical processes. 111 Here we focus primarily on N2 fixation. In past studies we characterized the physiological and 112 evolutionary responses of the globally important, photoautotrophic, N2-fixing cyanobacterium,
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