Organelle Crosstalk Regulators Are Regulated in Diseases, Tumors, and Regulatory T Cells: Novel Classification of Organelle Crosstalk Regulators

To examine whether the expressions of 260 organelle crosstalk regulators (OCRGs) in 16 functional groups are modulated in 23 diseases and 28 tumors, we performed extensive -omics data mining analyses and made a set of significant findings: (1) the ratios of upregulated vs. downregulated OCRGs are 1:2.8 in acute inflammations, 1:1 in metabolic diseases, 1:1.2 in autoimmune diseases, and 1:3.8 in organ failures; (2) sepsis and trauma-upregulated OCRG groups such as vesicle, mitochondrial (MT) fission, and mitophagy but not others, are termed as the cell crisis-handling OCRGs. Similarly, sepsis and trauma plus organ failures upregulated seven OCRG groups including vesicle, MT fission, mitophagy, sarcoplasmic reticulum–MT, MT fusion, autophagosome–lysosome fusion, and autophagosome/endosome–lysosome fusion, classified as the cell failure-handling OCRGs; (3) suppression of autophagosome–lysosome fusion in endothelial and epithelial cells is required for viral replications, which classify this decreased group as the viral replication-suppressed OCRGs; (4) pro-atherogenic damage-associated molecular patterns (DAMPs) such as oxidized low-density lipoprotein (oxLDL), lipopolysaccharide (LPS), oxidized-1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (oxPAPC), and interferons (IFNs) totally upregulated 33 OCRGs in endothelial cells (ECs) including vesicle, MT fission, mitophagy, MT fusion, endoplasmic reticulum (ER)–MT contact, ER– plasma membrane (PM) junction, autophagosome/endosome–lysosome fusion, sarcoplasmic reticulum–MT, autophagosome–endosome/lysosome fusion, and ER–Golgi complex (GC) interaction as the 10 EC-activation/inflammation-promoting OCRG groups; (5) the expression of OCRGs is upregulated more than downregulated in regulatory T cells (Tregs) from the lymph nodes, spleen, peripheral blood, intestine, and brown adipose tissue in comparison with that of CD4+CD25− T effector controls; (6) toll-like receptors (TLRs), reactive oxygen species (ROS) regulator nuclear factor erythroid 2-related factor 2 (Nrf2), and inflammasome-activated regulator caspase-1 regulated the expressions of OCRGs in diseases, virus-infected cells, and pro-atherogenic DAMP-treated ECs; (7) OCRG expressions are significantly modulated in all the 28 cancer datasets, and the upregulated OCRGs are correlated with tumor immune infiltrates in some tumors; (8) tumor promoter factor IKK2 and tumor suppressor Tp53 significantly modulate the expressions of OCRGs. Our findings provide novel insights on the roles of upregulated OCRGs in the pathogenesis of inflammatory diseases and cancers, and novel pathways for the future therapeutic interventions for inflammations, sepsis, trauma, organ failures, autoimmune diseases, metabolic cardiovascular diseases (CVDs), and cancers.

With progress of super-multiplexed optical imaging and barcoding (48) and other system-level spectral imaging and analyses (49,50), it has been recognized that the crosstalk between mitochondria and other organelles, such as lysosomes, peroxisomes, and the endoplasmic reticulum (ER) (51), is mediated by transcriptional programs and other signaling mechanisms (52). Organelle exchange materials including lipids, ions, and proteins at the membrane contact sites (MCSs), which may be different from membrane trafficking between organelles by vesiculotubular carriers regulated by Rab GTPase (53). Organelle interactions also likely mediate organelle dysfunction downstream of MT impairments (54). In addition, external or internal stress activates several well-orchestrated processes aimed at either restoring cellular homeostasis or committing cell death (55). These processes include unfolded protein response (UPR) in ER and mitochondria (56), autophagy, hypoxia, and MT function, which underlie the ER stress response (57), suggesting that cellular pathological responses may be mediated in organelle crosstalk mechanisms (58). Accordingly, alterations to these networks, such as impaired ER-mitochondria MCSs, have been linked to several diseases such as neurodegeneration (59,60), CVD (61), diabetes (62), kidney diseases (63,64), and cancers (65,66).

Expression Profile of Organelle Crosstalk Regulator Genes in Microarray Data From Patients With Various Inflammatory Diseases and Cancers
The 25 microarray datasets of AI and injuries, ADs, MDs, and CVDs ( Table 2); one microarray dataset of Middle East respiratory syndrome coronavirus (MERS-CoV)-infected human microvascular ECs; one microarray dataset of severe respiratory syndrome coronavirus (SARS-CoV)-infected human airway epithelial cells; two microarray datasets of influenza virus-infected lung epithelial cells, Calu-3 cells (non-smallcell lung cancer cell line), and human umbilical vein ECs (HUVECs); one microarray of Kaposi sarcoma-associated herpes virus-infected primary human dermal ECs ( Table 3); six microarrays of ECs treated by pro-atherogenic DAMPs ( Table 4); six microarray datasets of Treg cells ( Table 5); 15 microarrays of Treg regulator deficiency ( Table 6); six microarrays of TLR deficiencies ( Table 7); one microarray of ROS negative regulator nuclear factor erythroid 2-related factor 2 (Nrf2) deficiency ( Table 8); and two microarrays of caspase-1 deficiency ( Table 9) were collected from National Institutes of Health (NIH)-National Center for Biotechnology Information (NCBI)-Gene Expression Omnibus (GEO) databases (https://www.ncbi.nlm. nih.gov/gds/) and analyzed with an online software GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/). In addition, gene expression data from 28 cancers were analyzed with the Gene Expression Profiling Interactive Analysis (GEPIA2) database (http://gepia2.cancer-pku.cn/#index), in which dataset sources were from The Cancer Genome Atlas (TCGA)/Genotype-Tissue Expression (GTEx) data (Table 10). Furthermore, 19 microarray datasets of oncogene and tumor suppressor deficiencies were collected from NCBI-GEO and analyzed with GEO2R ( Table 11). The differentially expressed OCRGs and their changes in all microarrays and TCGA datasets are listed in Supplementary Tables 1, 2. The original microarray experiments used different cells, which prevented us from comparing the effects of disease conditions in regulating OCRGs in the same cell types. Of note, our approach was well-justified. For example, as a common practice, we (23) and others (72) often studied gene expression in non-ideal heterogeneous peripheral blood mononuclear cell (PBMC) populations in pathophysiological conditions, which are actually composed of many cell types (also see the Discussion section).

Metascape Pathway Analysis
We utilized Metascape Pathway Analysis (MPA; http:// metascape.org/gp/index.html#/main/step1) (73) to characterize molecular and cellular functions related to the identified genes in our microarray analysis. Differentially expressed genes were identified and uploaded into MPA for analysis. The core and pathways analysis was used to identify molecular and cellular pathways, as we have previously reported (23).

Protein-Protein Interaction Analysis
Protein-protein interaction (PPI) networks were generated from STRING database (https://string-db.org/). Enrichment analysis results of the shared gene and top 10 connected proteins were downloaded and visualized by using Cytoscape software 3.7.2 (https://cytoscape.org/) (74).

Statistical Analysis of Microarray Data
Twelve housekeeping genes including CHMP2A, EMC7, GPI, PSMB2, PSMB4, RAB7A, SNRPD3, VPS29, VCP, ACTB, RPL27, and OAZ1 (Supplementary Table 3 of Housekeeping Genes) in all 85 GEO datasets regardless of species were chosen for this study. The housekeeping gene list was extracted from the list provided by Eisenberg and de Jonge (77,78). Briefly, the mean fold change (FC) of housekeeping genes between treatment and control groups varies from 0.72 to 1.55. As this variation was out of the range of FC < 0.5 or FC > 2 (|log2FC| > 1), we concluded that the datasets were of high quality. The target genes with expression changes more than 2-fold in microarrays were defined as the upregulated genes, while genes with their expression decreased more than 2-fold in microarrays were defined as downregulated genes (p < 0.05, |log2FC| > 1).

The Ratios of Upregulated vs. Downregulated Organelle Crosstalk Regulators in Diseases Are Different, and Differentially Expressed Organelle Crosstalk Regulators Are Shared in Diseases
We hypothesized that pathological conditions significantly modulate the expressions of organelle crosstalk regulators in disease-specific and cell type-specific manner. To examine this hypothesis, we collected 260 organelle crosstalk regulators (regulatomic genes and OCRGs) in 16 groups (Figure 1) and 1 | Two hundred sixty organelle crosstalk regulators (OCRGs) were searched from three databases such as National Center for Biotechnology Information (NCBI), Gene Set Enrichment Analysis (GSEA), and the Human Protein Atlas (HPA) website.

Gene symbol Source
To determine whether among 260 OCRGs upregulated and downregulated regulators were shared in disease categories, we performed a Venn diagram analysis. As shown in Figures 2A-D, in 26 upregulated OCRGs in AIs, the upregulation of two regulators, SERPINA1 and AZU1, was shared among acute respiratory distress syndrome (ARDS), sepsis, and trauma; upregulation of CD24 and FKBP8 was shared among ARDS and trauma; and upregulation of GRN was shared between sepsis and trauma. In 46 upregulated OCRGs in MDs, upregulation of two regulators VAMP8 and SERPINA1 was shared between obese and atherosclerosis; and two upregulated regulators DNM2 and MTFP1 were shared between T2D and atherosclerosis. In 80 upregulated OCRGs in ADs, three regulators (i.e., GPRC5A, LAMP3, and MX2) were shared among RA, autoimmune skin disease (ASD), and inflammatory bowel disease (IBD); three regulators (i.e., OSBPL8, SERPINA1, and MX1) were shared between RA and IBD; seven regulators (i.e., PPARG, MYO19, MAP1LC3A, TLR9, NACC1, P4HA2, and SAMD9) were shared between RA and ASD; and four regulators (i.e., POU2F2, VMP1, ATP11A, and KDR) were shared between ASD and IBD. In 39 upregulated OCRGs in OFs, two regulators (i.e., BAX and GRN) were shared between CKD hemodialysis and hepatitis B virus liver failure. These results have demonstrated that first, the  (6), and ER-PM junctions (10 genes); endosome-Golgi trafficking (four genes); autophagosome-lysosome fusion (four genes); autophagosome-endosome/lysosome fusion (nine genes); vesicle-related (125 genes) coded proteins are enhanced by the Human Protein Atlas. Because some genes have more than one function, the final selection is 260 non-repetitive genes. The detailed gene list is in Table 1. majority of the upregulated OCRGs was disease-specific; second, ADs shared more upregulated OCRGs than other diseases; and third, the ratios of upregulated OCRGs vs. downregulated OCRGs were 1:2.8 in AIs, 1:1 in MDs, 1:1.2 in ADs, and 1:3.8 in OFs, suggesting that AIs and OFs had downregulated OCRGs much more than those of upregulated in comparison with those of others. We then used a Venn diagram to analyze the overlapping OCRGs and their classifications among AIs, MDs, ADs, and OFs ( Figure 2E) and listed the exclusively expressed OCRGs upregulated and downregulated in these four types of diseases in Supplementary Tables 4A,B. The results showed that a total of 24 upregulated OCRGs were shared by two or three different diseases. AIs and MDs, and AIs and ADs shared three and one OCRGs, respectively. MDs and ADs, and MDs and OFs shared five and three OCRGs, respectively. ADs and OFs shared six OCRGs. AIs, MDs, and ADs shared three OCRGs. AIs, MDs, and OFs shared one OCRG. MDs, ADs, and OFs shared one OCRG. There were 12, 17, 43, and  We then hypothesized that every major disease group modulates differentially 16 OCRG groups. We used the donut chart analysis. As shown in Figure 3, These results have demonstrated that first, vesicle, MT fission, and mitophagy were three top groups of organelle crosstalk regulators upregulated in all four major diseases. Since these three groups of OCRGs are only upregulated in AIs, sepsis, and trauma, we also classify those three groups including vesicle, MT fission, and mitophagy as the cell crisis-handling OCRGs, at least in the partial functions of the three groups, which were well-correlated with a previous report that mitophagy regulator PINK1 is an MT quality control gate keeper (80); second, ER crosstalk regulators were only upregulated in MD and AD groups but not in AIs and OFs; third, a few groups of OCRGs were upregulated in AIs (three groups) and OFs (seven groups), but the other two disease groups had more groups of OCRGs upregulated (MDs had 12 groups and ADs had 14 groups). Therefore, similar to the cell crisis-handling OCRGs that we defined, we also classify vesicle, MT fission, mitophagy, sarcoplasmic reticulum-MT, MT fusion, autophagosome-lysosome fusion, and autophagosome/endosome-lysosome fusion as the cellular failure-handling OCRGs, at least in the partial functions of seven groups; fourth, MT fusion regulators and sarcoplasmic reticulum-MT regulators were upregulated in MDs, ADs, and OFs; and fifth, AIs, MDs, ADs, and OFs downregulated 15, 9, 14, and 15 OCRG groups, respectively, suggesting that AIs and OFs upregulate less OCRG groups but downregulate more OCRG groups than MDs and ADs. To determine the functions of upregulated OCRGs, we performed MPAs. As shown in Figures 4A-D, AIs upregulated the top pathways including vacuole organization, lysosomal transport, neutrophil degranulation, regulation of endocytosis, positive regulation of peptidase activity, protein transfer within lipid bilayer, MT fission, vesicle organization, response to acid chemical, lysosomal organization, and receptor-mediated endocytosis. MDs upregulated the top pathways including MT organization, organelle fusion, macroautophagy, vesicle organization, response to anesthesia, myeloid leukocyte activation, protein localization, positive regulation of transmembrane transport, and endosomal transport. ADs upregulated the top pathways including MT fission, protein localization, membrane fusion, organelle fusion, neurodegeneration with brain iron accumulation (NBIA) subtype pathway, insertion of tail-anchored proteins, calcium ion transmembrane transport, vesicle fusion, Fragile X syndrome, MT localization, response to inorganic substance, regulation of NIK/NF-kB signaling, bile acid metabolic process, cholesterol metabolism, lung fibrosis, and protein targeting. OFs upregulated the top pathways including macroautophagy, organelle fusion, autophagosome maturation, cytosolic calcium ion transport, negative regulation of neuron apoptotic process, antigen processing and presentation, and negative regulation of cellular component organization. In Figures 5A-D  localization, response to light stimulus, response to cadmium ion, positive regulation of blood circulation, regulation of peptide hormone secretion, L1CAM interactions, and cellular response to unfolded protein. ADs downregulated the top pathways including mitochondrion organization, autophagy, organelle fusion, MT membrane organization, endocytosis, positive regulation of apoptotic process, establishment of protein localization to organelle, negative regulation of MT fission, vesicle organization, and lysosomal transport. OFs downregulated the top pathways including MT fission, vesicle organization, protein localization, organelle fusion, Golgi vesicle transport, regulation of vesicle-mediated transport, MT fusion, negative regulation of mitochondrion organization, lysosomal transport, ROS metabolic process, endocytosis, and response to hyperoxia. A Venn diagram was used to analyze the overlapping pathways of upregulated and downregulated OCRGs among these four major types of diseases. As shown in Figure 4E, for upregulated OCRGs, vesicle organization was shared by AIs and MDs; MT fission was shared by AIs and ADs; macroautophagy was shared by MDs and OFs; organelle fusion was shared by MDs, ADs, and OFs. Figure 4F lists the exclusively enriched upregulated pathways in these four diseases. In Figure 5E, for downregulated OCRGs, MT fragmentation involved in the  apoptotic process and mitochondrion organization was shared by AIs and ADs; autophagy signaling was shared by AIs, MDs, and ADs; MT fusion was shared by AIs and OFs; response to nutrient levels was shared by AIs, ADs, and OFs; regulated exocytosis, lysosomal transport, vesicle organization, and organelle fusion were shared by ADs and OFs; response to light stimulus and Golgi vesicle transport were shared by MDs and OFs; protein localization and MT fission were shared by AIs, MDs, and OFs. Figure 5F lists the exclusively enriched downregulated pathways in these four diseases. These results have demonstrated that (1) the majority of signal pathways for upregulated OCRGs are the major disease group-specific; (2) upregulated pathway organelle fusion is shared by three disease groups such as MDs, ADs, and OFs; (3) upregulated MT fission is shared by AIs and ADs; (4) upregulated vesicle organization is shared by AIs and MDs; (5) upregulated protein localization is shared by MDs and ADs; and (6) more downregulated pathways are shared than upregulated pathways among diseases.

Decreased Autophagosome-Lysosome Fusion Is Required for Viral Replications, Which Classify This Decreased Group as the Viral Replication-Suppressed Organelle Crosstalk Regulators
It has been reported that using single organelle multispectral flow cytometry identified altered energy metabolism, changes in MT size, and MT membrane potential in viral infected cells    Table 5A) and were from 12 functional groups except MT fusion, MT biogenesis, autophagosomelysosome fusion, and endosome-Golgi complex (GC) groups; 143 OCRGs were downregulated and were from all the 16 functional groups (Figures 6A,C). The significant pathways for upregulated OCRGs included protein localization, mitochondrion organization, membrane fusion, organelle fusion, regulation of calcium ion transmembrane transporter activity, regulation of viral process, endomembrane system organization, metabolism of steroids, regulation of organelle assembly, and leukocyte chemotaxis. The top 10 pathways for downregulated OCRGs included mitochondrion organization, autophagy, MT fusion, MT transport, negative regulation of mitochondrion organization, lysosomal transport, organelle localization, endosomal transport, endocytosis, and protein localization (Supplementary Figures 3A,B).
Since MERS-CoV infection in human microvascular ECs induced significant modulation of OCRGs, we further used a Venn diagram and MPA to examine MERS-CoV modulation of OCRGs. As shown in Figure 6B, MERS-CoV infection resulted in upregulation of 62 OCRGs and downregulation of 65 OCRGs. The majority of upregulated OCRGs in 12, 24, 36, and 48 h post infections were shared in at least two time points; four OCRGs were shared in all four time points such as HSPD1, MX1, STX1A, and GTPBP2. Seven downregulated OCRGs such as OPTN, BNIP3L, VAMP8, VPS41, AASS, EPS15, and PDCD6IP were shared in all four time points. Besides the overlapped three genes, the upregulated 59 OCRGs were from 15 functional groups, except autophagosome-lysosome fusion; and the downregulated 62 OCRGs were from 11 functional groups, except ER-PM junctions, sarcoplasmic reticulum-MT, MT biogenesis, ER-GC interaction, and endosome-GC groups ( Figure 6C). As shown in Supplementary Table 5B, downregulation of five including VAMP8, VPS41, ATG14, STX17, and RILP out of nine regulators were in autophagosome-endosome/lysosome fusion; and downregulation of one out of four regulators, TIRAP, was in the autophagosome-lysosome fusion group. The top 10 pathways for upregulated OCRGs included mitochondrion organization, synaptic vesicle budding from presynaptic endocytic zone membrane, regulation of mitochondrion organization, autophagy, protein localization, response to unfolded protein, cargo recognition for clathrin-mediated endocytosis, divalent metal ion transport, MT DNA metabolic process, and tissue remodeling. The top 10 pathways for downregulated OCRGs included macroautophagy, organelle fusion, autophagosome maturation, protein localization, vacuolar transport, regulation of MT fission, membrane trafficking, autophagosome membrane docking, endocytosis, and MT transport. The Venn diagram indicated that MT transport, endocytosis, regulated exocytosis, and autophagosome maturation pathways were commonly downregulated in influenza virus-and MERS infectious clone (icMERS)-inoculated cells (Supplementary Figures 3C,D).

Taken together, our results have demonstrated that (1) virus infection in ECs and lung epithelial cells significantly modulate
OCRGs in all the functional groups; (2) decreased one group autophagosome-lysosome fusion and four signaling pathways including MT transport, endocytosis, regulated exocytosis, and autophagosome maturation are the significant organelle crosstalk features of viral infections. The significant modulation of OCRGs by MERS-CoV in human microvascular ECs may be the underlying mechanism for much higher (41-50%) acute kidney injuries caused by MERS-CoV than that of SARS-CoV (6.7%) and COVID-19 (3%) (85). These results suggest that increased organelle crosstalk in all 15 functional groups (except autophagosome-lysosome fusion) but decreased lysosome degradation are required for viral replication; and significant modulation of organelle crosstalk in human microvascular ECs in coronavirus family infection represented by MERS-CoV may be the important underlying mechanism for COVID-19 (caused by SARS-CoV 2)-induced cardiovascular complications (86,87).

Organelle Crosstalk Regulators Upregulated by Pro-atherogenic Damage-Associated Molecular Patterns in Endothelial Cells Are Classified Endothelial Cell-Activation/Inflammation-Promoting Organelle Crosstalk Regulator Groups
Our previous reports showed that sterile inflammatory stimuli can cause intracellular organelle stress that occurs not only in cancer cells but also in vascular ECs (37). We reported that lysolipids are capable of transdifferentiating human aortic ECs (HAECs) into innate immune cells, including induction of potent DAMP receptors, such as CD36 molecule (14). CD36 pathways are activated by several distinct ligands, which converged on these pathways and results in inflammatory responses and endothelial dysfunction. CD36 pathway may be an underlying cause of CVDs and cerebrovascular diseases (88). Oxidized lipids upregulated by CD36 can modulate endothelial properties and may contribute to atherogenesis (89). However, how DAMP receptor signaling modulates expression of organelle crosstalking in ECs remains poorly understood. We examined the expression changes of OCRGs in ECs under stimulations of various pathogen-associated molecular patterns (PAMPs)/DAMPs (90)(91)(92). As shown in  (95). However, another report showed that reduction of NOTCH1 expression in HAECs by siRNA, in the absence of stimulations with inflammatory lipids or cytokines, increased inflammatory molecules and binding of monocytes (96). In the datasets of this paper, we found that inhibition of NOTCH1 expression with siRNA in HAECs upregulated three OCRGs and downregulated six OCRGs. In addition, interferon-α (IFNα), IFNβ and IFNγ treatment of HUVECs led to upregulation of 7, 11, and 6 OCRGs, respectively, but no downregulation of OCRGs. Of note, oscillatory shear vs. laminar shear (fibrosa), oscillatory shear vs. laminar shear (ventricularis) (97), and MAECs from atherogenic apolipoprotein E (ApoE)deficient mice vs. MAECs from wild-type control mice had no modulation of OCRG expressions potentially due to a longterm chronic adaptation process in response to shear stress or hyperlipidemia. Pro-atherogenic DAMP stimuli oxidized lowdensity lipoprotein (oxLDL) (98) and proinflammatory oxidized 1-palmitoyl-2-arachidonoyl-sn-glycerol-3-phosphatidylcholine (oxPAPC) stimulation of MAECs presumably via transient receptor potential ankyrin 1 (TRPA1) (99) upregulated three, zero, and seven OCRGs and downregulated five, six, and seven OCRGs ( Table 4). Figures 7A,B (Supplementary Table 6 (Figure 7C). The downregulated top 5 pathways included MT fission, autophagy, synthesis of bile acids and bile salts, endocytosis, and RAB geranylgeranylation ( Figure 7D). By comparison, 20 OCRGs were upregulated and were classified into five groups (Supplementary Figures 5A,B); the top pathways involved in upregulating OCRGs in LPS-stimulated ECs included MT fission, endosomal transport, receptor internalization, cytokine signaling in immune system, and ZNF410 TARGET GENES (Supplementary Figure 5C), latter four top pathways of which were different from those in DAMPstimulated upregulation of OCRGs in ECs. The top pathways involved in downregulating OCRGs in LPS-stimulated ECs included MT fission, regulation of calcium ion transmembrane transporter activity, negative regulation of transferase activity, receptor metabolic process, and establishment of organelle localization, also latter four top pathways of which were different from those in DAMP-stimulated upregulation of OCRGs in ECs (Supplementary Figure 5D). Taken together, our results have demonstrated that (1) acute inflammatory (influenza) virus infection has higher OCRG modulation than in chronic tumorigenic (herpes) virus infection in ECs; (2) EC activation   Recent reports showed that the MT membrane potential and the proliferation inhibition function of CD4 + Foxp3 + Treg from patients with myasthenia gravis are enhanced by autophagy inducing agent rapamycin and suppressed by phosphoinositide 3-kinase (PI3 kinase) and autophagy inhibitor 3-methyladenine (3-MA) (102) and that during autoimmune conditions, Treg function alterations associate with MT oxidative stress, dysfunctional mitophagy, and enhanced DNA damage and cell death (103,104). We hypothesized that the expressions of OCRGs are modulated in CD4 + CD25 high FOXP3 + Treg in comparison with those of CD4 + CD25 − T effector cell controls. As shown in Table 5, Treg from eight different tissues including lymph nodes (LNs), visceral adipose tissue, brown adipose tissue (cold), brown adipose tissue (warm), spleen from mice with skeletal muscle injury for 4 days, spleen from mice with skeletal muscle injury for 14 days, and spleen from male and female mice had no downregulated OCRGs. In addition, Treg from five tissues such as warm spleen, skeletal muscle from mice with skeletal muscle injury for 4 days, skeletal muscle from mice with skeletal muscle injury for 14 days, intestine, and peripheral blood had one, four, two, one, and one downregulated OCRGs, respectively. Moreover, Treg in spleen from female mice had no upregulated OCRGs; and Treg from the rest of the 12 groups had one to 12 upregulated OCRGs (Supplementary Table 7 listed, in detail, the significant expressed OCRGs in Treg compared with conventional T cells). To examine a hypothesis that the expressions of OCRGs are required for the suppressive functions of Treg, we determined this hypothesis with Treg signature gene deficient microarray datasets. The 15 microarrays of Treg regulator deficiency datasets were collected to analyze the expression changes of OCRGs ( Table 6). In the deficiency datasets of Treg signature genes GATA binding protein 3 (Gata3), histone deacetylase 9 (Hdac9), and peroxisome proliferator activated receptor gamma (Pparg) in LNs, there were no significant expression changes of OCRGs. There were seven significantly upregulated OCRGs and no downregulated OCRGs in Treg signature transcription factor B-cell lymphoma 6 (Bcl6) knockout Treg from spleen and LN. There were six significantly upregulated OCRGs and one downregulated OCRG in Foxo1 knockout Treg from the thymus, spleen, and LNs. In Dicer 1 (ribonuclease III, microRNA-maturation enzyme) knockout CD4 + T cells, there were five upregulated OCRGs and one downregulated OCRG. In tripartite motif containing 28 [E3 small ubiquitin-like modifier (SUMO)-protein ligase Trim28] knockout Treg, there were three upregulated OCRGs and five downregulated OCRGs. In B lymphocyte-induced maturation protein 1 (Blimp1) deficiency Treg, there were three upregulated OCRGs and six downregulated OCRGs. As shown in Figure 8A, when combining all the upregulated and downregulated OCRGs in the Treg, besides the overlapping genes, four OCRGs downregulated in Treg included sarcoplasmic reticulum-mitochondria contact regulator OSBP-related protein 8 (Osbpl8) (105), MT fission regulators MX1 and MX2, and one vesicle regulator Hexim1 (Supplementary Table 8). There were no significant pathways of the upregulated OCRGs from MPA. The 19 upregulated OCRGs included one autophagosomelysosome fusion regulator Tirap, one mitophagy regulator Vmp1, one MT fission gene Dcn, one MT translocation Tomm7, Vdac1 with more function (mitophagy, ER-MT contact, sarcoplasmic reticulum-MT), MT fission and fusion, mitophagy regulator Bnip3, and the other 13 vesicle regulators (Supplementary Table 8 and Figure 8B). The top signaling pathways of these upregulated OCRGs from the MPA included positive regulation of macroautophagy, regeneration, regulation of protein stability, positive regulation of apoptotic process, and leukocyte chemotaxis ( Figure 8C). These results have demonstrated for the first time that Treg from various tissues and mice with injured skeletal muscle have upregulation of OCRGs compared with those of CD4 + CD25 − T effector controls; and Treg slightly upregulate a few OCRGs in Treg from visceral adipose tissue, skeletal muscle, and intestine. The results of weakened Treg cells from 11 microarrays (Treg signature gene knockout datasets) showed that the upregulated OCRGs were more than downregulated OCRGs ( Table 6 and Supplementary Table 9 list in detail differentially expressed OCRGs). As shown in Figure 8D, the 17 upregulated OCRGs included one autophagosome-lysosome fusion gene Tirap, one ER-endosome contact gene Npc1, two ER-MT contact genes Bcap31 and Itpr1 (also sarcoplasmic reticulum-MT group), one ER-PM junctions Stx1a, two mitophagy genes Optn and Atg7, two MT fission genes Mtfr2 and Mtfp1, and the other eight vesicle regulators (Nsdhl, Clta, Abcd3, Ctsa, Rab11fip5, Dyrk4, Mbd1, and Tyr). The eight downregulated OCRGs included two MT fission regulators Dcn and Mapt and six vesicle regulators (Ankrd6, Igf2r, Gtpbp2, Dpp7, Gprc5a, and Grn) (Supplementary Table 9 and Figure 8E). There were no significant pathways in the downregulated OCRGs from MPA. The signaling pathways of these upregulated OCRGs included regulation of autophagy, adaptive immune system, Fragile X syndrome, insulin secretion lipid transport, and organic hydroxy compound metabolic process ( Figure 8F). Taken together, our results have demonstrated that (1) the expression of OCRGs are modulated in CD4 + FOXP3 + Treg and Treg cells with signature genes deficiencies; and (2) upregulated OCRGs in Treg are more than downregulated OCRGs. In weakened Treg when Treg signature genes are deficient, upregulated OCRGs are more than downregulated OCRGs; and (3) positive regulation of macroautophagy, regeneration, regulation of protein stability, positive regulation of apoptotic process, and leukocyte chemotaxis signaling are upregulated in Treg; and regulation of autophagy, adaptive immune system, Fragile X syndrome, insulin secretion, lipid transport, and organic hydroxy compound metabolic process are upregulated in weakened Treg.

Regulate the Expressions of Organelle Crosstalk Regulators
In order to determine the mechanisms underlying the expression changes of OCRGs in diseases, virus-infected cells, and proatherogenic DAMP-treated ECs, we examined expressions of OCRGs in nine microarrays including six TLRs (106), one ROS regulator Nrf2 (23), and two caspase-1-deficient microarrays. Caspase-1 is activated in the DAMP/PAMP-sensing protein complexes termed inflammasomes (3,11,16,36,39,90,(106)(107)(108)(109)(110) (Tables 7-9). The results showed that TLR2, TLR4, and TLR3/7/9 deficiencies upregulated 29, seven, and nine OCRGs and downregulated 37, 12, and 12 OCRGs, respectively (Supplementary Figure 6). In addition, ROS negative regulator Nrf2 deficiency upregulated 14 and downregulated seven OCRGs. Moreover, caspase-1 deficiency upregulated seven and downregulated five OCRGs. Then we proposed two models to explore the mechanisms underlying the expression changes of OCRGs regulated by DAMP/PAMP sensing TLRs and caspase-1/inflammasomes (Figures 9A,B). A Venn diagram was used to identify the regulated OCRGs in diseases, virus infections, and cells stimulated by pro-atherogenic DAMPs (Supplementary Figures 7-11). As shown in Figure 9C and Supplementary It has been reported that mitophagy pathways are intricately linked to the metabolic rewiring of cancer cells to support the high bioenergetic demand of the tumors (111); autophagy, acting as a cancer-suppressive function, is inclined to hinder metastasis by selectively downregulating critical transcription factors of the epithelial-mesenchymal transition (EMT) in the early phases (112). The molecular mechanisms underlying fusion, with either lysosomes or plasma membrane, are key determinants to maintain cell homeostasis upon stressing stimuli. The accumulation of undigested substrates leads to cancer and other diseases such as lysosomal storage disorders and agerelated neurodegenerative diseases (113). We hypothesized that carcinogenesis modulates the expressions of OCRGs. To examine this hypothesis, we collected the expression data of 260 OCRGs in 28 cancer datasets in the NIH-NCI TCGA (https://www. cancer.gov/about-nci/organization/ccg/research/structuralgenomics/tcga/using-tcga)/GTEx database (GTEx Portal, https://www.gtexportal.org/home/) from EGPIA2 (http://gepia2. cancer-pku.cn/#index). As shown in Table 10, all the 28 cancers from the gastrointestinal, respiratory, brain, genitourinary, hematopoietic, and digestive systems significantly modulated the expressions of OCRGs. The upregulated OCRGs range from one OCRG in lung adenocarcinoma (LUAD) to 166 OCRGs in thymoma; and downregulated OCRGs range from three in pancreatic adenocarcinoma (PAAD) to 65 in testicular germ cell tumor.
To identify the common features of OCRG modulation in cancers, we calculated the percentage (a/b%) of upregulated OCRGs (a) over total upregulated expressed genes and (b) in the cancer microarrays, and the ratios of downregulated OCRGs over total downregulated genes. We noticed that 16 cancers had upregulated OCRG percentage >1% and 12 cancers had upregulated OCRGs percentages <1%. Cancers were roughly classified into eight systems to explore the expression changes of OCRGs. The numbers of upregulated OCRGs were more than those of downregulated genes in tumors of the immune system, digestive system, and nervous system. The numbers of downregulated OCRGs were more than those of the upregulated OCRGs in tumors of the endocrine system, respiratory system, and circulation system and most tumors of the reproductive system and urinary system. In breast invasive carcinoma (BRCA) and skin cutaneous melanoma (SKCM), the numbers of upregulated OCRGs were more than those of downregulated OCRGs. In head and neck squamous cell carcinoma (HNSC), the numbers of upregulated OCRGs were less than those of downregulated OCRGs (Figures 10A,B). We then examined a hypothesis that upregulations of OCRGs are correlated with increased immune cell infiltration. To examine this hypothesis, GSCA database (http://bioinfo.life. hust.edu.cn/GSCA/#/immune) (76) was used to analyze the correlation of upregulated OCRGs with immune infiltrates. Liver hepatocellular carcinoma (LIHC) and lung squamous cell carcinoma (LUSC) were studied for the details as an example.
The result in Figure 10C shows that almost 19 upregulated OCRGs in LIHC were positively correlated with B cells, natural killer (NK) cells, effector-memory T cells, naturally occurring Treg (nTreg), CD8 T cells, dendritic cells (DCs), type 1 Treg (Tr1), and type 1 T helper cells (Th1) infiltration but negatively correlated with macrophages, neutrophils, CD4 T cells, inducible Treg (iTreg), central memory T cells, monocytes, Th17, and   Figure 10D). Therefore, our findings have demonstrated that the expression modulations of OCRGs can predict the degrees of tumor immune infiltrations and serve as potential therapeutic targets. The GO (Gene Ontology) chord analysis showed that more upregulated OCRGs in LIHC and LUSC were enriched in mitochondrion organization pathway than other pathways (Figures 10E,F). In fact, the upregulated OCRGs in most tumors can be enriched in mitochondrion organization pathways (Supplementary Figure 12). We further examined five digestive cancers such as PAAD, stomach adenocarcinoma (STAD), rectal adenocarcinoma (READ), LIHC, and colon adenocarcinoma (COAD) among the cancer groups with >1% OCRGs and performed the Venn diagram analysis on upregulated OCRGs of these five digestive cancers. As shown in Supplementary Figure 13A, the results showed that PAAD had 80 specific OCRGs (54.8%) out of 146 upregulated OCRGs. In contrast, the other cancers had much lower specific OCRGs. For example, STAD, READ, LIHC, and COAD had three (5.6%), one (2.8%), two (11.1%), and zero (0%) specific OCRGs, respectively. Of note, one OCRG shared by all five cancer groups was translocase of outer MT membrane 40 (TOMM40). We also found that TOMM40 was upregulated in 14 out of 33 types of cancers (42.4%) (Supplementary Figure 13B). Our results are well-correlated with previous reports that TOMM40 (TOM40) and significant numbers of MT protein import machineries overexpressed in cancers such as the TOM complex (TOM20, TOM40, TOM7, and TOM70), TIM23 complex, TIM22 complex, small Tim chaperons and Mia40, and Tim 44 (111,114). To elucidate the functional aspects of TOMM40, we searched the PPI network database in the STRING database (https:// string-db.org/). As shown in Supplementary Figure 13C, the top 10 proteins functionally interacted with TOMM40 including translocase of outer MT membrane (TOM) complex members TOMM7, TOMM20, TOMM70A, and TOMM22; translocase of inner MT membrane (TIM) complex members TIMM50, TIMM44, TIMM13, and TIMM10; sorting and assembly machinery complex (SAM) member SAMM50; and CYC1 (cytochrome C1, complex III subunit 4). As shown in Supplementary Figures 13D,E, the most relative top 10 genes to TOMM40 were localized in two types of protein complexes, the translocase of outer MT membrane complexes (TOMs) and translocase of inner MT membrane complexes (TIMs), and were mainly enriched in protein targeting to mitochondria, protein transporter activity and MT protein complex in biology process, molecular function and cell component (115,116). The enriched pathways of these 11 genes were MT protein import, Pink/Parkin-mediated mitophagy, and Ub-specific processing proteases (117). We further determined whether increased expressions of TOMM40 and 10 interaction proteins in cancers lead to better prognosis by analyzing the overall survival map of hazard ratio (HR) and disease-free survival map [relapse-free survival (RFS)] of TOMM40 and 10 interaction proteins. The result showed that overall survival of patients in most cancers were positively related to these 11 genes (red box in Supplementary Figure 13F); and RFS of patients in most cancers was positively related to upregulation of these 11 genes (red box in Supplementary Figure 13G; the blue box was the negative correlation between the expression of genes and RFS). It has been reported that MT protein transport system is modulated in cancers (118). A previous report showed that TOMM70 acts as receptor of the MT antiviral-signaling protein (MAVS) and thereby participates in the corresponding system of innate immunity against viral infections (119). It remains unknown whether this innate immune function of TOMM70 is correlated with the better prognosis of cancers upregulating TOMM40 complexes. Relations between abundance of tumor-infiltrating lymphocytes, immunoinhibitors, immuno-stimulators, MHCs, and expression of TOMM40 were explored by using TISIDB database (http:// cis.hku.hk/TISIDB/index.php) (75). The results indicated that the expressions of TOMM40 were positively correlated with abundance of act CD8, act CD4, CD56, and monocyte cells in most of the cancers and that immuno-inhibitor PVRL2; immuno-stimulators CD276, PVR, TNFRSF18, TNFRSF25, and TNFRSF4; and HLA-A, HLA-B, HLA-C, HLA-F, TAP1, TAP2, and TAPBP molecules were positively correlated with expression of TOMM40 in most of cancers (Supplementary Figure 14). We speculate that upregulation of  The results show that in pancreatic adenocarcinoma (PAAD), brain lower-grade glioma (LCC), and esophageal carcinoma (ESCA), these 15 cancers [from PAAD to uterine corpus endometrial carcinoma (UCEC)] upregulated OCRGs more than the downregulated OCRGs; in lung adenocarcinoma (LUAD), adrenocortical carcinoma (ACC), and acute myeloid leukemia (LAML), these 13 cancers (from HNSC to LUAD) downregulated OCRGs more than the upregulated genes. In order to rule out the influence of the overall expression profile on our interest OCRGs, we take the ratio of number of OCRGs and number of total differently expressed genes as the comparison criteria for the number of upregulated and downregulated genes. Result show that 16 cancers have upregulated OCRG percentage >1% and that 12 cancers have upregulated OCRGs percentages <1%. (B) Expression of OCRGs in tumors was roughly classified according to the system. The numbers of upregulated OCRGs are more than downregulated genes in tumors of immune system, digestive system, and nervous system. The numbers of downregulated OCRGs are more than upregulated OCRGs in tumors of the endocrine system, respiratory system, and circulation system and most tumors of the reproductive system and urinary system. In breast invasive carcinoma (BRCA) and skin cutaneous melanoma (SKCM), the numbers of upregulated OCRGs are more than those of downregulated OCRGs. In head and neck squamous cell carcinoma (HNSC), the numbers of upregulated OCRGs are less than those of downregulated OCRGs.   (123); and a limited role for Tp53 is found in modulating early tumor progression induced by APC loss in mouse intestine (124). APC KO led to six OCRG upregulation and three OCRG downregulation compared with that of wild-type controls, respectively. Furthermore, phosphatidylinositol 3-kinase (PI3-kinase) and phosphatase and tensin homolog deleted on chromosome 10 (PTEN) are major positive and negative regulators of PI3 kinase pathway in regulating cell growth, survival, and proliferation and are two of the most frequently mutated proteins in human cancers (125). PTEN is a tumor suppressor (126) Figure 15C). FIGURE 11 | A novel working model shows the function, classification, and regulated mechanisms of OCRGs in diseases, and DAMP-and virus-treated cells. (A) The membrane contact sites between two organelles, at least between ER and mitochondria (Mito, MT), have been found to play several significant functions from previous (Continued) FIGURE  Our data in Table 11 show that IKK2 depletion upregulated five OCRGs in lung tumor cells, which were well-correlated with the finding that IKK2 depletion attenuated tumor proliferation and prolonged mouse survival. We then tested a hypothesis that IKK2 depletion upregulated OCRGs may partially overlap with LUAD-downregulated OCRGs. As shown in Supplementary Figure 16A, the Venn diagram indicated that vesicle regulator perilipin 4 (PLIN4) was overlapped between the LUAD-downregulated OCRGs and the IKK2 KOupregulated OCRGs. As shown in Supplementary Figure 16B, the expression profile analysis using cancer and normal gene expression database GEPIA (http://gepia.cancer-pku.cn/index. html) (127) showed that the expression of PLIN4 was decreased in 23 out of 33 tumor types compared with controls. Our data in Table 8 show that tumor suppressor Tp53 KO in liver tumors upregulated 23 OCRGs and downregulated 48 OCRGs, which were associated with induction of carcinomas in Tp53 KO mice (122,126). Similarly, we then tested a hypothesis that Tp53 KO upregulated OCRGs may partially overlap with that liver tumor (LIHC)-upregulated OCRGs; and Tp53 KO downregulated OCRGs may partially overlap with liver tumor (LIHC)-downregulated OCRGs. As shown in Supplementary Figure 16C, the Venn diagram indicated that prolyl 4-hydroxylase subunit alpha 2 (P4HA2) was shared between the Tp53 KO upregulated OCRGs and the liver tumor (LIHC)-upregulated OCRGs; and alpha-aminoadipic semialdehyde synthase (AASS) was shared between the Tp53 KO downregulated OCRGs and the liver tumor (LIHC)downregulated OCRGs. The cancer gene expression database analysis showed that the expressions of vesicle regulator P4HA2 were increased in seven out of 33 tumor types compared with controls (Supplementary Figure 16D); and the expression of vesicle regulator AASS in seven out of 33 tumor types was decreased compared with that of controls (Supplementary Figure 16E). Taken together, our results have demonstrated that first, tumor promoter IKK2 and tumor suppressor Tp53 significantly modulate the expressions of OCRGs; second, lung tumor LUAD-downregulated vesicle regulator PLIN4 may contribute to IKK2 KO-promoted tumor formation; third, liver tumor (LIHC)-upregulated vesicle regulator P4HA2 may increase Tp53 KO-promoted liver tumorigenesis; and fourth, LIHC-downregulated vesicle regulator AASS may contribute to Tp53 suppression of liver tumorigenesis.

DISCUSSION
Although alterations to these networks, such as impaired ER-mitochondria MCSs, have been linked to several diseases such as neurodegeneration (59,60), CVD (61), diabetes (62), kidney diseases (63,64), and cancers (65,66), an important question remains poorly characterized how the expressions of organelle crosstalk regulator genes are modulated in various diseases. To examine whether the expressions of 260 OCRGs in 16 functional groups are modulated in 23 diseases and 28 tumors, we performed extensive -omics data mining analyses in a panoramic manner with the method that we pioneered in 2004 (23,26,29,91,107,109,128) and made a set of significant findings: (1) the ratios of upregulated vs. downregulated OCRGs are 1:2.8 in AIs, 1:1 in MDs, 1:1.1 in ADs, and 1:3.8 in OFs; and AIs and OFs upregulate less OCRG groups (three to seven out of 16) than metabolic and ADs (11 to 13 out of 16); (2) sepsis and trauma-upregulated OCRG groups including vesicle, MT fission, and mitophagy but not other groups of OCRGs; thus, the three groups of OCRGs are classified as the acute crisis-handling OCRGs; and similarly, sepsis and trauma plus OFs-upregulated seven OCRG groups including vesicle, MT fission, mitophagy, sarcoplasmic reticulum-MT, MT fusion, autophagosome-lysosome fusion, and autophagosome/endosome-lysosome fusion are classified as the cell failure-handling OCRGs; (3) the majority of upregulated pathways are disease group-specific; upregulated organelle fusion and macroautophagy are shared by MDs, ADs, and OFs; upregulated MT fission is shared by AIs, MDs, and ADs; upregulated vesicle organization is shared by AI and MDs; and upregulated protein localization is shared by MDs and ADs; (4) increased OCRG expressions in all the 15 functional groups except autophagosome-lysosome fusion but decreased autophagosome-lysosome fusion are required for viral replications, which classify this decreased group as the viral replication-suppressed OCRGs. (5) PAMPs from influenza virus and Kaposi sarcoma-associated herpes virus infections and proatherogenic DAMPs such as oxLDL, LPS, oxPAPC, and IFNs totally upregulated 33 OCRGs in ECs, which classify vesicle, MT fission, mitophagy, MT fusion, ER-MT contact, ER-PT junction, and autophagosome/endosome-lysosome fusion as the seven EC-activation/inflammation-promoting OCRG groups; (6) the expression of OCRGs is modulated in Treg from the LNs, spleen, peripheral blood, intestine, and brown adipose tissue in comparison with that of CD4 + CD25 − T effector controls; (7) TLR2, TLR4, TLR3/7/9, caspase-1, and ROS regulator Nrf2 can upregulate 46 OCRGs from 14 groups out of all 16 groups (except for MT fission and fusion, and ER-MT contact OCRGs), suggesting that DAMP/PAMP-sensing systems play significant roles in modulating the expressions of OCRGs; (8) OCRG expressions are significantly modulated in all the 28 cancer datasets; upregulated OCRGs in LIHC and LUSC are correlated with immune cell infiltrations, suggesting that upregulation of certain OCRGs may promote immune cell infiltration; MT protein translocase TOMM40 and MT import machine are upregulated in cancers and are positively associated with better prognosis; and TOMM40 is correlated with some immune infiltration signature genes, suggesting that increase of protein transport into mitochondria may facilitate the immune cell infiltration; and (9) tumor promoter factor IKK2 and tumor suppressor Tp53 significantly modulate the expressions of OCRGs; lung tumor-downregulated vesicle regulator PLIN4 may contribute to IKK2 KO-attenuated tumor formation; liver tumor-upregulated vesicle regulator P4HA2 may increase Tp53 deficiency-promoted liver tumorigenesis; and liver tumordownregulated vesicle regulator AASS may contribute to Tp53 suppression of liver tumorigenesis.
The original microarray experiments we analyzed used different cells, which prevented us from comparing the effects of various regulators in regulating the expressions of OCRGs in the same cell types, although our database mining method was not ideal. However, to fill in the important knowledge gaps, our approach was justified. Actually, this approach has been a common practice that we (23) and others (72,129) often use in studying gene expression in non-ideal, heterogeneous PBMC populations in disease conditions vs. healthy conditions, and PBMCs are actually composed of many cell types, such as B cells (∼15%), T cells (∼70%), monocytes (∼5%), and NK cells (∼10%) (130).
To summarize our findings from a panoramic analysis on the expression changes of 260 OCRGs in 51 diseases and cancers presented here, we propose a novel working model to integrate these results, as follows, in Figure 11A: first, the MCSs between two organelles, at least between ER and mitochondria (Mito, MT), have been found to play several significant functions such as metabolism and Ca 2+ transport as we reported (4); organelle communicating ROS as we recently reported (4,38,(40)(41)(42)131); apoptosis as we have reported (132,133); and autophagy, mitophagy, and DAMP communication as we have reported (37). The metabolism regulatory functions between ER-MT contact sites include gluconeogenesis, glycogen synthesis and breakdown, fat storage, hormone metabolism, drug metabolism, lipid biosynthesis, and homeostasis (134); second, since our study analyzed the 260 OCRGs in 51 major diseases and cancers and many other master regulator deficient transcriptomic data, we have demonstrated for the first time that 16 functional groups of OCRGs are not equally modulated in various diseases and cancers. As shown in Figure 11B, we identified three groups of OCRGs such as vesicle, MT fission, and mitophagy as the cell crisis-handling OCRGs, at least in partial functions of the three groups; seven groups of OCRGs including three cell crisis-handling OCRGs plus sarcoplasmic reticulum-MT, MT fusion, autophagosome-lysosome fusion, and autophagosome/endosome-lysosome fusion as the cell failure-handling OCRGs; and autophagosome-lysosome fusion as virus-suppressed OCRGs. Previous reports showed that growing numbers of viruses are found to weaponize the ubiquitin modification system to suppress anti-viral type I IFN pathways (135). Similarly, we found that virus infections weaponize the suppression of autophagosome-lysosome fusion group potentially for virus replication. Since most viruses use endocytosis to enter the host cell, 11 clinically approved generic drugs are identified as potential candidates for repurposing as blockers of several potential routes for severe acute SARS-CoV-2 endocytosis (136), which needs to be further reconsidered since we found that coronavirus and other virus infections in ECs and epithelial cells suppress endocytosislysosome pathways (Supplementary Figure 4); 10 groups of OCRGs activated by DAMPs in ECs including vesicle (137), MT fission, mitophagy, autophagosome/endosome-lysosome fusion, ER-MT contact, ER-PM junctions, sarcoplasmic reticulum-MT, MT fusion, ER-endosome, and ER-GC interaction. Treg plastic OCRGs, and oncogenes and tumor suppressors promoted vesicle regulators; and third, extracellular PAMPs/DAMPs, cytokines, and viruses act via their receptors including TLRs on the cell membrane and intracellular locations (Nod-like receptors and inflammasomes) (90) to activate OCRGs directly or indirectly by activating intracellular organelle dangers first and then OCRGs. Therefore, similar to our recently proposed new concept that ROS are an integrated system for sensing and alarming organelle metabolic homeostasis and dysfunction (38), here, we propose a new concept that the organelle crosstalk serves as both new DAMPs sensing and communicating network and new cell crisis and cell failure-handling network (37) to fulfill both physiological functions and pathological functions ( Figure 11C).
One limitation of the current study is that due to the low throughput nature of verification techniques in every laboratory including ours, we could not verify every result we identified with the analyses of high-throughput data, which are similar to all the papers with RNA-Seq, single-cell RNA-Seq, and other -omics data. We acknowledge that carefully designed in vitro and in vivo experimental models will be needed in the future to verify regulator gene deficiency-upregulated OCRGs further and the underlying mechanisms we report here. Nevertheless, our findings provide novel insights on the roles of upregulated OCRGs in the pathogenesis of inflammatory diseases and cancers, novel pathways for the future therapeutic interventions for inflammations, sepsis, trauma, OFs, ADs, metabolic CVDs, and cancers.