EMBL Australia

Osteoclasts are large multinucleated bone-resorbing cells formed by the fusion of monocyte/macrophage-derived precursors that are thought to undergo apoptosis once resorption is complete. Here, by intravital imaging, we reveal that RANKL-stimulated osteoclasts have an alternative cell fate in which they fission into daughter cells called osteomorphs. Inhibiting RANKL blocked this cellular recycling and resulted in osteomorph accumulation. Single-cell RNA sequencing showed that osteomorphs are transcriptionally distinct from osteoclasts and macrophages and express a number of non-canonical osteoclast genes that are associated with structural and functional bone phenotypes when deleted in mice. Furthermore, genetic variation in human orthologs of osteomorph genes causes monogenic skeletal disorders and associates with bone mineral density, a polygenetic skeletal trait. Thus, osteoclasts recycle via osteomorphs, a cell type involved in the regulation of bone resorption that may be targeted for the treatment of skeletal diseases.

Rationale: Aging represents a major risk factor for coronary artery disease and aortic aneurysm formation. MicroRNAs (miRs) have emerged as key regulators of biological processes, but their role in age-associated vascular pathologies is unknown. Objective: We aim to identify miRs in the vasculature that are regulated by age and play a role in age-induced vascular pathologies. Methods and Results: Expression profiling of aortic tissue of young versus old mice identified several age-associated miRs. Among the significantly regulated miRs, the increased expression of miR-29 family members was associated with a profound downregulation of numerous extracellular matrix (ECM) components in aortas of aged mice, suggesting that this miR family contributes to ECM loss, thereby sensitizing the aorta for aneurysm formation. Indeed, miR-29 expression was significantly induced in 2 experimental models for aortic dilation: angiotensin II-treated aged mice and genetically induced aneurysms in Fibulin-4 R/R mice. More importantly, miR-29b levels were profoundly increased in biopsies of human thoracic aneurysms, obtained from patients with either bicuspid ( n =79) or tricuspid aortic valves ( n =30). Finally, LNA-modified antisense oligonucleotide-mediated silencing of miR-29 induced ECM expression and inhibited angiotensin II-induced dilation of the aorta in mice. Conclusion: In conclusion, miR-29-mediated downregulation of ECM proteins may sensitize the aorta to the formation of aneurysms in advanced age. Inhibition of miR-29 in vivo abrogates aortic dilation in mice, suggesting that miR-29 may represent a novel molecular target to augment matrix synthesis and maintain vascular wall structural integrity.

Measurement science has been converging to smaller and smaller samples, such that it is now possible to detect single molecules. This Review focuses on the next generation of analytical tools that combine single-molecule detection with the ability to measure many single molecules simultaneously and/or process larger and more complex samples. Such single-molecule sensors constitute a new type of quantitative analytical tool, as they perform analysis by molecular counting and thus potentially capture the heterogeneity of the sample. This Review outlines the advantages and potential of these new, quantitative single-molecule sensors, the measurement challenges in making single-molecule devices suitable for analysis, the inspiration biology provides for overcoming these challenges, and some of the solutions currently being explored.

Genetic control of metabolism is currently best understood at the level of transcription and epigenetics. Only limited information is available on post-transcriptional regulation of metabolism. While a few metabolic enzymes were previously known to moonlight as RNA-binding proteins in physiologically relevant contexts, recent discoveries highlight that several dozen of metabolic enzymes belonging to a wide spectrum of pathways exhibit RNA-binding activity in living mammalian cells. Abundant RNA–enzyme interactions might suggest novel roles of RNA in affecting enzyme function, for instance, as competitive inhibitors or allosteric regulators. A function of RNA as assembly scaffold for enzyme complexes is also conceivable, with potentially wide-ranging implications for our understanding of how cells organize and control metabolic flux. Finally, enzymes can moonlight as regulators of (m)RNAs, as exemplified by aconitase/IRP1 and GAPDH. In the past century, few areas of biology advanced as much as our understanding of the pathways of intermediary metabolism. Initially considered unimportant in terms of gene regulation, crucial cellular fate changes, cell differentiation, or malignant transformation are now known to involve ‘metabolic remodeling’ with profound changes in the expression of many metabolic enzyme genes. This review focuses on the recent identification of RNA-binding activity of numerous metabolic enzymes. We discuss possible roles of this unexpected second activity in feedback gene regulation (‘moonlighting’) and/or in the control of enzymatic function. We also consider how metabolism-driven post-translational modifications could regulate enzyme–RNA interactions. Thus, RNA emerges as a new partner of metabolic enzymes with far-reaching possible consequences to be unraveled in the future. In the past century, few areas of biology advanced as much as our understanding of the pathways of intermediary metabolism. Initially considered unimportant in terms of gene regulation, crucial cellular fate changes, cell differentiation, or malignant transformation are now known to involve ‘metabolic remodeling’ with profound changes in the expression of many metabolic enzyme genes. This review focuses on the recent identification of RNA-binding activity of numerous metabolic enzymes. We discuss possible roles of this unexpected second activity in feedback gene regulation (‘moonlighting’) and/or in the control of enzymatic function. We also consider how metabolism-driven post-translational modifications could regulate enzyme–RNA interactions. Thus, RNA emerges as a new partner of metabolic enzymes with far-reaching possible consequences to be unraveled in the future. Metabolic enzymes were long considered to be constitutively expressed housekeeping proteins, and even nowadays glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA continues to be broadly used for normalization of real-time quantitative PCR experiments. However, this traditional view is challenged by advances in many areas, including developmental, cancer, and stem cell biology. The expression profiles of metabolic enzymes are controlled by cell identity, which enables tissue metabolic specialization. Furthermore, metabolic enzyme expression is also subject to fine-tuning temporal regulation in response to feast/famine and to day/night cycles (reviewed in [1Hong S.H. et al.Nuclear receptors and metabolism: from feast to famine.Diabetologia. 2014; 57: 860-867Crossref PubMed Scopus (26) Google Scholar, 2Zhao X. et al.Nuclear receptors rock around the clock.EMBO Rep. 2014; 15: 518-528Crossref PubMed Scopus (49) Google Scholar], respectively). The discovery of the nuclear hormone receptors (NHRs) in the 1980s represented a breakthrough in the understanding of the transcriptional control of metabolic networks. NHRs represent an extended family of ligand-responsive DNA-binding proteins that, upon activation, can switch transcriptional programs in cooperation with coactivators or corepressors [3Privalsky M.L. The role of corepressors in transcriptional regulation by nuclear hormone receptors.Annu. Rev. Physiol. 2004; 66: 315-360Crossref PubMed Scopus (258) Google Scholar]. NHRs are transcriptional master regulators of metabolism by altering the metabolic enzyme profiles in response to feeding and fasting as well as circadian signaling. An illustrative example is the role of NHRs in liver metabolism. Secretion of cortisol from the adrenal gland during prolonged starvation induces the activation of the glucocorticoid receptor in the liver. This leads to the transcription of two master regulators of sugar metabolism, glucose-6-phosphatase (G6PC) and phosphoenolpyruvate carboxykinase (PECK), which promote the synthesis of glucose via gluconeogenesis [1Hong S.H. et al.Nuclear receptors and metabolism: from feast to famine.Diabetologia. 2014; 57: 860-867Crossref PubMed Scopus (26) Google Scholar, 4Liu Y. et al.Reduction of hepatic glucocorticoid receptor and hexose-6-phosphate dehydrogenase expression ameliorates diet-induced obesity and insulin resistance in mice.J. Mol. Endocrinol. 2008; 41: 53-64Crossref PubMed Scopus (47) Google Scholar]. By contrast, liver X receptors (LXRs) and farnesoid X receptor (FXR) are activated by feeding-induced synthesis of their respective ligands, oxysterols and bile acid. In antagonism to fasting-activated NHRs, both LXRs and FXR suppress gluconeogenesis by upregulating the expression of glucokinase, which promotes glucose utilization, and by increasing glycogen synthesis [5Laffitte B.A. et al.Activation of liver X receptor improves glucose tolerance through coordinate regulation of glucose metabolism in liver and adipose tissue.Proc. Natl. Acad. Sci. U.S.A. 2003; 100: 5419-5424Crossref PubMed Scopus (419) Google Scholar, 6Renga B. et al.Glucocorticoid receptor mediates the gluconeogenic activity of the farnesoid X receptor in the fasting condition.FASEB J. 2012; 26: 3021-3031Crossref PubMed Scopus (43) Google Scholar, 7Zhang Y. et al.Activation of the nuclear receptor FXR improves hyperglycemia and hyperlipidemia in diabetic mice.Proc. Natl. Acad. Sci. U.S.A. 2006; 103: 1006-1011Crossref PubMed Scopus (716) Google Scholar]. LXR activation also leads to an enhancement of triacylglycerol synthesis by upregulating the genes involved in lipogenesis [8Grefhorst A. et al.Stimulation of lipogenesis by pharmacological activation of the liver X receptor leads to production of large, triglyceride-rich very low density lipoprotein particles.J. Biol. Chem. 2002; 277: 34182-34190Crossref PubMed Scopus (404) Google Scholar]. Thus, the study of transcription factors such as NHRs and numerous others has contributed much to our understanding of the genetic control of metabolism [1Hong S.H. et al.Nuclear receptors and metabolism: from feast to famine.Diabetologia. 2014; 57: 860-867Crossref PubMed Scopus (26) Google Scholar, 2Zhao X. et al.Nuclear receptors rock around the clock.EMBO Rep. 2014; 15: 518-528Crossref PubMed Scopus (49) Google Scholar, 3Privalsky M.L. The role of corepressors in transcriptional regulation by nuclear hormone receptors.Annu. Rev. Physiol. 2004; 66: 315-360Crossref PubMed Scopus (258) Google Scholar, 9Mangelsdorf D.J. et al.The nuclear receptor superfamily: the second decade.Cell. 1995; 83: 835-839Abstract Full Text PDF PubMed Scopus (6064) Google Scholar, 10Yang X. et al.Nuclear receptor expression links the circadian clock to metabolism.Cell. 2006; 126: 801-810Abstract Full Text Full Text PDF PubMed Scopus (761) Google Scholar]. Importantly, transcriptomes only partially correlate with their corresponding proteomes, implying that RNA-based post-transcriptional regulation should play an important role in sculpting cellular proteomes [11Schwanhausser B. et al.Global quantification of mammalian gene expression control.Nature. 2011; 473: 337-342Crossref PubMed Scopus (4059) Google Scholar]. Interestingly, a few metabolic enzymes had been noted to bind RNA themselves and, in some instances, participate in the post-transcriptional control of specific mRNAs [12Ciesla J. Metabolic enzymes that bind RNA: yet another level of cellular regulatory network?.Acta Biochim. Pol. 2006; 53: 11-32Crossref PubMed Scopus (86) Google Scholar]. For example, thymidine synthase (TYMS) can bind and inhibit the translation of its own RNA when the levels of its substrates are low, establishing a negative feedback loop [13Chu E. et al.Autoregulation of human thymidylate synthase messenger RNA translation by thymidylate synthase.Proc. Natl. Acad. Sci. U.S.A. 1991; 88: 8977-8981Crossref PubMed Scopus (331) Google Scholar, 14Chu E. et al.Regulation of thymidylate synthase in human colon cancer cells treated with 5-fluorouracil and interferon-gamma.Mol. Pharmacol. 1993; 43: 527-533PubMed Google Scholar, 15Chu E. et al.Identification of a thymidylate synthase ribonucleoprotein complex in human colon cancer cells.Mol. Cell. Biol. 1994; 14: 207-213Crossref PubMed Scopus (84) Google Scholar]. Conceptually, such a mechanism represents a simple yet effective way to adjust to conditions when the enzyme is not required. In this review, we discuss the emerging roles of protein–RNA interactions in controlling metabolism. Over the past three decades, sporadic reports have shown that metabolic enzymes can moonlight as RNA-binding proteins (RBPs) and, in some instances, regulate the expression of their target mRNAs [12Ciesla J. Metabolic enzymes that bind RNA: yet another level of cellular regulatory network?.Acta Biochim. Pol. 2006; 53: 11-32Crossref PubMed Scopus (86) Google Scholar, 16Hentze M.W. Enzymes as RNA-binding proteins: a role for (di)nucleotide-binding domains?.Trends Biochem. Sci. 1994; 19: 101-103Abstract Full Text PDF PubMed Scopus (123) Google Scholar, 17Hentze M.W. Preiss T. The REM phase of gene regulation.Trends Biochem. Sci. 2010; 35: 423-426Abstract Full Text Full Text PDF PubMed Scopus (82) Google Scholar] (Table 1). These moonlighting enzymes (see Glossary) participate in varied metabolic such as the metabolism, and and In RNA in or [12Ciesla J. Metabolic enzymes that bind RNA: yet another level of cellular regulatory network?.Acta Biochim. Pol. 2006; 53: 11-32Crossref PubMed Scopus (86) Google Scholar, 15Chu E. et al.Identification of a thymidylate synthase ribonucleoprotein complex in human colon cancer cells.Mol. Cell. Biol. 1994; 14: 207-213Crossref PubMed Scopus (84) Google Scholar, E. et al.Identification of an RNA for human thymidylate synthase.Proc. Natl. Acad. Sci. U.S.A. 1993; PubMed Scopus Google Scholar, E. et al.Identification of the of glyceraldehyde-3-phosphate dehydrogenase as a novel RNA-binding PubMed Scopus Google Scholar, E. dehydrogenase RNA in the Biol. Chem. 1995; PubMed Scopus Google Scholar]. While of the moonlighting metabolic enzymes in living cells and the and of RNA of also known as regulatory and have been by and et of function regulatory with 2006; PubMed Scopus Google Scholar], and in cellular and as Y. et thymidylate synthase and its mRNA in 2010; PubMed Scopus Google Scholar, B. et regulatory proteins are for function and control in the 2008; Full Text Full Text PDF PubMed Scopus Google Scholar, B. et in the regulatory in the 2006; PubMed Scopus Google Scholar, et control of cell function by Full Text Full Text PDF PubMed Scopus Google Scholar]. from the of the which the of regulatory links gene expression and intermediary metabolism by moonlighting RNA-binding metabolic enzymes M.W. Preiss T. The REM phase of gene regulation.Trends Biochem. Sci. 2010; 35: 423-426Abstract Full Text Full Text PDF PubMed Scopus (82) Google of Metabolic Enzymes as in the RNA RNA RNA RNA and of and and dehydrogenase and activity for several of enzyme of dehydrogenase at of and of dehydrogenase of dehydrogenase pathways and of metabolism, and and in a new have been to a of two used to to RNA in These T. et for RNA-binding proteins in for many 2010; PubMed Scopus Google Scholar] and proteins et unexpected RNA-binding proteins in 2010; PubMed Scopus Google Scholar], as including many not previously known to with the dozen metabolic enzymes with RNA in and proteins involved in metabolism were the of moonlighting metabolic enzymes. The dehydrogenase in both as an by RNA-binding a limited of target T. et for RNA-binding proteins in for many 2010; PubMed Scopus Google Scholar]. the is not an with RNA for in cellular the of in identification two in a new RNA 1). to cell by of protein–RNA complexes and quantitative a of in and cells et al.The and its on Cell. 2012; Full Text Full Text PDF PubMed Scopus Google Scholar, A. et RNA biology from an of mammalian 2012; Full Text Full Text PDF PubMed Scopus Google Scholar]. of were novel RNA and known RNA-binding This several promotes at the that can only with at not promote is to living with protein–RNA is with and including of and to as quantitative information and are A. et RNA biology from an of mammalian 2012; Full Text Full Text PDF PubMed Scopus Google Scholar, A. et identification of RNA-binding proteins by PubMed Scopus Google Scholar]. the the RNA metabolic enzymes with et al.The and its on Cell. 2012; Full Text Full Text PDF PubMed Scopus Google Scholar, A. et RNA biology from an of mammalian 2012; Full Text Full Text PDF PubMed Scopus Google Scholar, et al.The RNA-binding of stem Mol. Biol. PubMed Scopus Google Scholar] (Table that the RNA and metabolism is previously and the REM and enzyme had previously been to bind RNA in [12Ciesla J. Metabolic enzymes that bind RNA: yet another level of cellular regulatory network?.Acta Biochim. Pol. 2006; 53: 11-32Crossref PubMed Scopus (86) Google Scholar] and the of and with RNA in cells by an A. et RNA biology from an of mammalian 2012; Full Text Full Text PDF PubMed Scopus Google Scholar, A. et identification of RNA-binding proteins by PubMed Scopus Google Scholar]. and RNA shown that and with of mRNAs in from of A. et RNA biology from an of mammalian 2012; Full Text Full Text PDF PubMed Scopus Google Scholar]. In has been with the as a of the which that the of this enzyme with RNA is in RNA in and and of PubMed Scopus Google Scholar]. the moonlighting enzymes by the RNA to metabolic pathways and of bind or (Table 1). This that involved in such as the represent to with as in Interestingly, some of the known and moonlighting are to in dehydrogenase a RNA-binding and enzyme et dehydrogenase in and in J. 2004; PubMed Scopus Google Scholar], 2008; PubMed Scopus Google Scholar], an with to the of the in the et of in 2010; PubMed Scopus Google Scholar]. Importantly, the metabolic activity is to bind in dehydrogenase J. PubMed Scopus Google Scholar]. is involved in the post-transcriptional regulation of mRNA and this its with and its translation a mechanism for Biol. 2012; PubMed Scopus Google Scholar]. is also by in of the such as nuclear ribonucleoprotein and a role of RNA biology in this A. et proteins in Full Text Full Text PDF PubMed Scopus Google Scholar]. The enzyme dehydrogenase also known as the of in However, as an in cells et al.The and its on Cell. 2012; Full Text Full Text PDF PubMed Scopus Google Scholar] and also as a of which is involved in the of the J. et RNA: identification and of the human 2008; Full Text Full Text PDF PubMed Scopus Google Scholar]. in and has been with is the of activity of the enzymes and the of the et function of dehydrogenase is for and cell Mol. 2010; PubMed Scopus Google Scholar], that the mechanism this not from the activity of a recent study that or of induces a in the of the of the RNA et or of dehydrogenase of and of Mol. 2014; PubMed Scopus Google Scholar]. In of the function of moonlighting metabolic enzymes is with the of protein–RNA interactions in cell biology. In the that the for its role in the regulation of cellular metabolism, regulatory is with A. et of the RNA-binding activity of a regulatory by in enzymatic and genetic Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar, M.W. a regulatory RNA-binding and 1991; 19: PubMed Scopus Google Scholar, et and of from liver and its to the Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar, et an RNA-binding and 1991; Full Text PDF PubMed Scopus Google Scholar]. The role of in the post-transcriptional control of the important role that RNA-binding enzymes play in RNA stem loop were in the of mRNAs M.W. et al.Identification of the for the regulation of human PubMed Scopus Google Scholar] and in the of receptor mRNA et regulatory RNA that control mRNA levels and PubMed Scopus Google Scholar, A in the mediates regulation of receptor mRNA in the 53: Full Text PDF PubMed Scopus Google Scholar] proteins were in to a in the of and Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar, et of a to the of human messenger PubMed Scopus Google Scholar] and regulatory et of the an RNA regulatory the human Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar] and B. et levels of a novel Biol. Chem. 1994; Full Text PDF PubMed Google Scholar, et of a second regulatory function, and post-translational Biol. Chem. 1994; Full Text PDF PubMed Google Scholar]. have been in proteins involved in and utilization, and the by which regulate have been M.W. et to regulation of metabolism.Cell. 2010; Full Text Full Text PDF PubMed Scopus Google Scholar]. bind to in and with an in the mRNA to in the leads to mRNA in this the are crucial to levels proteins are broadly expressed and are of both is the also specific roles for in and the is of in and the (reviewed in M.W. et to regulation of metabolism.Cell. 2010; Full Text Full Text PDF PubMed Scopus Google Scholar, et metabolism and its control by regulatory 2012; PubMed Scopus Google Scholar, The in from Pharmacol. 2014; PubMed Scopus Google Scholar, et al.The of regulatory proteins in an Pharmacol. 2014; PubMed Scopus Google the of the of the of mRNA that et in the that only J. PubMed Scopus Google Scholar]. and are and both are to the enzyme that the of to a as a However, only of the an and as a RNA-binding and activity are In conditions the and as an the is when is and the to its et of function regulatory with 2006; PubMed Scopus Google Scholar] In a of the is in the et of regulatory proteins and regulatory J. 2004; PubMed Scopus Google Scholar], a for activation of RNA-binding activity in A second example of a with metabolic and RNA-binding activity is the enzyme which glyceraldehyde-3-phosphate to In to this in and cell have been as in et al.The of from 2011; PubMed Scopus Google Scholar]. is also a of the of translation complex that mRNA translation in cells et al.The a of gene Biochem. Sci. Full Text Full Text PDF PubMed Scopus Google Scholar]. The complex the synthase also known as or and GAPDH. While is a and to their in the the and to the complex upon of and by et al.The a of gene Biochem. Sci. Full Text Full Text PDF PubMed Scopus Google Scholar]. is the RNA-binding the is also to the with target has also been as an in its own with from a and RNA E. dehydrogenase RNA in the Biol. Chem. 1995; PubMed Scopus Google Scholar, of glyceraldehyde-3-phosphate dehydrogenase with and RNA of the A and 2003; PubMed Scopus Google Scholar, dehydrogenase is of the three RNA-binding proteins of PubMed Scopus Google Scholar, of RNA by glyceraldehyde-3-phosphate 1993; PubMed Scopus Google reports have on to in the of numerous mRNAs E. dehydrogenase RNA in the Biol. Chem. 1995; PubMed Scopus Google Scholar, of glyceraldehyde-3-phosphate dehydrogenase with and RNA of the A and 2003; PubMed Scopus Google Scholar, et dehydrogenase expression by a mechanism mRNA Cell. Biol. 2008; PubMed Scopus Google Scholar, Y. et al.The glyceraldehyde-3-phosphate dehydrogenase is both and messenger RNA in 2008; PubMed Scopus Google Scholar, et dehydrogenase to the of messenger RNA in human cancer possible role in regulation and PubMed Scopus (84) Google Scholar]. of RNA with and that the mediates to RNA E. dehydrogenase RNA in the Biol. Chem. 1995; PubMed Scopus Google Scholar]. An gene regulation and metabolism from the study of cell activation et control of cell function by Full Text Full Text PDF PubMed Scopus Google Scholar] are switch from to In cells on translation of is by of to an in the of the mRNA This is a of as by or of the enzymatic function of by cells with cell activation and the switch to is as an to mRNA and in the Thus, the switch to emerges as a mechanism to the of production by the enzyme in RNA the enzyme and RNA for to the on could potentially be involved in the as has been that the of or with RNA to in E. dehydrogenase RNA in the Biol. Chem. 1995; PubMed Scopus Google Scholar, dehydrogenase is of the three RNA-binding proteins of PubMed Scopus Google Scholar, of RNA by glyceraldehyde-3-phosphate 1993; PubMed Scopus Google Scholar, et al.Identification of the mammalian DNA-binding as glyceraldehyde-3-phosphate J. Biochem. PubMed Scopus Google Scholar, et of glyceraldehyde-3-phosphate dehydrogenase with and of J. Biochem. PubMed Scopus Google Scholar]. By contrast, the glyceraldehyde-3-phosphate has not shown of RNA with the RNA not by the through the activity is by the of the in a The RNA also the assembly of the that the enzyme RNA as a or E. et al.Identification of the of glyceraldehyde-3-phosphate dehydrogenase as a novel RNA-binding PubMed Scopus Google Scholar]. While or with RNA could be involved in its enzymatic and RNA regulatory is also known to be in with links to changes in its and as in et al.The of from 2011; PubMed Scopus Google Scholar]. by at the can to the and activation of its cell as can in PubMed Scopus Google Scholar, X. et of activity by three pathways of in 2003; PubMed Scopus Google Scholar]. leads to of of the the enzyme to participate in metabolic from to the et of the is to Biol. PubMed Scopus Google Scholar, et of glyceraldehyde-3-phosphate dehydrogenase by the in Biol. Chem. 1994; Full Text PDF PubMed Google Scholar]. a has been to be for RNA et of glyceraldehyde-3-phosphate dehydrogenase to the of in 2011; PubMed Scopus Google Scholar], and to the RNA-binding activity of et dehydrogenase expression by a mechanism mRNA Cell. Biol. 2008; PubMed Scopus Google Scholar]. Thus, in cell or metabolism could also the function of via post-translational modifications of the a several of RNA–enzyme can be RNA with the and/or and is in with or the of the RNA to the enzyme is this of is to by the The RNA to a from the an could have on or allosteric or on the metabolic function of the A of the is that RNA interactions of the enzyme with another cellular for example, a or Enzymes function as or the with RNA can complex or with when with an of the enzyme can also enzymes a are by interactions to a with metabolic of enzymes in Biol. Chem. Full Text PDF PubMed Google Scholar, et of the Biol. Chem. Full Text PDF PubMed Google Scholar, J. and Rev. PubMed Google Scholar]. RNA could enzymes of a to of a Interestingly, to a complex with which and shown to be to et on of and enzymes in role of Cell. Physiol. PubMed Scopus Google Scholar]. The for the et of the Biol. Chem. Full Text PDF PubMed Google Scholar] and by recent of by and Chem. PubMed Scopus Google Scholar]. has been for pathways such as the enzymes which in the et of complexes in living 2008; PubMed Scopus Google Scholar]. is much in for in and a for production in on an RNA scaffold et of with RNA 2011; PubMed Scopus Google Scholar]. be a in by such as aconitase/IRP1 and might suggest that an enzyme to RNA control the expression of the RNA mRNAs or controlling mRNA is important to that RNA also the enzyme its complex metabolism and this and RNA could interactions with the enzyme through to the or through allosteric Enzymes are by their own substrates and a enzyme–RNA might also be by of Interestingly, even have been to be to function as for example, which is by et of a stem cell RNA-binding by an intermediary 2014; Scopus Google Scholar]. cellular levels might post-translational modifications post-translational modifications For example, many metabolic enzymes are and is to the cellular levels of and Y. The and the regulation of Sci. 2012; Full Text Full Text PDF PubMed Scopus Google Scholar]. to and and and Thus, metabolism could RNA to enzymes through changes in their this could the regulatory of a much the enzyme that By contrast, RNA can as an of the activity of an The is activated by of RNA and its role in and 2012; PubMed Scopus Google Scholar]. in a is the with RNA its a is and can the the of cell synthesis to and in cancer, and Mol. Biol. Google Scholar, et al.The their and Mol. Sci. PubMed Scopus Google Scholar, A. E. of and receptors in human J. Google Scholar]. of proteins or receptor and A. of PubMed Scopus Google Scholar, J. RNA in and Full Text Full Text PDF PubMed Scopus Google Scholar]. While are from the and the regulatory are is that cell could to the of RNA-binding enzymes and These for of the moonlighting as even their RNA are not yet the that not of the for their has been known for a of a to as an that cellular metabolism, is only now that many metabolic enzymes RNA-binding activity in living cells. We can currently only the of this we to the of this to and how metabolism and gene regulation might be at this level (see we that the identification of the and the of their on enzymatic function in cellular be also be important to how changes in metabolism regulate the interactions enzymes and and the consequences of this regulation RNA-binding enzymes could a new in gene regulation and is the function of the RNA-binding activity of many metabolic in the regulation of target RNA of their function as metabolic bind to of by available should on important enzymes bind are their RNA-binding and with that are crucial for or complex enzyme–RNA interactions metabolic or and how is this is the function of the RNA-binding activity of many metabolic in the regulation of target RNA of their function as metabolic bind to of by available should on important enzymes bind are their RNA-binding and with that are crucial for or complex enzyme–RNA interactions metabolic or and how is this This by a to and by a from the and of to and also by the and the of the for and We for and an assembly of several enzymes a with metabolic enzymes that a function their activity in we on RNA-binding enzymes. a that interactions and regulatory cellular metabolism and gene regulation M.W. Preiss T. The REM phase of gene regulation.Trends Biochem. Sci. 2010; 35: 423-426Abstract Full Text Full Text PDF PubMed Scopus (82) Google Scholar]. an to and a of proteins that with in living cells.

assay. We pushed this comparative alignment of IRF-3 and NLRP12 homologs and show that the lack or presence of cognate cleavage motifs in IRF-3 and NLRP12 could contribute to the presentation of disease in cats and tigers, for example. Our findings provide an explanatory framework for indepth studies into the pathophysiology of COVID-19.

-dependent cascades in astrocytes. We have therefore uncovered a mechanism by which a memory trace at one synapse could alter signal handling by multiple neighboring connections.

The joints of mammals are lined with cartilage, comprised of individual chondrocytes embedded in a specialized extracellular matrix. Chondrocytes experience a complex mechanical environment and respond to changing mechanical loads in order to maintain cartilage homeostasis. It has been proposed that mechanically gated ion channels are of functional importance in chondrocyte mechanotransduction; however, direct evidence of mechanical current activation in these cells has been lacking. We have used high-speed pressure clamp and elastomeric pillar arrays to apply distinct mechanical stimuli to primary murine chondrocytes, stretch of the membrane and deflection of cell-substrate contacts points, respectively. Both TRPV4 and PIEZO1 channels contribute to currents activated by stimuli applied at cell-substrate contacts but only PIEZO1 mediates stretch-activated currents. These data demonstrate that there are separate, but overlapping, mechanoelectrical transduction pathways in chondrocytes.

The transcriptional co-activators YAP (or YAP1) and TAZ (or WWTR1) are frequently activated during the growth and progression of many solid tumors, including lung, colorectal, breast, pancreatic, and liver carcinomas as well as melanoma and glioma. YAP/TAZ bind to TEAD-family co-activators to drive cancer cell survival, proliferation, invasive migration, and metastasis. YAP/TAZ activation may also confer resistance to chemotherapy, radiotherapy, or immunotherapy. YAP-TEAD cooperates with the RAS-induced AP-1 (FOS/JUN) transcription factor to drive tumor growth and cooperates with MRTF-SRF to promote activation of cancer-associated fibroblasts, matrix stiffening, and metastasis. The key upstream repressor of YAP/TAZ activation is the Hippo (MST1/2-LATS1/2) pathway and the key upstream activators are mechanically induced Integrin-SRC and E-cadherin-AJUBA/TRIP6/LIMD1, growth factor induced PI3K-AKT, and inflammation-induced G-protein coupled receptor (GPCR) signals, all of which antagonize the Hippo pathway. In this review, strategies to target YAP/TAZ activity in cancer are discussed along with the prospects for synergy with established pillars of cancer therapy.

The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release.

Antigen recognition by the T-cell receptor (TCR) is a hallmark of the adaptive immune system. When the TCR engages a peptide bound to the restricting major histocompatibility complex molecule (pMHC), it transmits a signal via the associated CD3 complex. How the extracellular antigen recognition event leads to intracellular phosphorylation remains unclear. Here, we used single-molecule localization microscopy to quantify the organization of TCR-CD3 complexes into nanoscale clusters and to distinguish between triggered and nontriggered TCR-CD3 complexes. We found that only TCR-CD3 complexes in dense clusters were phosphorylated and associated with downstream signaling proteins, demonstrating that the molecular density within clusters dictates signal initiation. Moreover, both pMHC dose and TCR-pMHC affinity determined the density of TCR-CD3 clusters, which scaled with overall phosphorylation levels. Thus, TCR-CD3 clustering translates antigen recognition by the TCR into signal initiation by the CD3 complex, and the formation of dense signaling-competent clusters is a process of antigen discrimination.

Covering: 2000 up to 2018 The cytochromes P450 (P450s) are a superfamily of heme-containing monooxygenases that perform diverse catalytic roles in many species, including bacteria. The P450 superfamily is widely known for the hydroxylation of unactivated C-H bonds, but the diversity of reactions that P450s can perform vastly exceeds this undoubtedly impressive chemical transformation. Within bacteria, P450s play important roles in many biosynthetic and biodegradative processes that span a wide range of secondary metabolite pathways and present diverse chemical transformations. In this review, we aim to provide an overview of the range of chemical transformations that P450 enzymes can catalyse within bacterial secondary metabolism, with the intention to provide an important resource to aid in understanding of the potential roles of P450 enzymes within newly identified bacterial biosynthetic pathways.

BACKGROUND: Metagenomics has become a prominent approach for exploring the role of the gut microbiota in human health. However, the temporal variability of the healthy gut microbiome has not yet been studied in depth using metagenomics and little is known about the effects of different sampling and preservation approaches. We performed metagenomic analysis on fecal samples from seven subjects collected over a period of up to two years to investigate temporal variability and assess preservation-induced variation, specifically, fresh frozen compared to RNALater. We also monitored short-term disturbances caused by antibiotic treatment and bowel cleansing in one subject. RESULTS: We find that the human gut microbiome is temporally stable and highly personalized at both taxonomic and functional levels. Over multiple time points, samples from the same subject clustered together, even in the context of a large dataset of 888 European and American fecal metagenomes. One exception was observed in an antibiotic intervention case where, more than one year after the treatment, samples did not resemble the pre-treatment state. Clustering was not affected by the preservation method. No species differed significantly in abundance, and only 0.36% of gene families were differentially abundant between preservation methods. CONCLUSIONS: Technical variability is small compared to the temporal variability of an unperturbed gut microbiome, which in turn is much smaller than the observed between-subject variability. Thus, short-term preservation of fecal samples in RNALater is an appropriate and cost-effective alternative to freezing of fecal samples for metagenomic studies.

An average shotgun proteomics experiment detects approximately 10,000 human proteins from a single sample. However, individual proteins are typically identified by peptide sequences representing a small fraction of their total amino acids. Hence, an average shotgun experiment fails to distinguish different protein variants and isoforms. Deeper proteome sequencing is therefore required for the global discovery of protein isoforms. Using six different human cell lines, six proteases, deep fractionation and three tandem mass spectrometry fragmentation methods, we identify a million unique peptides from 17,717 protein groups, with a median sequence coverage of approximately 80%. Direct comparison with RNA expression data provides evidence for the translation of most nonsynonymous variants. We have also hypothesized that undetected variants likely arise from mutation-induced protein instability. We further observe comparable detection rates for exon-exon junction peptides representing constitutive and alternative splicing events. Our dataset represents a resource for proteoform discovery and provides direct evidence that most frame-preserving alternatively spliced isoforms are translated.

Tumors have aberrant proteomes that often do not match their corresponding transcriptome profiles. One possible cause of this discrepancy is the existence of aberrant RNA modification landscapes in the so-called epitranscriptome. Here, we report that human glioma cells undergo DNA methylation-associated epigenetic silencing of NSUN5, a candidate RNA methyltransferase for 5-methylcytosine. In this setting, NSUN5 exhibits tumor-suppressor characteristics in vivo glioma models. We also found that NSUN5 loss generates an unmethylated status at the C3782 position of 28S rRNA that drives an overall depletion of protein synthesis, and leads to the emergence of an adaptive translational program for survival under conditions of cellular stress. Interestingly, NSUN5 epigenetic inactivation also renders these gliomas sensitive to bioactivatable substrates of the stress-related enzyme NQO1. Most importantly, NSUN5 epigenetic inactivation is a hallmark of glioma patients with long-term survival for this otherwise devastating disease.

The HIV capsid is semipermeable and covered in electropositive pores that are essential for viral DNA synthesis and infection. Here, we show that these pores bind the abundant cellular polyanion IP6, transforming viral stability from minutes to hours and allowing newly synthesised DNA to accumulate inside the capsid. An arginine ring within the pore coordinates IP6, which strengthens capsid hexamers by almost 10°C. Single molecule measurements demonstrate that this renders native HIV capsids highly stable and protected from spontaneous collapse. Moreover, encapsidated reverse transcription assays reveal that, once stabilised by IP6, the accumulation of new viral DNA inside the capsid increases >100 fold. Remarkably, isotopic labelling of inositol in virus-producing cells reveals that HIV selectively packages over 300 IP6 molecules per infectious virion. We propose that HIV recruits IP6 to regulate capsid stability and uncoating, analogous to picornavirus pocket factors. HIV-1/IP6/capsid/co-factor/reverse transcription.

Abstract Background 5-Methylcytosine (m 5 C) is a prevalent base modification in tRNA and rRNA but it also occurs more broadly in the transcriptome, including in mRNA, where it serves incompletely understood molecular functions. In pursuit of potential links of m 5 C with mRNA translation, we performed polysome profiling of human HeLa cell lysates and subjected RNA from resultant fractions to efficient bisulfite conversion followed by RNA sequencing (bsRNA-seq). Bioinformatic filters for rigorous site calling were devised to reduce technical noise. Results We obtained ~ 1000 candidate m 5 C sites in the wider transcriptome, most of which were found in mRNA. Multiple novel sites were validated by amplicon-specific bsRNA-seq in independent samples of either human HeLa, LNCaP and PrEC cells. Furthermore, RNAi-mediated depletion of either the NSUN2 or TRDMT1 m 5 C:RNA methyltransferases showed a clear dependence on NSUN2 for the majority of tested sites in both mRNAs and noncoding RNAs. Candidate m 5 C sites in mRNAs are enriched in 5′UTRs and near start codons and are embedded in a local context reminiscent of the NSUN2-dependent m 5 C sites found in the variable loop of tRNA. Analysing mRNA sites across the polysome profile revealed that modification levels, at bulk and for many individual sites, were inversely correlated with ribosome association. Conclusions Our findings emphasise the major role of NSUN2 in placing the m 5 C mark transcriptome-wide. We further present evidence that substantiates a functional interdependence of cytosine methylation level with mRNA translation. Additionally, we identify several compelling candidate sites for future mechanistic analysis.

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a consensus approach, METEORE ( https://github.com/comprna/METEORE ), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.

Nanopore sensors detect individual species passing through a nanoscale pore. This experimental paradigm suffers from long analysis times at low analyte concentration and non-specific signals in complex media. These limit effectiveness of nanopore sensors for quantitative analysis. Here, we address these challenges using antibody-modified magnetic nanoparticles ((anti-PSA)-MNPs) that diffuse at zero magnetic field to capture the analyte, prostate-specific antigen (PSA). The (anti-PSA)-MNPs are magnetically driven to block an array of nanopores rather than translocate through the nanopore. Specificity is obtained by modifying nanopores with anti-PSA antibodies such that PSA molecules captured by (anti-PSA)-MNPs form an immunosandwich in the nanopore. Reversing the magnetic field removes (anti-PSA)-MNPs that have not captured PSA, limiting non-specific effects. The combined features allow detecting PSA in whole blood with a 0.8 fM detection limit. Our 'magnetic nanoparticle, nanopore blockade' concept points towards a strategy to improving nanopore biosensors for quantitative analysis of various protein and nucleic acid species.

For the fabrication of perovskite solar cells (PSCs) using a solution process, it is essential to understand the characteristics of the perovskite precursor solution to achieve high performance and reproducibility. The colloids (iodoplumbates) in the perovskite precursors under various conditions were investigated by UV-visible absorption, dynamic light scattering, photoluminescence, and total internal reflection fluorescence microscopy techniques. Their local structure was examined by in situ X-ray absorption fine structure studies. Perovskite thin films on a substrate with precursor solutions were characterized by transmission electron microscopy, X-ray diffraction analysis, space-charge-limited current, and Kelvin probe force microscopy. The colloidal properties of the perovskite precursor solutions were found to be directly correlated with the defect concentration and crystallinity of the perovskite film. This work provides guidelines for controlling perovskite films by varying the precursor solution, making it possible to use colloid-engineered lead halide perovskite layers to fabricate efficient PSCs.

While membrane models now include the heterogeneous distribution of lipids, the impact of membrane charges on regulating the association of proteins with the plasma membrane is often overlooked. Charged lipids are asymmetrically distributed between the two leaflets of the plasma membrane, resulting in the inner leaflet being negatively charged and a surface potential that attracts and binds positively charged ions, proteins, and peptide motifs. These interactions not only create a transmembrane potential but they can also facilitate the formation of charged membrane domains. Here, we reference fields outside of immunology in which consequences of membrane charge are better characterized to highlight important mechanisms. We then focus on T cell receptor (TCR) signaling, reviewing the evidence that membrane charges and membrane-associated calcium regulate phosphorylation of the TCR-CD3 complex and discuss how the immunological synapse exhibits distinct patterns of membrane charge distribution. We propose that charged lipids, ions in solution, and transient protein interactions form a dynamic equilibrium during T cell activation.