It is well known that the dysfunction of ABCD1 results in X-linked adrenoleukodystrophy, a severe neurodegenerative disease. Recently, it is reported that ABCD3 and ABCD4 are responsible for hepatosplenomegaly and vitamin B12 deficiency, respectively. In this review, the targeting mechanism and physiological functions of the ABCD transporters are summarized along with the related disease.ATP-binding cassette (ABC) transporters are one of the largest families of membrane-bound proteins and transport a wide variety of substrates across both extra- and intracellular membranes. They play a critical role in maintaining cellular homeostasis. To date, four ABC transporters belonging to subfamily D have been identified. ABCD1–3 and ABCD4 are localized to peroxisomes and lysosomes, respectively. ABCD1 and ABCD2 are involved in the transport of long and very long chain fatty acids (VLCFA) or their CoA-derivatives into peroxisomes with different substrate specificities, while ABCD3 is involved in the transport of branched chain acyl-CoA into peroxisomes. On the other hand, ABCD4 is deduced to take part in the transport of vitamin B There are 48 ATP-binding cassette (ABC) transporters in humans that are classified into seven subfamilies, A to G, based on structural organization and amino acid homology , 2. ABC To date, four ABCD transporters have been identified: adrenoleukodystrophy protein (ALDP/ABCD1), ALDP-related protein (ALDRP/ABCD2), the 70-kDa peroxisomal membrane protein (PMP70/ABCD3), and the PMP70-related protein P70R/ABCD4) [ [4–7]. T ABCD4 cause a newly identified inborn error of vitamin B12  metabolism . Th. Th54]. The type of a given ABCD1 mutation, such as missense, nonsense, frameshift, deletion, or insertion, does not predict the disease phenotype. Different clinical phenotypes have even been reported in monozygotic twins . It has At present, there is no effective treatment for preventing the onset or the progression of the neurological pathogenesis that occurs in X-ALD. Allogeneic hematopoietic stem cell transplantation (HSCT) is the only currently available therapeutic procedure, which halts the progress of cerebral demyelination in patients with early stages of CCALD . The mecβ-oxidation [In addition to HSCT-based therapy, pharmacological therapies are still of importance in order to delay both the onset and progression of the disease. Many candidate compounds have been reported for X-ALD therapy to date. The targets of these compounds can be categorized into 4 groups : pharmacxidation , suppresxidation , and redxidation . However


C. elegans CHE-1, a terminal selector of ASE sensory neuron identity. In undifferentiated cells, ectopic expression of CHE-1 results in activation of ASE neuron type-specific effector genes. Once cells differentiate, their plasticity is restricted and ectopic expression of CHE-1 no longer results in activation of ASE effector genes. In striking contrast, removal of the respective terminal selectors of other sensory, inter-, or motor neuron types now enables ectopically expressed CHE-1 to activate its ASE-specific effector genes, indicating that terminal selectors not only activate effector gene batteries but also control the restriction of cellular plasticity. Terminal selectors mediate this restriction at least partially by organizing chromatin. The chromatin structure of a CHE-1 target locus is less compact in neurons that lack their resident terminal selector and genetic epistasis studies with H3K9 methyltransferases suggest that this chromatin modification acts downstream of a terminal selector to restrict plasticity. Taken together, terminal selectors activate identity-specific genes and make non-identity-defining genes less accessible, thereby serving as a checkpoint to coordinate identity specification with restriction of cellular plasticity.The acquisition of a specific cellular identity is usually paralleled by a restriction of cellular plasticity. Whether and how these two processes are coordinated is poorly understood. Transcription factors called terminal selectors activate identity-specific effector genes during neuronal differentiation to define the structural and functional properties of a neuron. To study restriction of plasticity, we ectopically expressed DOI:http://dx.doi.org/10.7554/eLife.24100.001 The acquisition of differentiated cell identities in a multicellular organism is accompanied by the loss of developmental plasticity. Undifferentiated cells are pluripotent and have the potential to activate diverse categories of genes. As differentiation progresses, cells activate cellular identity-specific genes as well as repress non-identity-specific genes, thereby losing pluripotency and attaining a differentiated state that is restricted. In this work, we aimed to uncover molecules and mechanisms that coordinate identity specification with the restriction of cellular plasticity.The progressive loss of developmental plasticity in differentiating cells was first observed in pioneering somatic nuclear transplant experiments , 1962. WC. elegans, the overexpression of myogenic helix-loop-helix TF hlh-1/MyoD early in embryonic development leads to the activation of muscle genes in all somatic cells  are ectopically expressed in progressively more differentiated cells also demonstrate restriction of plasticity. For instance, in ic cells . Howevernd elt-7 , ectodernd elt-3  and phar3  TF which specifies the identity of cholinergic motor neurons (MNs). We identified an allele of unc-3 in which cholinergic MNs express identity-specific markers and function normally, yet are still plastic. This finding strongly suggests that even in an otherwise appropriately specified neuron, terminal selector function is required to restrict plasticity. Next, using a LacI/LacO spot assay , and a reporter of a CHE-1 target gene, gcy-5, that is normally expressed in ASER , smFISH probes against gcy-5 mRNA, and an allele of gcy-5 in which the endogenous locus is tagged with mNeonGreen using CRISPR/Cas9-mediated genome engineering , prom::gfpgcy-5 is broadly activated in numerous cells  neurons, which are dividing and differentiating at this time. As some VNC neurons are born during embryonic stages, we examined whether VNC cells that activate gcy-5 at L2 are those that are newly born. To this end, we used a pan-neuronal marker, prom::rfprab-3, which is brightly expressed in VNC neurons that were born during embryonic stages, but is dim in cells that are still undergoing differentiation. In these worms, activation of fosmid::gfpgcy-5 after L2 CHE-1hs expression is enriched in lowrab-3 cells , hypodermal (promdpy-7), pan-neuronal (promric-19), and two neuron-type-specific drivers . With the exception of the hypodermal promoter, these promoters all become activated only in post-mitotic cells at the time that cells are initiating expression of various identity-specific genes. CHE-1 driven by all neuronal promoters resulted in broad ectopic expression of prom::gfpgcy-5, fosmid::gfpgcy-5, and fosmid::yfpceh-36  . However, fosmid::gfpgcy-6 and prom::rfpgcy-7 show restricted activation in only 1–2 extra cells  cholinergic MNs are born and found in approximately their wildtype positions in the ventral nerve cord (VNC), retro-vesicular ganglion (RVG), and pre-anal ganglion (PAG) of the worm. They express pan-neuronal identity markers, and form axonal projections. However, these neurons lack expression of all the acetylcholine pathway genes, numerous other terminal identity genes, show defects in synaptogenesis and are non-functional (unc-3(-) neurons retain plasticity, we induced CHE-1hs in wildtype and unc-3 mutant worms at various larval stages and scored the expression of prom::gfpgcy-5 in the RVG, VNC, and PAG. In addition to fifty unc-3 dependent MNs, these ganglia contain 19 GABAergic MNs and 13 other unc-3-independent neurons  than wildtype cells. Additionally, smFISH of these worms showed that expression of endogenous gcy-5 mRNA was also induced in unc-3(-) cells to a similar extent  neurons, which is consistent with the idea that che-1 is not sufficient for the induction of these genes, as discussed earlier (0 neurons induced in >20 worms checked). As the transgenic markers that show increased induction in unc-3(-) neurons are randomly integrated into the different chromosomes of the worm, this phenotype suggests that several regions of the genome remain receptive to CHE-1hs activity in the mutant condition.To assess the breadth of CHE-1rom::rfp . No induunc-3 is required broadly for activation of both generic and sub-type-specific cholinergic MN identity features. The further diversification of cholinergic MNs into sub-types is controlled by the activity of various class-specific repressors, such as paired homeodomain TF unc-4, the nuclear receptor TF unc-55, and the T-box TF mab-9  BAG neurons express fosmid::gfpgcy-5 in response to adult CHE-1hs as opposed to 4% of wildtype BAG neurons  AFD neurons express fosmid::gfpgcy-5 after adult CHE-1hs whereas 2% of wildtype AFD neurons do  ASG neurons express fosmid::gfpgcy-5 as opposed to 2% of wildtype ASG neurons . In the case of unc-42 mutants, neither fosmid::rfpgcy-5, nor fosmid::yfpceh-36 was detected in the ASH neurons after CHE-1 misexpression (fosmid::rfpgcy-5). Expression of che-1 early in the development of GABAergic MNs and ASH neurons does lead to activation of target genes, based on tissue-specific promoter driven expression of che-1  mutants. mes-2 is the enzyme responsible for the histone methyl transferase activity of PRC2 and is known to be required for H3K27me3 in the C. elegans germline at all stages, and in somatic cells during embryonic and early larval stages, but not in the adult . MET-2 and HPL-1/2 localization could not be quantified because of low expression levels in neurons. Therefore, it remains to be seen if terminal selectors like unc-3 regulate the correct deposition of H3K9me or if they regulate other functions mediated by met-2 and HP1 to make non-identity defining genes less accessible.Further attempts to understand how  mutants . Second,staining . A thirdC. elegans neurons, identity-defining terminal selectors not only initiate and maintain the expression of effector genes that define a cellular phenotype but they also trigger the restriction of cellular plasticity. We propose that the coordination of identity specification and restriction of plasticity ensures the robustness of the differentiated state, protecting cells from accidental transcription of unwanted genes in response to fluctuations in the environment  at genes that it transcriptionally activates, since we find that the loss of enzymes that generate these marks does not promote cellular plasticity.How terminal selectors might modulate chromatin compaction remains unresolved. In cholinergic MNs there is no obvious difference in the gross, overall levels of H3K9me3 between wildtype and met-2 and hpl-1/2 and (b) carried out by the correct deposition of H3K9me on genes that are not activated in a given neuron type. This hypothesis can be tested in the future by performing cell-type-specific ChIP-seq experiments to determine the distribution of H3K9me3 in wild-type and terminal selector mutant neurons. How terminal selectors may modulate the deposition of chromatin marks remains to be discovered. One possibility is that terminal selectors directly activate target genes that define a specific neuronal identity while also directly silencing genes that are normally not expressed in the respective neuron type. Although some TFs can act as both activator and repressor depending upon the presence of other co-factors (cis-regulatory elements. We rather favor at this point a model in which (a) heterochromatin forms, perhaps by default mechanisms, on loci that are not activated during cellular differentiation and (b) unc-3 regulates the expression or function of some of the proteins that organize the heterochromatic state  likely to be mediated by -factors , we disfic state . These oAll strains were maintained using standard protocols. For heatshock experiments, worms were grown at 15°C, heatshocked at 32°C for 30 min, left at 20°C overnight and scored about 24 hr later.prom::che-1::: :3XHA::BLRP; rol-6(su1006)]; ntIs1 otIs305 otIs587 otIs586 ; ntIs1[gcy-5prom::GFP]otIs629 otIs583 : otEx6597 otEx6598 otEx5430 [ift-20OH11979: fosmid::yfp]otEx3909 [ceh-36OH8882: prom::nlstagrfp]otis355 otis348 [unc-47OH10598: fosmid::yfp::h2b]otis388  II; ot841 (hpl-1::mKate2) protein tag CRISPR engineered into the genomeOH14021: ot860 (hpl-2:: mKate2) protein tag CRISPR engineered into the genomeOH14220: ot861 (met-2:: mKate2) protein tag CRISPR engineered into the genomeOH14221: prom::rfp; LacO repeats]; otIs593 otIs545  gwIs39 otis445 [ace-2OH11744: unc-3(e151), ceh-14(ch3), lin-11(n389), unc-30(e191), unc-42(e419), ets-5(tm1734), ttx-1(p797), met-2(ok2307), set-25(n5021), hpl-1(tm1489), hpl-2(n4317), unc-55(e402), unc-4(e120), mab-9(gk396730), SS186: (mes-2(bn11) unc-4(e120)/mnC1 dpy-10(e128) unc-52(e444)II)prom::che-1::2Xflaghsp16.41 was cloned into the miniMOS vector pCFJ910 and integrated into the genome. Three independent insertions were obtained of which OTti6 was used for all experiments.MiniMos was performed exactly as presented in gcy-5, SL2::1XNLS::mNeonGreen was inserted after the stop codon of gcy-5. For unc-3, mNeonGreen::AID tag was inserted into the C-terminus of the protein just before the stop codon. For hpl-1, mKate2 was inserted into the protein after the 12th amino acid. This tag was based on a published hpl-1 protein fusion . A worm pellet of 20–50 μL was then shaken in 1 mg/mL of collagenase type IV /1 mM CaCl2/1% Triton X-100/0.1 M Tris-HCl(pH7.5) at 37°C for 30 min. The worms were then washed three times in PBS/0.5% Triton X-100, blocked, and stained. Blocking was done in PBS/0.2% gelatin/0.25% Triton for 30 min at room temperature. Antibodies were diluted in PBS/0.1% gelatin/0.25% Triton. Primary antibody was left on overnight at 4°C or 1 hr at room temperature and secondary antibody was applied for 3 hr at room temperature. After washing off the secondary antibody, worms were incubated with DAPI for 15 min, washed again and mounted on glass slides. Primary antibodies used were: H3K27me3  and GFP . All secondary antibodies were Alexa Flour dyes used at 1:1000 dilution.A modified version of the protocol published in met-2; set-25 embryos and L1s, which have been shown by Mass Spectroscopy to not have any H3K9me3  showed non-specific staining as observed by the presence of staining in  H3K9me3 . We foun H3K9me3 . Worms wµManager and Zen were used for image acquisition and processing .smFISH was performed using Custom Stellaris FISH probes, purchased from Biosearch Technologies. Staining was performed according to the manufacturer's protocol. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been favorably evaluated by K VijayRaghavan (Senior Editor) and three reviewers, one of whom, Kang Shen (Reviewer #1), is a member of our Board of Reviewing Editors.Thank you for submitting your article "Coordinated control of terminal differentiation and restriction of cellular plasticity" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:C. elegans TF che-1. They found that expression of che-1 induces ectopic expression of neuronal specific genes, but only in young animals. This restriction is lost in multiple but not all selector mutants. They further showed that chromatin compaction is affected in the selector mutants. While the direct link between the selector genes and chromatin state is not clear, this exciting manuscript produced important insights into the mechanistic link between differentiation and restriction of plasticity.Patel and Hobert tested the relationship between cellular differentiation and cellular plasticity. They performed thorough and elegant experiments using the Essential revisions:che-1 is still able to produce transcriptionally active CHE-1. However, this assay uses an overexpressed, 4X transgene. Why not just tag the hs-che-1 with mcherry? That should provide a direct measure of the level of expression achieved by heatshocking at different stages. Since this is a very important manipulation for the paper, I suggest that the authors do this experiment.1) In 2) What could the difference between the five terminal selectors that are required for restricting plasticity and the two that are not? Is it because there's a fate transformation in the latter group, so that another terminal selector is expressed? Or perhaps the degree of lineage separation from ASE?gcy-5 expression. These tissues are separated from neuronal fate very early in embryogenesis. Supposedly, layers of fate restriction would have piled on by the time of terminal differentiation . Would this imply that terminal differentiation triggers a different kind and qualitatively stronger restriction? If so, it would enhance the interpretation of the main results: the requirement of the examined terminal selectors is not simply a result of neuronal subtypes being specified late from a generic neuronal fate. If the authors so wish, it would be interesting to see if non-neuronal genes  can be expressed easier in unc-3 mutants than in the WT.3) I find the result intriguing where ectopic expression of CHE-1 in hypoderm and muscle in the embryo could induce 4) The last paragraph of the Discussion considers possible mechanisms to explain this conundrum but the suggested alternatives seem baroque and difficult to follow. Perhaps this section can be clarified by careful editing.unc-3 pathway to restrict "cellular plasticity," this experiment does not rule out the possibility that the met-2 gene product could also affect gene expression by other means. Moreover, immunostaining did not detect a quantitative difference in H3K9me levels in wildtype vs. unc-3 mutant neurons. The authors suggest that unc-3 may affect the distribution of H3K9me marks but not the overall level. This explanation seems plausible but is not directly tested. What is needed here is an experiment to ask if H3K9me marks are specifically applied to off target genes  in neurons that express UNC-3. A ChIP-seq experiment that specifically interrogates genes in the UNC-3-expressing neurons could resolve this question but this set up may not be technically feasible. Have the authors considered other alternative strategies for tackling this question? At the very least, this technical caveat should be directly addressed in the text.5) Of greater concern is the absence of direct evidence that a "terminal selector" transcription factor (UNC-3 in this case) prevents ectopic gene induction by triggering the local application of H3K9 methylation marks to silence transcription. Although the authors perform a convincing genetic epistasis experiment to confirm that the H3K9 modifying enzyme met-2 functions in the  Essential revisions:1) In che-1 construct used in this assay is HA-tagged, and therefore can be detected by staining. We have confirmed the presence of the heatshock induced CHE-1 by both staining for HA and by performing smFISH of che-1mRNA. These figures have now been added in The heatshock 2) What could the difference between the five terminal selectors that are required for restricting plasticity and the two that are not? Is it because there's a fate transformation in the latter group, so that another terminal selector is expressed? Or perhaps the degree of lineage separation from ASE?unc-30 and unc-42 mutants respectively (in which che-1 is not able to reprogram identity). Additionally, lineage separation also does not explain the discrepancy as unc-3 dependent cholinergic motor neurons are lineally very closely related to the GABA-ergic motor neurons and equally distant from che-1 dependent ASE neurons. Another explanation for the difference could reside in the properties of the transcription factors themselves – however, we did not find any differences in the protein domains in the transcription factors that do and do not regulate plasticity. A broader understanding of the functions of these transcription factors, such an assessment of gene expression in wt vs. mutant neurons, might be required to answer this question. There is evidence that both unc-42 and unc-30 work with co-factors to specify their respective neuronal fates. It is also possible that these co-factor transcription factors control cellular plasticity in these cells. These points are now briefly raised in the Discussion.This is indeed interesting to consider – there is no evidence, as far as we know, that the GABA-ergic neurons and the ASH differentiate into another cell fate in 3) I find the result intriguing where ectopic expression of CHE-1 in hypoderm and muscle in the embryo could induce gcy-5 expression. These tissues are separated from neuronal fate very early in embryogenesis. Supposedly, layers of fate restriction would have piled on by the time of terminal differentiation . Would this imply that terminal differentiation triggers a different kind and qualitatively stronger restriction? If so, it would enhance the interpretation of the main results: the requirement of the examined terminal selectors is not simply a result of neuronal subtypes being specified late from a generic neuronal fate. If the authors so wish, it would be interesting to see if non-neuronal genes  can be expressed easier in unc-3 mutants than in the WT.hlh-1 in wt and unc-3 mutants. However, we did not see the ectopic induction of an unc-97 reporter in either wt or unc-3 mutants at any larval stages. Based on these results alone though, we cannot conclude that in unc-3 mutant neurons muscle genes are not accessible for activation. The inability of hlh-1 to activate unc-97 might simply suggest that hlh-1 is insufficient for the activation of unc-97 and may require co-factors. There is evidence that hlh-1 works together with unc-120 and hnd-1 to activate muscle genes, supporting the hypothesis that it may not be sufficient in larval somatic tissues to activate unc-97. This would be analogous to the inability of che-1 to activate ASEL genes gcy-6 and gcy-7 in all somatic larval tissues. We think that this caveat makes the results from this experiment inconclusive and therefore did not include them.We did try this experiment, i.e., we expressed 4) The last paragraph of the Discussion considers possible mechanisms to explain this conundrum but the suggested alternatives seem baroque and difficult to follow. Perhaps this section can be clarified by careful editing.This paragraph has now been edited.5) Of greater concern is the absence of direct evidence that a "terminal selector" transcription factor (UNC-3 in this case) prevents ectopic gene induction by triggering the local application of H3K9 methylation marks to silence transcription. Although the authors perform a convincing genetic epistasis experiment to confirm that the H3K9 modifying enzyme met-2 functions in the unc-3 pathway to restrict "cellular plasticity," this experiment does not rule out the possibility that the met-2 gene product could also affect gene expression by other means. Moreover, immunostaining did not detect a quantitative difference in H3K9me levels in wildtype vs. unc-3 mutant neurons. The authors suggest that unc-3 may affect the distribution of H3K9me marks but not the overall level. This explanation seems plausible but is not directly tested. What is needed here is an experiment to ask if H3K9me marks are specifically applied to off target genes  in neurons that express UNC-3. A ChIP-seq experiment that specifically interrogates genes in the UNC-3-expressing neurons could resolve this question but this set up may not be technically feasible. Have the authors considered other alternative strategies for tackling this question? At the very least, this technical caveat should be directly addressed in the text.gcy-5 lacI/O array to address this question. Specifically, we asked if the localization of H3K9me3, HPL-2, HPL-1 or MET-2 changes at the gcy-5 LacI/LacO transgenic locus in wt vs. unc-3 mutant neurons. This, however, also proved technically unreliable for the following reasons: For detecting H3K9me3, we performed immunostaining and tried to ask if the colocalization between the LACI::GFP (bound at the gcy-5 LacO locus) and H3K9me3 changes in wt and unc-3 mutants. However, this staining procedure required an acetone/methanol fixation, which did not preserve the chromatin architecture , and co-staining experiments were therefore unreliable. We also tried to measure the co-localization of HPL-1/2 and MET-2 using the mKATE-2 tagged CRISPR alleles at the gcy-5 LacI/O locus, but could not reliably image fluorescence because of low expression levels in neurons. The fact that the manuscript does not show the functional relationship between unc-3 and met-2 mediated chromatin effects has now been further clarified by the addition of these attempted experiments and an edited Discussion.Yes, a cell-specific ChIP-seq would be the ideal experiment, however it is technically challenging. In the absence of this, we did try to use the


Escherichia coli AlkB protein catalyzes the oxidative demethylation of 1-methyladenine (1-meA) and 3-methylcytosine (3-meC) in both DNA and RNA. AlkB homolog 3 (ALKBH3) was also shown to demethylate 1-meA and 3-meC (induced in single-stranded DNA and RNA by a methylating agent) to reverse the methylation damage and retain the integrity of the DNA/RNA. We previously reported the high expression of ALKBH3 in clinical tumor specimens and its involvement in tumor progression. In this study, we found that ALKBH3 effectively demethylated 1-meA and 3-meC within endogenously methylated RNA. Moreover, using highly purified recombinant ALKBH3, we identified N6-methyladenine (N6-meA) in mammalian transfer RNA (tRNA) as a novel ALKBH3 substrate. An in vitro translation assay showed that ALKBH3-demethylated tRNA significantly enhanced protein translation efficiency. In addition, ALKBH3 knockdown in human cancer cells impaired cellular proliferation and suppressed the nascent protein synthesis that is usually accompanied by accumulation of the methylated RNAs. Thus, our data highlight a novel role for ALKBH3 in tumor progression via RNA demethylation and subsequent protein synthesis promotion.The mammalian AlkB homolog (ALKBH) family of proteins possess a 2-oxoglutarate- and Fe(II)-dependent oxygenase domain. A similar domain in the  Escherichia coli (E. coli) AlkB protein is a 2-oxoglutarate (2-OG)- and Fe(II)-dependent oxygenase that catalyzes the direct oxidative demethylation of 1-meA and 3-meC and plays a central role in DNA and RNA methylation damage repair12245in vitro cell growth and in vivo tumor growth in a xenograft modelSimilar to AlkB, ALKBH3 expresses preferential demethylase activity for 1-meA and 3-meC in single-stranded DNA (ssDNA) over double-stranded DNA (dsDNA), whose methylation is induced by a methylating agent1Accumulating evidence has established the association between DNA repair deficiencies and human diseases, including cancers, neurological diseases, and developmental defects131415in vitro. Moreover, ALKBH3 knockdown increases the 1-meA level in RNA and decreases nascent protein levels in the PANC-1 cell line. These findings contribute to novel progress in the field of RNA epigenetics.We report here that ALKBH3 expresses demethylation activity against 1-meA and 3-meC in RNA as well as N6-methyladenine (N6-meA) in only tRNA within endogenously methylated RNA bases. The demethylation of tRNA by recombinant ALKBH3 significantly enhances protein translation efficiency E. coli recombinant ALKBH3. First, we focused on 1-meA, 3-meC, N6-meA, and 5-meC. The reason is that the methylating agent-induced 1-meA and 3-meC in DNA/RNA are elucidated to be demethylated by ALKBH3, and N6-meA in mRNA was recently clarified to be a substrate for ALKBH5 and FTO (ALKBH9)15Various RNA bases are known to be methylated, including 1-meA, 3-meC, 5-methylcytosine (5-meC), and N6-meA. To evaluate the RNA demethylation activity of ALKBH3, total RNA purified from the human pancreatic cancer cell line PANC-1 was incubated with the silkworm-derived recombinant ALKBH3 proteinTo further investigate the substrate preference of ALKBH3, we incubated tRNA, messenger RNA (mRNA), and ribosomal RNA (rRNA) with the recombinant ALKBH3 and analyzed the methylation status of 1-meA, 3-meC, and N6-meA by LC-ESI-MS/MS. The recombinant ALKBH3 almost completely demethylated 1-meA in all three types of RNAs . On the Since ALKBH5 was recently reported to exhibit demethylation activity for N6-meA in mRNA, we compared the demethylation activities of recombinant ALKBH3 and ALKBH5 proteins purified from silkworm pupae , using cTo confirm the demethylation specificity of ALKBH3 in human RNAs, we size-fractionated the RNAs of PANC-1 cells into two fractions containing RNAs larger and smaller than approximately 200 nucleotides in length, respectively . The larin vitro translation system of luciferase mRNA using rabbit reticulocyte lysate, and the activity of the translated luciferase protein was measured in the incubation mixture by a luminometer. As shown in The difference between ALKBH3 and ALKBH5 in their preference of substrate in the smaller RNA fraction prompted us to examine the effect of ALKBH3 on protein translation through tRNA demethylation. We incubated bovine tRNA with the recombinant ALKBH3 protein or the mock control in the presence of 2-OG and Fe(II), and confirmed the demethylation of 1-meA, 3-meC, and N6-meA by LC-ESI-MS/MS . SubsequALKBH3 gene in the PANC-1 cell line (which has high expression of ALKBH3)Finally, to investigate the effect of ALKBH3-mediated RNA demethylation on protein synthesis in cancer cells, we knocked down ALKBH3 by using siRNAs that target different sequences of the human Over 100 structurally distinct RNA modifications have been identified so farThe function of ALKBH3 has been mainly studied in the context of DNA demethylation. ALKBH3 preferentially demethylates 1-meA and 3-meC in ssDNA over dsDNA that are induced by methylating agents such as methyl methanesulfonate, to repair harmful DNA methylation damage. Recently, it was elegantly shown that ALKBH3 is associated with the helicase ASCC3 to demethylate endogenously methylated 3-meC in ssDNA in prostate cancer cellset al. demonstrated that the luciferase mRNA and E. coli tRNA exposed to methylating agents were repaired by ALKBH3 to recover their functionsIn RNA, repair functions of ALKBH3 on methylated lesions have also been proposed, ALKBH3 can demethylate 1-meA and 3-meC in an RNA oligonucleotide, reactivates bacteriophage ssRNA that had been treated by methylating agents1+ RNA, including mRNA, and is relatively abundantly located near the stop codons and in long internal exons as well as in the 3′UTR of mRNA222729Evidence is accumulating with regard to the location and function of N6-meA, which N6-meA is the most abundant internal modification in poly(A)Recently, FTOin vitro translation was increased by addition of ALKBH3-treated tRNA compared with control tRNA, and that knockdown of ALKBH3 in PANC-1 cancer cells significantly suppressed the translation of nascent protein accompanying the accumulation of 1-meA in the tRNA-enriched smaller RNA fraction. These results indicate that the demethylation of tRNA catalyzed by ALKBH3 would affect protein translation efficiency in cells. Although the mechanism remains unclear, aminoacylation of bacterial tRNA treated with the methylating agent dimethyl sulfate was reported to be inhibitedin vivo.Other important findings in this study are that the efficiency of In summary, our findings reveal that ALKBH3 demethylates endogenously methylated 1-meA and 3-meC in RNA as well as N6-meA in tRNA and that ALKBH3-modified tRNA increases protein translation efficiency. These results represent new findings in RNA epigenetics. Moreover, although further investigation is required to understand the molecular relationship between methylated tRNA bases and the translation machinery, ALKBH3 demethylase would be a promising therapeutic target for cancer with a novel action mechanism of regulating RNA methylation.2 atmosphere in RPMI 1640 medium  supplemented with 10% heat-inactivated fetal calf serum and 100 μg/ml kanamycin.Bovine liver tRNA and calf liver rRNA were purchased from Sigma-Aldrich . Bovine kidney mRNA was purchased from Clontech Laboratories, Inc. . The human pancreatic cancer cell line PANC-1 was obtained from the American Type Culture Collection  and was grown at 37 °C under 5% COTotal RNA and a larger RNA fraction (excluding RNAs of less than 200 nucleotides in length) were isolated from the PANC-1 cells with the miRNeasy Mini Kit  according to the manufacturer’s protocol. A smaller RNA fraction (enriched RNAs of less than 200 nucleotides in length) was isolated from the PANC-1 cells with the miRNeasy Mini Kit and RNeasy MinElute Cleanup Kit (QIAGEN) according to the manufacturer’s protocol. The purified RNA was analyzed with an Experion automated electrophoresis system using the RNA StdSens Analysis Kit .4. Subsequently, the RNAs were purified by ethanol precipitation for further examination.Recombinant FLAG-His-tagged ALKBH3 was expressed in silkworm pupae and purified by column chromatography as described previously2O) and then incubated for 2 h at 45 °C. Subsequently, 5.5 μl of 1 M ammonium bicarbonate and 0.002 units of venom phosphodiesterase II (Wako) were added to the solution. The incubation was continued for an additional 2 h at 25 °C. Thereafter, the mixture was incubated for 1 h at 37 °C with 0.5 units of alkaline phosphatase . Then, 1.3 μl of 0.1 N HCl, 50 μl of H2O, and 20 μl of chloroform were added to the mixture. The sample was vortexed and the resulting suspension was centrifuged for 5 min at 5,000 g. The aqueous layer was collected and evaporated to dryness. The resulting nucleoside residues were solubilized in Milli-Q water . Liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) analyses were performed on a Waters ACQUITY UPLC system  coupled to a Quattro Premier XE triple quadrupole mass spectrometer (Waters). LC separations were carried out on a COSMOSIL Cholester 2.5 μm, 2.0 × 100 mm column  at 50 °C, at a flow rate of 0.3 ml/min. The mobile phase consisted of solvent A (5 mM ammonium formate and 0.2% (v/v) formic acid) and solvent B (acetonitrile), starting with 100% solvent A/0% solvent B for 2 min, followed by a 3-min linear gradient of 0 to 10% solvent B, a 1-min linear gradient of 10% to 90% solvent B, 4 min with 90% solvent B, and 5 min re-equilibration with the initial mobile phase conditions. The data at one run were acquired for 15 min. The mass spectrometer was operated using an ESI source in the positive mode. ESI-MS/MS was conducted in the negative-ion mode. The ionization parameters were capillary voltage, 3.0 kV; extractor voltage, 2 V; source temperature, 120 °C; desolvation temperature, 350 °C; desolvation gas flow, 800l/h; and cone gas flow, 50l/h. The selected reaction monitoring (SRM) transitions (m/z of precursor ion/m/z of product ion) and parameters (cone voltage and collision energy) for nucleosides are listed in Five microliters of 0.1 M ammonium acetate (pH 5.3) and 0.5 units of nuclease P1 (Wako) were added to the purified RNA sample  was used. The reaction was performed for 10 min at 30 °C in a 10 μl reaction mixture, containing 7.0 μl of Flexi rabbit reticulocyte lysate, 0.1 μl of 1 mM amino acid mixture without leucine, 0.1 μl of 1 mM amino acid mixture without methionine, 0.28 μl of 2.5 M potassium chloride, 0.2 μg of luciferase control RNA, and silkworm recombinant ALKBH3- or mock control-treated bovine tRNA. Subsequently, the luciferase activity was measured on a 20/20n luminometer (Promega) using a luciferase assay system (Promega) according to the manufacturer’s protocol.5) were seeded in a 6-well plate and transfected either with 25 nM control siRNA or ALKBH3 siRNA  using the Lipofectamine 2000 Reagent  according to the manufacturer’s protocol. The control and ALKBH3 siRNA sequences were as follows: 5′-auccgcgcgauaguacgua-3′ and 5′-uacguacuaucgcgcggau-3′ for control siRNA; 5′-gagagaagcuucacugaaa-3′ and 5′-uuucagugaagcuucucuc-3′ for ALKBH3 siRNA#1; and 5′-gaaagaagcugacuggaua-3′ and 5′-uauccagucagcuucuuuc-3′ for ALKBH3 siRNA#2. At 48 h after transfection, the cells were harvested. Cell lysates were resolved on a 10% sodium dodecyl sulfate (SDS)-polyacrylamide gel (Bio-Rad) and transferred to a polyvinylidene difluoride membrane . The membranes were blocked with 3% bovine serum albumin at room temperature for 1 h. Thereafter, the membranes were incubated overnight with anti-ALKBH3 antibody  at 4 °C or for 1 h with anti-β-actin antibody (Sigma-Aldrich) at room temperature. This was followed by incubation with horseradish peroxidase (HRP)-conjugated anti-rabbit IgG or anti-mouse IgG  for 1 h. Bound HRP conjugates were visualized using the enhanced chemiluminescence reagent  and captured with the ImageQuant LAS 4000 imager .PANC-1 cells  and RNeasy MinElute Cleanup Kit (QIAGEN) according to the manufacturer’s protocols. The purified RNA samples were denatured at 95 °C for 5 min and then immediately chilled on ice. Two-fold serial dilutions of the denatured RNA samples were spotted on a PVDF membrane. The membrane was washed with 2× saline sodium citrate buffer, air-dried, and baked at 80 °C for 2 h. The membrane was blocked with 5% skim milk in phosphate-buffered saline for 1 h at room temperature and then incubated overnight with anti-N1-methyladenosine antibody  at 4 °C, followed by incubation with HRP-conjugated anti-mouse IgG antibody. Bound HRP conjugates were visualized using the enhanced chemiluminescence reagent .in vitro using the Click-iT AHA Alexa Fluor 488 Protein Synthesis HCS Assay . At 48 h after transfection of cells with ALKBH3 siRNA, the culture medium was replaced with methionine-free RPMI 1640 medium  containing 50 μM of the methionine analog l-azidohomoalanine (AHA) and the cells were incubated for 2 h. The medium was then replaced to remove free AHA. The cells were fixed with 3.7% formaldehyde for 15 min and permeabilized with 0.5% Triton X-100 for 20 min at room temperature. The AHA was stained using a Click-iT reaction cocktail (with fluorescein isothiocyanate (FITC)), and the nuclei were stained using Hoechst 33342 dye. Fluorescence measurement was carried out by using the Envision Multilabel Reader  with the following filters: for Hoechst 33342, excitation/emission = 340/440 nm; and for FITC-Alexa Fluor 488, excitation/emission = 485/535 nm. The nascent protein synthesis ability was calculated from the fluorescence intensities of FITC-Alexa Fluor 488/Hoechst 33342.Nascent protein synthesis was measured t-test.Statistically significant differences between the control group and the treated group were determined using the unpaired Student’s How to cite this article: Ueda, Y. et al. AlkB homolog 3-mediated tRNA demethylation promotes protein synthesis in cancer cells. Sci. Rep.7, 42271; doi: 10.1038/srep42271 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


For somex vivo reported in 2011 indeed brings hope to these patients [in vitro and the resulting meiotic cells can further give rise to healthy and fertile offspring via microinsemination. This culture method has later been successfully applied to cryopreserved mouse testis tissues [ex vivo, the efficiency is no doubt a major concern. The proportion of meiotic cells in cultured testis explants (around 1.71 %) is much lower than that in the mature testis (over 50 %) [in vitro. Such exploitations will not only help characterization of the mechanisms underlying spermatogenesis but also would speed up the clinical application for treating male infertility.The success in generating functional sperm patients . Using t tissues . Howeverer 50 %) . Thus, dBmp8a, but not Bmp8b, was expressed abundantly in the mouse spermatogonia. Unlike most BMPs, BMP8A protein activated not only canonical SMADs 1, 5, and 8 (SMAD1/5/8) signaling but also SMADs 2 and 3 (SMAD2/3) signaling in the mouse spermatogonia. Through signal dissection and receptor characterization, we clarified that the resulting SMAD2/3 signaling, potentially through activation of receptor complexes formed by ALK5 type I receptor and ACVR2A, ACVR2B, or TGFBR2 type II receptor, promoted the proliferation of spermatogonia, whereas the resulting SMAD1/5/8 signaling, potentially through activation of receptor complexes formed by ALK3 type I receptor and ACVR2A or BMPR2 type II receptor, can direct the subsequent differentiation of spermatogonia. Taken as a whole, the dual functions exerted by BMP8A may increase the proportion of differentiating spermatogonia to enter meiosis. Thus, BMP8A can be potentially developed as the first kind of extrinsic spermatogenic activator supplemented in the culture to improve the spermatogenesis efficiency ex vivo.Recently, our data demonstrated that bone morphogenetic protein 8A (BMP8A) can act as a novel spermatogenic activator . As compin vitro [in vitro. In summary, by characterizing the profiles of spermatogenic activators contributing to different stages of spermatogenesis, an efficient cultured procedure using these factors may be developed to recreate limitless cycles of spermatogenesis in vitro and thus will benefit future treatment for male infertility.Although supplement with BMP8A significantly increased the final outcome of meiotic cells in cultured testis explants, some concerns should be noted. Firstly, we demonstrated that the BMP8A-induced spermatogonia were tended to differentiate rather than to maintain stemness; this may exhaust the stem cell pool after one round of spermatogenesis. Secondly, BMP8A signaling alone seems not be sufficient for spermatogonia to trigger the initiation of meiosis, as reflected by no change in some meiosis-related gene in treated spermatogonia. This indicates that finding of other spermatogenic activators capable of promoting the completion of diverse stages of spermatogenesis is demanded. Complying with the above concept, several soluble molecules can be considered. For example, colony stimulating factor 1 may be tested to serve as an extrinsic spermatogenic activator that helps expansion of stem cell population in the culture system, as addition of this factor has been shown to enhance the self-renewal of spermatogonial stem cells in vitro . Retinoi


Here we confirm viral RNA recombination in vivo using an alphavirus, the SAV3 subtype of Salmon pancreas disease virus. The virus causes pancreas disease in Atlantic salmon and heavy losses in European salmonid aquaculture. Atlantic salmon were injected with a SAV3 6K-gene deleted cDNA plasmid, encoding a non-viable variant of SAV3, together with a helper cDNA plasmid encoding structural proteins and 6K only. Later, SAV3-specific RNA was detected and recombination of viral RNA was confirmed. Virus was grown from plasmid-injected fish and shown to infect and cause pathology in salmon. Subsequent cloning of PCR products confirming recombination, documented imprecise homologous recombination creating RNA deletion variants in fish injected with cDNA plasmid, corresponding with deletion variants previously found in SAV3 from the field. This is the first experimental documentation of alphavirus RNA recombination in an animal model and provides new insight into the production of defective virus RNA.RNA recombination in non-segmented RNA viruses is important for viral evolution and documented for several virus species through  Togaviridae21367Alphavirus is one of two genera in the family in vitroin vitro has been documented experimentally in transfected cells in the early nineties12in vivo across all susceptible species.Recombination in RNA viruses refers to the process that occurs within a single genomic segment during virus replication. The copy-choice model describes polymerase switching between templates during RNA synthesis10in vitro and formation of infectious virusin vivo. We used Atlantic salmon, one of the species susceptible to SAV3 infection, and we have documented for the first time recombination of alphavirus RNA in an animal model. Virus was grown in cell culture from heart of FL-∆6K/Helper-6K injected fish and shown to be pathogenic to salmon in experimental challenge.In a previous study on the SAV3 subtype of SPDV, we documented that infectious virus (with full-length genome) is present alongside with numerous RNA deletion mutants in heart of clinically diseased Atlantic salmon, and we hypothesised that recombination of genomes was the explanation for thisFirst, we aimed to document presence of viral RNA transcripts following injection with plasmid/plasmid mixtures. Atlantic salmon parr were injected intramuscularly (i.m.) with a combination of a cDNA plasmid expressing full-length SAV3 genome with the 6K-gene deleted (FL-∆6K) and a helper cDNA vector (Helper-6K) encoding the structural genes including 6K . SAV3-sp3 TCID50Experimental infection with live virus results in pathological changes in heart, pancreas and skeletal muscle when given at doses above 10in vivo.The 6K gene is required for replication and production of infectious virusnd passage cells inoculated with heart tissue from individuals 3w-1 and 3w-2, 3 days post inoculation (dpi)  appeared for fish no. 3w-1 and 3w-2 , was used for challenge studies. The obtained titre was 106.8 TCID50/ml, and before subsequent use RNA including recombined sequences were confirmed as described above (amplification of unique SAV3 FL-∆6K encoded RNA and Helper-6K RNA). The entire viral genome of 3w-2H isolate was also sequenced confirming it to be identical to the original SAV3-H10 genome sequence, with the exception of a C1375G mutation of nsp3, resulting in a Q459E substitution.Our next focus was to show that virus could be isolated from target/internal organs. Organ material (heart/kidney) from the real-time PCR positive fish  were proon (dpi) . At 3rd and 3w-2 . For theand 3w-2 . Supernath passage, in vivo experiment. SAV3 RNA was detected by PCR in all individuals sampled at 4 and 6 wpi  H10 isolate (GenBank ref. no. JQ799139)Oncorhynchus keta) heart cells (CHH-1) were used to grow the virus and were obtained from the European Collection of Cell Cultures (ECACC), maintained at 20 °C in Leibovitz’s L-15 media with GlutaMAXTM (Invitrogen), supplemented with 5% foetal bovine serum (FBS) (Sigma Aldrich) and 50 μg/ml gentamicin.Chum salmon  for both experimental in vivo studies were obtained from the Norwegian institute for water research (NIVA), Solbergstrand, Norway. The average individual weight was 50 g in the first and 28 g in second in vivo study. Both studies were conducted in fresh water (city water) at the aquarium facilities of The Norwegian University of Life Science/Norwegian Veterinary Institute in Oslo, Norway. In the first in vivo study, the water temperature was 12 ± 1 °C, while in the second study the water temperature was 7 °C the first two weeks and 10 ± 1 °C the remaining four weeks. Six randomly selected fish used in the first study, were tested for persistent infection with infectious pancreatic necrosis virus (IPNV) by PCR and low levels of viral RNA was detected in two. Fish were negative for salmon pancreas disease virus (n = 10). Fish were anaesthetized with 30–40 mg/litre benzocaine prior to handling, i.e. injection or sampling. Fish were euthanized by a sharp blow to the head after being put in deep anaesthesia. All experiments were approved by The Norwegian Animal Research Authority and the local IACUC of the Norwegian University of Life Sciences and carried out in compliance with national regulation for the use of animals in experimental research.Atlantic salmon parr  and the helper cDNA plasmid (Helper-6K) are described in Guo 2O in a total of 100 μl for the FL-∆6K/Helper-6K group, or 20 μg/fish for FL-∆6K group (100 μl injection volume). Fish from the two groups were kept in separate tanks and a third tank with 10 non-injected parr was included as negative control (dH2O injected). Ten fish per experimental tank were sampled once a week for five weeks post injection (wpi). At 4 wpi, the number of fish sampled from the two experimental tanks was reduced to 6 and 7, due to mortality experienced between 3 and 4 wpi. The mortality was caused by a Saprolegnia infection, commonly seen in recirculating systems and fish handled/stressed. The infection was treated with malachite green (10 mg/L). From the dH2O -injected fish in the control tank no mortalities occurred and five individuals were sampled at each time point, 0 weeks and 5 weeks after onset of the experiment .Atlantic salmon parr were used in the study. 50 individuals were randomly selected for injection with a plasmid mix of FL-∆6K and Helper-6K and 50 were selected for injection with FL-∆6K only. The fish were injected intramuscularly with 20 μg of each plasmid  diluted in dH® (Invitrogen). Parallel samples of heart and head kidney were preserved on transport medium (Leibovitz’s L-15 supplemented with 100 mg/ml gentamicin and 30% glycerol). Samples from heart and pancreas were submerged in 10% phosphate-buffered formalin, embedded in paraffin and stained with haematoxylin and eosin using standard methods. Histopathological changes in heart and pancreas was evaluated as describedHeart and head kidney tissue were collected and preserved in RNAlater® Fibrous tissue mini kit on heart specimens and RNeasy®mini kit (Qiagen) on kidney, all according to the kit protocols. On-column DNAse treatment was included for all samples. The tissue was homogenized in kit RLT buffer with β-mercaptoethanol using steel beads in a FastPrep-24 homogenizer . RNA was extracted from cell supernatants using QIAamp Viral RNA mini kit (Qiagen) according to the protocol of the manufacturer. RNA was quantified using the Nanodrop ND-1000 spectrophotometer (NanoDrop Technologies). RNA was denatured at 95 °C for 2.5 minutes and transferred directly to ice immediately before cDNA synthesis was performed with SuperScript® III First-Strand Synthesis SuperMix for qRT-PCR (Thermo Fisher Scientific), according to the protocol, using 500 ng RNA in the reaction for heart and kidney samples. For a few samples with RNA concentration too low to include 500 ng, maximum volume of RNA possible was used. Real-time PCR analysis was conducted with Platinum SYBR Green qPCR SuperMix UDG (Thermo Fischer Scientific) as earlier described® 96 Real-time PCR system (Roche), with primers targeting E2 gene. A conventional PCR was also used as an alternative to real-time PCR, where Q5® High-Fidelity DNA Polymerase (New England BioLabs) was used in combination with primers E1- Fwd and E1- Rev (RNA was extracted from heart and kidney tissue using the RNeasy E1- Rev  defining E1- Rev  and run TM) or Q5® High-Fidelity DNA Polymerase for 35 cycles. The products were visualized by gel electrophoresis and products of approximately 2.9 kb were excised and purified with QIAquick gel extraction kit (Qiagen). PCR products were ligated into the pCR 2.1 vector using TOPO TA cloning kit (Invitrogen) before subsequently being transformed into competent OneShot TOP10 bacterial cells (Invitrogen), after manufacturer’s procedures. The insert of purified plasmids of one to six clones was sequenced by commercial services (GATC biotech) using standard vector primers and sequencing primers  at 14dpi unless cytopathic effect (CPE) was observed (late passages). Supernatant was clarified by centrifugation before transferring to a naïve cell culture. Anti-IPNV antiserum (K262) was added to the inoculum up to 4th passage, and real-time PCR confirmed all supernatants IPNV negative. IPNV real-time PCR was performed as described above using specific IPNV primers . IPNV was neutralized by adding K262, a custom made rabbit serum to IPNV primers .th and final supernatant were determined by endpoint dilution on CHH-1 cells grown in 96-well plates, estimating the TCID50 by the method of Kärbernd passage using a polyclonal antibody against SAV3 structural proteinsSAV3 titre of the 56.8 TCID50 of recombined SAV3 (3w-2H isolate) from the 5th cell culture passage. 10 salmon parr were injected with 100 μl PBS, kept in a separate tank and used as negative controls. Six fish were sampled from the challenge tank at 4 and 6 wpi. Five fish from the negative control tank were sampled at 0 and 6 wpi. Sampling was performed and the samples preserved and analysed as described above. Presence of SAV3 antigens in situ in heart and pancreas was documented by immunohistochemistryA challenge study was conducted using 22 Atlantic salmon parr. In the experimental tank, 12 fish were injected intramuscularly with 100 μl 10How to cite this article: Petterson, E. et al. Experimental piscine alphavirus RNA recombination in vivo yields both viable virus and defective viral RNA. Sci. Rep. 6, 36317; doi: 10.1038/srep36317 (2016).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


The transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables “dual RNA-seq” studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique. The application of high-throughput sequencing–based transcriptomic technologies has delivered major advances in our understanding of biological processes in essentially every organism analyzed . The higFive years ago, we coined the term “dual RNA-seq” to refer to the simultaneous RNA-seq analysis of a bacterial pathogen and its infected host  and theoThis newfound feasibility has led to a variety of emerging applications of dual RNA-seq to bacterial infection models, including the direct correlation of bacterial gene activity with a specific host response and the identification of “molecular phenotypes” of pathogen genes that are invisible in standard virulence assays . Here, wChlamydia trachomatis [ribBA) responding to extracellular reduction of iron , in contrast to an earlier microarray-based report in which only few changes in host transcription were observed during early infection [Most dual RNA-seq analyses so far have been exploratory, characterizing the transcriptional dynamics of a particular infection system. An early dual RNA-seq study of HEp-2 epithelial carcinoma cells infected with the obligate intracellular pathogen chomatis  revealed of iron . These cnfection .Haemophilus influenzae [dipeptide transport system permease protein (dpp) operon, whose gene products contribute to the protection against oxidative stress  strains—one being replication-competent and the other susceptible to killing by the host—in primary murine bone marrow–derived macrophages [phage shock protein A (pspA), led to a survival defect compared to the cognate wild-type strain , the previously uncharacterized Salmonella PinT sRNA was consistently and highly induced during infection of 14 distinct cell types. Biocomputational clustering of expression kinetics along a high-resolution time-course of infected HeLa cells predicted that PinT is activated by the PhoP/Q two-component system, which regulates intracellular virulence  untisolation .Salmonella-infected HeLa cells, we evaluated eight commonly used transcriptome stabilization techniques , previously been used to fix infected tissue samples [later. Therefore, transcriptome stabilization should be optimized empirically for any infection model. Promising recent studies have demonstrated the compatibility of paraformaldehyde-based fixation with cell sorting and, importantly, high-quality RNA isolation [To minimize unwanted transcriptomic changes during sample processing, the RNA content of infected cells may be stabilized. Two preservation strategies exist: Alcohol- or ammonium sulfate–based preservatives inactivate RNases and RNA polymerases by denaturing cellular proteins through the removal of water. In contrast, formaldehyde-containing fixatives induce intra- and intermolecular cross-links between amino groups and thereby block de novo transcription or RNA decay. In the context of dual RNA-seq, besides leaving cells physically intact to enable cell sorting, transcriptome stabilization must avoid quenching fluorescent signals  or interfering with high-quality RNA isolation (which is problematic with cross-linked samples). In our recent study of erial of ). For th samples ,19,21 ; this cVibrio cholera infection in a juvenal rabbit model [Salmonella at early time points of infection [This naturally raises the question: how many cDNA reads are enough? Differential expression power analyses universally favor biological replication over sequencing depth, particularly once a minimum depth threshold has been attained. For eukaryotes, increasing sequencing depth appears to have diminishing returns after around 10–20 million nonribosomal RNA reads ,37—thougit model  showed tnfection . Thus, wThe broad strokes of dual RNA-seq analysis differ little from conventional RNA-seq ,41: sequSalmonella and mammalian hosts [Much complexity derives from working simultaneously with multiple genome sequences. Although this can be done easily by including all replicons of both organisms as references during mapping, it is important to determine the selectivity of read mapping to both genomes, as cross-mapping reads will affect transcript quantification. In practice, with standard Illumina read lengths of 75–150 bases, we observe negligible cross-mapping in the case of an hosts , with moan hosts , which ran hosts , containan hosts  can be uOnce mapping has been completed, normalization and quantification are required. Within-sample normalization methods, such as transcripts per million (TPM) , often sScaling normalization techniques address differences in sequencing depth between RNA-seq experiments. However, there are many other factors besides read depth which can introduce unwanted variation in high-throughput experiments and lead to reduced power in downstream analyses, commonly referred to as “batch effects” . Within Traditionally, batch effects were accounted for by incorporating date as a nuisance factor in differential expression analysis . While tR statistical programming language with packages available through the Bioconductor framework [p-value calculations. While these tools work with predefined annotations and ignore differential isoform usage, RNA-seq also raises the possibility of directly defining boundaries of eukaryotic transcripts, which are typically subject to regulated alternative splicing [R [Differential expression analysis forms the backbone of most RNA-seq analyses, most frequently done in the ramework . Popularramework , DESeq2 ramework , and limramework . These tramework –72: DESesplicing . A rangesplicing , though splicing  have beeicing [R  and therDrosophila embryos [Most of the published dual RNA-seq experiments have involved a time-course and analyzed differential expression by pairwise comparisons; however, this effectively ignores the temporal relationship between samples. Changes in transcript expression can be assumed to be smooth for most genes over time, and this assumption can be used to increase the power of analyses: in effect, contiguous samples act as partial replicates for one another, allowing for more accurate estimation of expression variance. While this does not remove the need for replication, it does raise the possibility of more informative designs than simple replication. For instance, rather than repeatedly sampling the same time points, replicate experiments could be staggered in time so as to provide higher temporal resolution while also demonstrating reproducibility. While not frequently used in the literature, such analyses are possible in analysis packages supporting generalized linear models, such as edgeR and limma/voom, by performing differential expression analysis along fitted curves . We hopSalmonella Gene Expression Compendium,” which collects expression data for 22 infection-relevant conditions [The outcome of differential expression analysis is a long list of genes for both bacteria and host, which must be interpreted in terms of gene function to produce testable hypotheses. Several databases provide suits for this purpose, though none provide complete information for either eukaryotic cells or bacteria. Popular databases include the Gene Ontology (GO)  and the nditions .Dual RNA-seq crucially depends on proper statistical analysis in order to determine gene sets significantly differentially expressed during infection. Originally developed for microarray experiments, many of these techniques remain poorly tested on RNA-seq datasets. Technical issues, such as biases towards detecting differential expression in longer transcripts in sequencing data as compared to array data , have maSynechocystis and its response to varying light intensities to identify putative directional interactions [Salmonella infection of HeLa cells, linking virulence gene expression in Salmonella to the induction of host immune signaling through the Janus kinase-Signal Transducer and Activator of Transcription (JAK-STAT) pathway [Candida albicans and murine host cells [Dual RNA-seq can also be directly used to infer links between genes through so-called network inference (NI) approaches which are popular in reconstructing global regulatory networks from large collections of expression data in diverse conditions ,85. NI mractions . We appl pathway . More cost cells ,87. Whilst cells .Yersinia pseudotuberculosis gene expression in the mouse cecum was able to discriminate between various intestinal bacterial species [Streptococcus spp. and influenza virus [Chlamydia spp. and human herpes virus [While the potential of dual RNA-seq in cell culture–based infection models has clearly not yet been exhausted, the next steps in the development of this technique are already on the horizon. For example, “Multi RNA-seq” was applied to characterize the human airway epithelium in conjunction with the commensal bacteria populating it ; similar species  , and the development of single-cell dual RNA-seq. With respect to the former, several studies suggest widespread differences in bacterial behavior during the infection of two-dimensional monocultures compared to that of three-dimensional tissue ,96 and wruginosa  and in arculosis . In bothSingle-cell dual RNA-seq promises to be a game changer in the study of those many bacterial pathogens that are known to form specific, phenotypically distinct subpopulations during infection , often aIn summary, dual RNA-seq is an emerging technique to profile gene expression changes that accompany infection of mammalian cells by bacterial pathogens. Unlike traditional approaches, dual RNA-seq has proven capable of capturing host and pathogen transcriptomes simultaneously, providing direct insight into host–pathogen interplay. However, dual RNA-seq is still in its infancy, and future efforts—with respect to both experimental aspects and bioinformatics—will be required to exploit its full potential.


Long non-coding RNA (lncRNA) is a kind of non-coding RNA (ncRNA), with a length of 200 nt to 100 kb, that lacks a significant open reading frame (ORF) encoding a protein. lncRNAs are widely implicated in various physiological and pathological processes, such as epigenetic regulation, cell cycle regulation, cell differentiation regulation, cancer, and neurodegenerative diseases, through their interactions with chromatin, protein, and other RNAs. Numerous studies have suggested that lncRNAs are closely linked with the occurrence and development of a variety of diseases, especially neurodegenerative diseases, of which the etiologies are complicated and the underlying mechanisms remain elusive. Determining the roles of lncRNA in the pathogenesis of neurodegenerative diseases will not only deepen understanding of the physiological and pathological processes that occur in those diseases but also provide new ideas and solutions for their diagnosis and prevention. This review aims to highlight the progress of lncRNA research in the pathological and behavioral changes of neurodegenerative diseases. Specifically, we focus on how lncRNA dysfunctions are involved in the pathogenesis of Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis. In the human genome, less than 2% of the transcripts encode proteins, and the remaining 98%–99% are non-coding RNAs (ncRNAs) .5Neurodegenerative disease is characterized by the loss of neurons or myelin in the brain and spinal cord, deteriorating over time and leading to dysfunction.lncRNAs were first found in rat full-length cDNA sequence libraries, usually overlapping or dispersed between transcripts. According to location and context, lncRNA can be divided into five categories, including inter-gene long-chain non-coding RNA , intron long-chain non-coding RNA , sense long-chain non-coding RNA , antisense long-chain non-coding RNA , and bidirectional long-chain non-coding RNA  .8, 9Tabl9At present, the source of lncRNA is not very clear. Ponting et al.in vivo, mediating the degradation of lncRNA and thus regulating its cell biological functions. On the other hand, lncRNA can act as a bait molecule for miRNA, targeting miRNA by target mimicry and inhibiting its further action, thus indirectly regulating the expression of miRNA target genes. In addition, lncRNA can act as an endogenous competitor of miRNA by binding miRNA-binding sites on mRNA.lncRNA is located in the nucleus or cytoplasm and lacks the ability to encode proteins. Initially, biologists thought that lncRNA had no biological function and was only the “noise” of genomic transcription, a byproduct of the activity of RNA polymerase II (RNA PII).Alzheimer’s disease (AD) is the most common cause of dementia. Deposition of beta-amyloid proteins (amyloid beta-peptide [Aβ]) in brain tissue, which can induce senile plaques, is one of the important factors underlying AD pathogenesis.Aβ is a normal metabolite generated by the hydrolysis of β-amyloid precursor protein (APP). β-site APP cleaving enzyme 1 (BACE1), a membrane-bound aspartic protease, is involved in the processing of APP and cleaves it to Aβ. BACE1-AS (BACE1-antisense) is an antisense transcript of BACE1. The expression of BACE1-AS in the brain of AD patients is upregulated, suggesting that BACE1-AS may play a role in the pathogenesis of AD.Brain cytoplasmic (BC) RNA is another lncRNA that causes AD and brain aging. Mouse BC1 RNA and human BC200 RNA are lncRNA transcripts that are transported as ribonucleoprotein particles to the dendritic processes and bind to poly(A)-binding protein (PABP1), a regulator of translation initiation, thus regulating gene expression at the translational level.Under inflammatory stimulation, lncRNA-17A can direct G-protein-coupled receptor 51 (GPR51) splicing to produce isoform variant B of the B-type receptor for the neurotransmitter g-aminobutyric acid . Because only the canonical variant, isoform A, contains the complete C-terminal portion needed to interact with GABAB R1 to generate a functional heterodimeric receptor, this alternative splicing causes the synthesis of a non-functional GABAB receptor. In addition, the overexpression of 17A causes an overproduction of Aβ.Some lncRNA polymorphisms are associated with AD pathogenesis. For example, rs7990916 (T > C) located in the lincRNA TCONS_00021856/linc-SLITRK5-11 gene showed significant differences between AD patients and a normal control group.Given that aging is also one of the major risks of neurodegenerative diseases, the role of lncRNA in aging cannot be overlooked. Zhang et al.Huntington’s disease (HD), also known as chorea or Huntington’s chorea, is an autosomal dominant neurodegenerative disease characterized by progressive dyskinesias and mental decline.In HD, the Huntingtin (Htt) protein accumulates gradually in cells, forming large molecules that accumulate in the brain, affecting the function of nerve cells, and resulting in the progressive death of the striatum and cortical nerve cells. lncRNA HttAS_v1 is an antisense transcript of the Htt gene and is expressed at a low level in the frontal cortex of HD patients, leading to high expression of Htt mRNA, which in turn promotes HD pathogenesis.38BDNFOS is an antisense transcription product of brain-derived neurotrophic factor (BDNF), which upregulates the transcription of BDNF and the translation of BDNF-mRNA in HD. Small interfering RNA (siRNA) treatment with BDNFOS can induce Htt expression. BDNFOS has a protective effect on neurons and improves the HD phenotype,NEAT1 (nuclear paraspeckle assembly transcript 1) is a nuclear-enriched ncRNA essential for the formation and maintenance of paraspeckles, which are subnuclear bodies found in mammalian cells.To detect ncRNAs involved in the pathogenesis of HD, one study examined the ncRNA expression profile of human HD brain tissue and found that the expression of the lncRNAs HAR1F and HAR1R, which are antisense transcripts of the first human accelerated region 1 (HAR1) gene, was significantly reduced in the striatum. These lncRNAs are involved in neurotransmission, memory structure, and synaptic plasticity in the mature brain, and their aberrant expression is also associated with HD.Parkinson’s disease (PD) is a chronic progressive movement disorder caused by loss of brain dopaminergic neurons. PD is a common neurodegenerative disease in the elderly, with clinical symptoms such as resting tremor, muscle tension instability, and posture instability.Loss or overexpression of PTEN-induced kinase 1 (PINK1) results in abnormal dopamine release and impaired motor function.The ubiquitin carboxy-terminal hydrolase L1 gene (Uchl1) has been shown to be closely related to brain function and neurodegenerative diseases. An antisense transcript of Uchl1, AS Uchl1, can regulate the expression of UCHL1 at the post-transcriptional level and enhance contact between post-transcriptional mRNA and polysaccharides, thus promoting the translation process and increasing protein synthesis. This activity has been disrupted in patients with familial PD, and studies have reported losses of UCHL1 activity in many other neurodegenerative diseases.Previous studies have showed that a-synuclein aggregation is the driving force in PD pathogenesis.Leucine-rich repeat kinase 2 (LRRK-2) is thought to be involved in the initiation/development of PD.Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that has no effective therapeutic means at present. ALS is characterized by the progressive paralysis of the limbs and muscles involved in speech, swallowing, and respiration due to the progressive degeneration of spontaneous motor neurons. In 2011, the repeated amplification of a six-nucleotide motif (GGGGCC) in the protein-coding gene C9ORF72 (chromosome 9 ORF 72) became the first identified causative mutation in ALS and front temporal dementia (FTD).TDP43 (TAR DNA-binding domain protein 43) and FUS/TLS (fused in sarcoma/translated in liposarcoma) are RNA-binding proteins that are predominantly located in the nucleus and play a role in regulating RNA metabolism. Studies have shown that abnormal accumulation of FUS/TLS and TDP43 in the cytosol directly leads to the misfolding of wtSOD1 (wild-type Cu/Zn superoxide dismutase) in non-SOD1 FALS  and SALS (sporadic ALS), which means that they constitute common molecular pathogenesis mechanisms of ALS.61With the rapid development of RNA sequencing technology and computational methods, lncRNA has gradually been recognized by researchers, and the current research regarding lncRNA in neurological diseases has made some progress. The expression patterns of most lncRNAs are more tissue specific than those of their respective mRNAs, suggesting that lncRNAs can be used as molecular markers for disease diagnosis and drug design. In view of the specificity effects of certain lncRNAs, targeted therapeutic drugs can be designed to minimize the impact of other unrelated genes to achieve the purpose of personalized treatment. However, the evidence for the association of lncRNAs with neurological disease is mainly due to differences in expression, and only a few functions of lncRNAs have been clearly demonstrated. Dynamic analysis of changes in the body is constrained by available analytical techniques. Along with the specificity of lncRNA itself, such as its numerous species, the small amount of information contained in the original sequences and the limitation of research methods have contributed to the superficiality of our knowledge of the mechanism of lncRNA action and of other regulatory mechanisms. It remains necessary to continue to pursue in-depth research into the effects of lncRNA and other regulatory mechanisms affected by the microenvironment of the body.The authors have declared that there are no conflicts of interest.


Positive-strand RNA viruses replicate their genomes in membrane-bound replication compartments. Brome mosaic virus (BMV) replicates in vesicular invaginations of the endoplasmic reticulum membrane. BMV has served as a productive model system to study processes like virus-host interactions, RNA replication and recombination. Here we present multiple lines of evidence showing that the structure of the viral RNA replication compartments plays a fundamental role and that recruitment of parental RNAs to a common replication compartment is a limiting step in intermolecular RNA recombination. We show that a previously defined requirement for an RNA recruitment element on both parental RNAs is not to function as a preferred crossover site, but in order for individual RNAs to be recruited into the replication compartments. Moreover, modulating the form of the replication compartments from spherular vesicles (spherules) to more expansive membrane layers increased intermolecular RNA recombination frequency by 200- to 1000-fold. We propose that intermolecular RNA recombination requires parental RNAs to be recruited into replication compartments as monomers, and that recruitment of multiple RNAs into a contiguous space is much more common for layers than for spherules. These results could explain differences in recombination frequencies between viruses that replicate in association with smaller spherules versus larger double-membrane vesicles and convoluted membranes. Viruses are intracellular parasites that depend on host cells for replication ,2,3. VirPositive-strand RNA viruses of plants and animals replicate their genomic RNA on remodeled intracellular membranes. For many such viruses, this genome replication occurs in virus-induced, vesicular RNA replication compartments (spherules) bound to intracellular membranes of the endoplasmic reticulum, peroxisomes, mitochondria or chloroplasts ,22,23,24pol, respectively. 1a is a multifunctional protein that interacts with host proteins to induce the invagination of endoplasmic reticulum membranes to form spherules, recruits genomic viral RNA and the 2apol to replication compartments and provides helicase and RNA capping functions  and andpol, Saccharomyces cerevisiae by expressing viral replication and encapsidation proteins in combination with one or more genomic RNAs . p. ppol webe B3∆5′ B 10]. P. Ppol we′ (pHGR3)B [10] anStandard procedures were used for all DNA manipulations . When nepB3URA3-Vector (pHGR82). pHGR82 is a pUC119-based version of pB3URA3 for cloning purposes. To make pHGR82, the EcoRI-PstI fragment of pHGR11 was replaced with the equivalent fragment from pB3URA3 ..pol. B3ΔThe marked acceptor RNA, B3Δ3′pm, participated in intermolecular RNA recombination at a frequency similar to that of wild type B3Δ3′ D. Forty-Results described above C and bef+ colonies were selected  sho sho−4 pe (15.7%) C. Contra1 layers C. Furthe1 layers C. 2apol pherules C. Results described above show that layers are more permissive to intermolecular RNA recombination than spherules. The low frequency of intermolecular RNA recombinants in spherules cannot be explained by a low number of cells harboring spherular replication compartments, by low abundance of parental RNAs, or by reduced levels of viral RNA polymerase. pol were expressed from the GAL1 promoter  to 1000-fold (GAL1 layers) (pol associated with layer formation might promote template switching (pol accumulation associated with layer formation (pol levels were only 1.2-fold higher in ADH layers that in GAL1 spherules (ADH layers was >200 fold higher (The frequency of intermolecular RNA recombination in plant cells  is simil layers) B higher  layers) C. This d layers)  or the a layers) B,C. Highwitching C, howeveormation C 37] ap apADH lapherules C, but RNd higher . The difference in intermolecular RNA recombination frequency between spherules and layers suggest that their ultra-structure is different in one or more key elements that regulate intermolecular RNA recombination. A model to explain the difference is that layer organization favors two fundamental parts of the recombination process : aggrega2+/Mn2+ into the Golgi from the cytosol [2+ in the replication compartments [Enhanced RNA recombination was detected for Tomato bushy stunt virus (TBSV) in a yeast strain lacking Pmr1p, an ion pump that controls Ca cytosol . Yeast lartments . Similarartments . We cannartments .−1–10−2 recombination events per genome [Poliovirus, a positive-strand RNA virus, undergoes homologous recombination at a frequency estimated to be as high as 10r genome . Early ir genome . Electror genome . Thus, f


Globally, ovarian cancer (OC) is the leading cause of gynecological cancer-associated deaths. Metastasis, especially multi-organ metastasis, determines the speed of disease progression. A multicenter retrospective study was performed to identify the factors that drive metastasis, from medical records of 534 patients with OC. The average number of target organs per patient was 3.66, indicating multi-organ metastasis. The most common sites of metastasis were large intestine and greater omentum, which were prone to co-metastasis. Results indicated that ascites and laterality, rather than age and menopausal status, were the potential drivers for multi-organ metastasis. Cancer antigen (CA) 125 (CA-125) and nine other blood indicators were found to show a significant, but weak correlation with multi-organ metastasis. A neural network cascade-multiple linear regression hybrid model was built to create an ovarian cancer metastasis index (OCMI) by integration of six multi-organ metastasis drivers including CA-125, blood platelet count, lymphocytes percentage, prealbumin, ascites, and laterality. In an independent set of 267 OC medical records, OCMI showed a moderate correlation with multi-organ metastasis (Spearman ρ = 0.67), the value being 0.72 in premenopausal patients, and good performance in identifying multi-organ metastasis (area under the receiver operating characteristic curve = 0.832), implying a potential prognostic marker for OC. Globally, close to 220,000 women develop ovarian cancer (OC) every year . Owing tRecently, Cardenas et al. proposed that the origin and evolution of OC follow a four-step process that includes migration, seeding, induction, and expansion . If the Based on the pathological characteristics of OC as it progresses through the stages, we believe that monitoring tumor cell dissemination can help understand the exact status of the disease as well as help in its effective management. Unfortunately, there are not enough good biomarkers available for monitoring tumor cell dissemination and thereby the pathological progression of OC . A cliniBased on the idea that routine medical examination indicators (MEIs) could be a potential source of biomarkers, we propose an alternative method for monitoring the progression of OC by making full use of the medical examination in clinical practice. Following the concept of CA-125-based combination biomarkers , an inteIn this study, 801 copies of OC medical records were collected from the affiliated hospitals of Harbin Medical University and were divided into two independent datasets including a training set and a validation set Figure . The traBriefly, one copy of a medical record corresponded to one patient who was clinically diagnosed with OC and underwent oophorectomy. A total of 15 possible metastatic sites were intraoperatively examined for each patient. Figure In the training set, about 55% of the patients developed ascites and bilateral ovarian cancer Figure , indepenA receiver operating characteristic (ROC) curve test was performed to explore whether tumor biomarkers or blood/urine test indicators could identify the presence of metastasis in a given organ. Our results suggested that 13 MEIs were significantly associated with metastasis  model was used for further integrating NNC output, ascites, and laterality into a digital number that we named OCMI Figure . CompareDespite being the second most common gynecologic malignancy, OC causes the largest number of gynecological cancer-associated deaths in the world , 18. TheThe epidemiological observation in 534 patients with OC revealed that more than half of the patients had multi-organ metastasis, but merely less than one in five patients showed no metastasis to any of the fifteen organs when first diagnosed. This observation was in line with the proven finding that a large proportion of OC patients actually end up succumbing to non-OC cancer . WidesprCompared to other cancers, OC is the most common cause of the formation of malignant ascites . MalignaIt was verified that NNC-based integration of three blood MEIs markedly enhanced the power of CA-125 to identify high-risk patients. The three MEIs are neutrophil percentage, prealbumin, and blood platelet count. Neutrophils were experimentally validated to promote epithelial-to-mesenchymal transition and OC cell migration , our resAs our previous work suggests –36, relyTwo potential limitations of the present study should be addressed. First, a small patient set was used to create OCMI. Despite an independent validation set being used to verify the effectiveness of NNC and OCMI in identifying high-risk patients, a larger patient set should be definitely tested for optimization of NNC and OCMI and for further assessment of their usefulness in OC management. Second, a correlation analysis between MEIs and multi-organ metastasis was performed on a limited number of MEIs, including age, menopausal status, CA-125, blood and urine test MEIs, ascites, and laterality. In the future study, clinical imaging examination and personal life habits questionnaire should be considered and investigated with equal importance.In conclusion, we provide a new means to evaluate the risk of metastasis and the extent of multi-organ metastasis in patients with OC. Integration of only four to six routine medical indicators is sufficient to make NNC and OCMI more clinically feasible. As a metastasis identification indicator, OCMI is expected to make it possible to effectively evaluate and monitor the rate and direction of disease progression of OC in future clinical practice.This study was approved by the Ethics Committee of the first affiliated hospitals of Harbin Medical University  and was carried out in accordance with the Declaration of Helsinki.Electronic medical record systems of the second and third affiliated hospitals of Harbin Medical University were used to access the medical records of hospitalized patients who were clinically diagnosed with OC and had undergone oophorectomy. The MEIs included age, menopausal status, CA-125, blood and urine tests (68 items), ascites, laterality, and metastatic sites (n = 15). The 15 metastatic sites included bladder, diaphragm, greater omentum, internal genital organ, large intestine, liver, lymph node, mesentery, paracolic sulci, peritoneum, rectouterine fossa, small intestine, spleen, stomach, and ureter. All the medical records were divided into two independent datasets, a training set n = 534,  and a vaIn the training set, the percentage of incidence of metastases was calculated for each site, and a hypergeometric test was performed to evaluate the significance of co-metastasis among all the 15 studied sites. The hypergeometric probability was calculated as follows:i and j, M is the total number of metastases to site i, n is the number of metastases to site j, m is the number of metastases to both sites. A total of 105 hypergeometric tests were performed for the 15 sites. To avoid false positives, all the P values were adjusted by using an EXCEL calculator of Holm-Bonferroni sequential correction developed by Gaetano J [Where N is the total number of metastases involving two sites aetano J . Co-metaaetano J  and Cytoaetano J  were appGraphPad Prism version 6.0  was used for identifying metastasis-related MEIs. First, a ROC curve test was performed to check whether a given MEI could identify single site cancer metastasis with an AUC of more than 0.5 and a P value of less than 0.001. To determine MEIs that were related with multi-organ metastasis, Spearman's correlation test was performed to evaluate the correlation between MEIs and the number of metastatic sites per patient. Spearman's correlation test was applied instead of Pearson's correlation test since some of the MEIs could not pass the D’Agostino-Pearson omnibus normality test and did not comply with the Gaussian distribution. A correlation was considered significant only if |ρ|  was more than 0.1 and P was less than 0.001. Besides, co-linearity among MEIs was checked and graphically displayed in a heatmap using HemI version 1.0.3.3. Co-linearity was determined to be present if a |ρ| of > 0.3 was calculated for any two MEIs.Tr) and the testing subset (RTe). The two correlation coefficients measured the correlation between the predicted and the actual numbers of metastatic sites of a patient. Similar values of RTr and RTe indicate good generalization ability of the model. Finally, the SPSS statistical software version 19.0  was used to build an MLR model to further integrate NNC output and the two intraoperative examination items, ascites and laterality, into a digital parameter, OCMI.All of the MOM-related MEIs were normalized into a 0 to 1 digital number for data unification as previously described . FollowiFor the NNC model, the 10-fold cross-validation method was used for model validation as previously described . Brieflyt-test, Chi-square test, one-way ANOVA test, and Holm-Sidak's multiple comparisons test. In this study, differences were considered as statistically significant when P < 0.001.Data are presented as mean ± standard deviation (SD). GraphPad Prism version 6.0 was applied to conduct the following statistical analyses, including a ROC curve test, D’Agostino-Pearson omnibus normality test, Spearman's correlation test, Student's