key: cord-1002576-urfewri7 authors: Costa, José Hélio; Mohanapriya, Gunasekaran; Revuru, Bharadwaj; Noceda, Carlos; Lima Thiers, Karine Leitão; Aziz, Shahid; Srivastava, Shivani; Oliveira, Manuela; Gupta, Kapuganti Jagadis; Kumari, Aprajita; Sircar, Debabrata; Kumar, Sarma Rajeev; Achra, Arvind; Sathishkumar, Ramalingam; Adholeya, Alok; Arnholdt-Schmitt, Birgit title: ROS/RNS balancing, aerobic fermentation regulation and cell cycle control – a complex early trait (‘CoV-MAC-TED’) for combating SARS-CoV-2-induced cell reprogramming date: 2021-06-11 journal: bioRxiv DOI: 10.1101/2021.06.08.447491 sha: f7b82404a2a95cbf785eb0fe5c6a28b54872c2d5 doc_id: 1002576 cord_uid: urfewri7 In a perspective entitled ‘From plant survival under severe stress to anti-viral human defense’ we raised and justified the hypothesis that transcript level profiles of justified target genes established from in vitro somatic embryogenesis (SE) induction in plants as a reference compared to virus-induced profiles can identify differential virus signatures that link to harmful reprogramming. A standard profile of selected genes named ‘ReprogVirus’ was proposed for in vitro-scanning of early virus-induced reprogramming in critical primary infected cells/tissues as target trait. For data collection, the ‘ReprogVirus platform’ was initiated. This initiative aims to identify in a common effort across scientific boundaries critical virus footprints from diverse virus origins and variants as a basis for anti-viral strategy design. This approach is open for validation and extension. In the present study, we initiated validation by experimental transcriptome data available in public domain combined with advancing plant wet lab research. We compared plant-adapted transcriptomes according to ‘RegroVirus’ complemented by alternative oxidase (AOX) genes during de novo programming under SE-inducing conditions with in vitro corona virus-induced transcriptome profiles. This approach enabled identifying a major complex trait for early de novo programming during SARS-CoV-2 infection, called ‘CoV-MAC-TED’. It consists of unbalanced ROS/RNS levels, which are connected to increased aerobic fermentation that links to alpha-tubulin-based cell restructuration and progression of cell cycle. We conclude that anti-viral/anti-SARS-CoV-2 strategies need to rigorously target ‘CoV-MAC-TED’ in primary infected nose and mouth cells through prophylactic and very early therapeutic strategies. We also discuss potential strategies in the view of the beneficial role of AOX for resilient behavior in plants. Furthermore, following the general observation that ROS/RNS equilibration/redox homeostasis is of utmost importance at the very beginning of viral infection, we highlight that ‘de-stressing’ disease and social handling should be seen as essential part of anti-viral/anti-SARS-CoV-2 strategies. In a perspective entitled 'From plant survival under severe stress to anti-viral human defense' we raised and justified the hypothesis that transcript level profiles of justified target genes established from in vitro somatic embryogenesis (SE) induction in plants as a reference compared to virus-induced profiles can identify differential virus signatures that link to harmful reprogramming. A standard profile of selected genes named We conclude that anti-viral/anti-SARS-CoV-2 strategies need to rigorously target 'CoV-MAC-TED' in primary infected nose and mouth cells through prophylactic and very early therapeutic strategies. We also discuss potential strategies in the view of the beneficial role of AOX for resilient behavior in plants. Furthermore, following the general observation that ROS/RNS equilibration/redox homeostasis is of utmost importance at the very beginning of viral infection, we highlight that 'de-stressing' disease and social handling should be seen as essential part of antiviral/anti-SARS-CoV-2 strategies. (number of sequences in each database X number of nucleotides of each gene). According In Figure 1A .2, the calculated IU of ADH were multiplied by a factor (5) Figure 423 legend. In the main text, we focus on the principle line of this research. Our results demonstrated that endophytes can interfere with the redox biology of the host 533 system related to the initiation of cell proliferation (Fig.1A.4) . Plant-mycorrhizal fungi 534 interaction is suggested to involve AOX from both symbiotic partners (102) (103) (104) 106) . whether AOX could be useful in therapy as proposed for mitochondrial respiratory 555 deficiency diseases (110) (111) (112) (113) (114) (115) ) will, in our view, crucially depend on its adaptive (positive 556 and negative) regulation, which includes also interaction with endophytes. In this context, 557 it is also pertinent to mention that recently an AOX-degrading protein has been discovered 558 that might be added as a tool in potential AOX-based therapies (85). In search for similarities between the beneficial role of AOX in plants in relation to 561 adaptive oxidative stress level equilibration relevant for virus tolerance and that of natural 562 agents in human cells, melatonin seems to be a strong candidate. Melatonin is a natural 563 hormone in humans, which has also been recognized as a phytohormone (116) . It is 564 produced in most organs and cells (70, (116) (117) (118) (119) , including also human salivary gland cells 565 (120) . Melatonin is known to possess anti-oxidant properties and shows high fluctuation in 566 its cellular concentration. In plants, melatonin seems not to enhance AOX transcription 567 (116) as it has been shown for auxin (75) . In turn melatonin interacts with other enzymes 568 involved in ROS/RNS balancing and was suggested to be in plants mainly involved in 569 biotic stress defense rather than in growth regulation (116) . Further, melatonin was 570 reported to enhance the induction of adventitious roots through interaction with auxin-571 mediated signaling, which suggests a role for melatonin also in early reprogramming (121) . All evidence put together, it could be suggested that melatonin might substitute early anti-573 oxidant function of AOX during reprogramming (75, 99, 122) . By looking at the CoV-infected human cells of various origins ( Fig. 2A and 2B) . Related to MERS-CoV-596 infected MRC5 cells, it can be seen that ASMT transcript levels were increasing dependent 597 on MOI level and infection time (Fig. 2B) . However, we did not identify ASMT transcripts This is the first research to start validating hypothesis and wider perspective published by 663 a non-institutional, voluntary competence focus under the title 'From plant survival under 664 severe stress to anti-viral human defense -a perspective that calls for common efforts' (21, 665 in press). The possibilities of using controlled pH to support these strategies by early testing and 692 treatment, should, in our view, be explored with priority. Cell reprogramming and its 693 relation also to cell death (140) , changes in anti-oxidant activity also related to AOX (141) (142) (143) , aerobic fermentation (144) and viral infections (144) (145) (146) (147) (148) are all influenced or indicated by extracellular pH. Extracellular pH might also by its interaction with 696 intracellular pH influence complex tasting, which includes not only sour tasting (149, 150) . The relation between smell and pH is, to our knowledge, not sufficiently explored yet. However, SARS-CoV-2 entry proteins were found to be expressed in olfactory epithelial 699 cells (151) . Kinase (non-significant) and G6PDH (significant) as well as mt-MDH2 (non-significant). In this situation, LDH transcript level was found equal to control. However, transcript 916 levels for SOD2 as a biomarker for oxidative stress regulation was slightly increased (non- in part less for this experimental system, which can be responsible for missing 956 significances). 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The graphical 1122 representation of the values is given in figure 1B.2. Number of biological replicates PFK (Phosphofructokinase), GAPDH (Glyceraldehyde-3-1126 phosphate dehydrogenase), G6PDH (glucose-6-phosphate dehydrogenase SNRK (sucrose non-fermenting related kinase), mTOR (mammalian target of rapamycin E2F (Transcription factor E2F), IRF9 (interferon regulatory factor 9), IRF3 (interferon 1130 regulatory factor 3), NFKB1 (nuclear factor kappa B1), NFKB-RelA Caspase Ex (Executioner caspases), Bcl-1132 xL, (B-cell lymphoma-extra large) ACE2 (Angiotensin-converting enzyme 2) Supplementary Table S8: Mean values ± SE of transcript abundance of genes in primary 1136 human lung epithelial cancer cells infected with MERS-CoV. The graphical 1137 representation of the values is given SOD2 (superoxide 1139 dismutase 2), GPX (glutathione peroxidase), GSR (glutathione reductase), NOS3 (nitric 1140 oxide synthase), ADH5 (alcohol dehydrogenase 5), PFK (Phosphofructokinase), GAPDH 1141 (Glyceraldehyde-3-phosphate dehydrogenase) Cyt-MDH1 (Cytosolic malate dehydrogenase 1), mt-MDH2 1143 (mitochondrial malate dehydrogenase), SNRK (sucrose non-fermenting related kinase IRF3 (interferon regulatory factor 3), NFKB1 (nuclear 1146 factor kappa B1), NFKB-RelA (nuclear factor Kappa B-RelA) The graphical 1151 representation of the values is given in figure 1B.4 a. Number of biological replicates: 3. dismutase 2), GPX (glutathione peroxidase), GSR (glutathione reductase), ADH5 1154 (alcohol dehydrogenase 5), PFK (Phosphofructokinase), GAPDH (Glyceraldehyde-3-1155 phosphate dehydrogenase), G6PDH (glucose-6-phosphate dehydrogenase SNRK (sucrose non-fermenting related kinase), mTOR (mammalian target of rapamycin E2F (Transcription factor E2F), IRF9 (interferon regulatory factor 9), IRF3 (interferon 1159 regulatory factor 3), NFKB1 (nuclear factor kappa B1) Caspase Ex (Executioner caspases), Bcl-1161 xL, (B-cell lymphoma-extra large) Supplementary Table S10: Mean values ± SE of transcript abundance of genes in 1164 primary human fetal lung fibroblast cells infected with SARS-CoV. The graphical 1165 representation of the values is given in figure 1B.4 b. Number of biological replicates PFK (Phosphofructokinase), GAPDH (Glyceraldehyde-3-1169 phosphate dehydrogenase), G6PDH (glucose-6-phosphate dehydrogenase E2F (Transcription factor E2F), IRF9 (interferon regulatory factor 9