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Is there a cellular mechanism that detects Ribosomal damage?

Is there a cellular mechanism that detects Ribosomal damage?



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What kinds of options, if any, do cells (Eukary and Prokary) have for detecting, and repairing damage in Ribosomes (of all types)? I am curious as to what happens when a cell sustains damage of some form, such as radiation, and the Ribosomes are damaged.


7.4: Repair Mechanisms

  • Contributed by Ross Hardison
  • T. Ming Chu Professor (Biochemistry and Molecular Biology) at The Pennsylvania State University

The second part of this chapter examines the major classes of DNA repair processes. These are:

  • reversal of damage,
  • nucleotide excision repair,
  • base excision repair,
  • mismatch repair,
  • recombinational repair, and
  • error-prone repair.

Many of these processes were first studies in bacteria such as E. coli, however only a few are limited to this species. For instance, nucleotide excision repair and base excision repair are found in virtually all organisms, and they have been well characterized in bacteria, yeast, and mammals. Like DNA replication itself, repair of damage and misincorporation is a very old process.

Reversal of damage

Some kinds of covalent alteration to bases in DNA can be directly reversed. This occurs by specific enzyme systems recognizing the altered base and breaking bonds to remove the adduct or change the base back to its normal structure.

Photoreactivation is a light-dependent process used by bacteria to reverse pyrimidine dimers formed by UV radiation. The enzyme photolyase binds to a pyrimidine dimer and catalyzes a second photochemical reaction (this time using visible light) that breaks the cyclobutane ring and reforms the two adjacent thymidylates in DNA. Note that this is not formally the reverse of the reaction that formed the pyrimidine dimers, since energy from visible light is used to break the bonds between the pyrimidines, and no UV radiation is released. However, the result is that the DNA structure has been returned to its state prior to damage by UV. The photolyase enzyme has two subunits, which are encoded by the phrA and phrBgenes in E. coli.

A second example of the reversal of damage is the removal of methyl groups. For instance, the enzyme O6‑methylguanine methyltransferase, encoded by the adagene in E. coli, recognizes O6‑methylguanine in duplex DNA. It then removes the methyl group, transferring it to an amino acid of the enzyme. The methylated enzyme is no longer active, hence this has been referred to as a suicide mechanism for the enzyme.

Excision Repair

The most common means of repairing damage or a mismatch is to cut it out of the duplex DNA and recopy the remaining complementary strand of DNA, as outlined in Figure 7.12. Three different types of excision repair have been characterized: nucleotide excision repair, base excision repair, and mismatch repair. All utilize a cut, copy, and paste mechanism. In the cuttingstage, an enzyme or complex removes a damaged base or a string of nucleotides from the DNA. For the copying, a DNA polymerase (DNA polymerase I in E. coli) will copy the template to replace the excised, damaged strand. The DNA polymerase can initiate synthesis from 3' OH at the single-strand break (nick) or gap in the DNA remaining at the site of damage after excision. Finally, in the pastingstage, DNA ligase seals the remaining nick to give an intact, repaired DNA.

Figure 7.12. A general scheme for excision repair, illustrating the cut (steps 1 and 2), copy (step 3) and paste (step 4) mechanism.

Nucleotide Excision Repair (NER)

In nucleotide excision repair, damaged bases are cut out within a string of nucleotides, and replaced with DNA as directed by the undamaged template strand. This repair system is used to remove pyrimidine dimers formed by UV radiation as well as nucleotides modified by bulky chemical adducts. The common feature of damage that is repaired by nucleotide excision is that the modified nucleotides cause a significant distortion in the DNA helix. NER occurs in almost all organisms examined.

Some of the best-characterized enzymes catalyzing this process are the UvrABC excinuclease and the UvrD helicase in E. coli. The genes encoding this repair function were discovered as mutants that are highly sensitive to UV damage, indicating that the mutants are defective in UV repair. As illustrated in Figure 7.13, wild type E. coli cells are killed only at higher doses of UV radiation. Mutant strains can be identified that are substantially more sensitive to UV radiation these are defective in the functions needed for UV-resistance, abbreviated uvr. By collecting large numbers of such mutants and testing them for their ability to restore resistance to UV radiation in combination, complementation groups were identified. Four of the complementation groups, or genes, encode proteins that play major rules in NER they are uvrA, uvrB, uvrCand uvrD.

Figure 7.13. Survival curve of bacteria exposed to UV radiation. Cultures of bacteria are exposed to increasing doses of UV radiation, plotted along the horizontal axis. Samples of each irradiated culture are then plated and the number of surviving colonies are counted (plotted as a logarithmic function on the vertical axis). Mutant strains that are more sensitive to UV damage are defective in the genes that confer UV-resistance, i.e. they are defective in uvr functions.

The enzymes encoded by the uvrgenes have been studied in detail. The polypeptide products of the uvrA, uvrB, and uvrCgenes are subunits of a multisubunit enzyme called the UvrABC excinuclease. UvrA is the protein encoded by uvrA, UvrB is encoded by uvrB, and so on. The UvrABC complex recognizes damage-induced structural distortions in the DNA, such as pyrimidine dimers. It then cleaves on both sides of the damage. Then UvrD (also called helicase II), the product of the uvrDgene, unwinds the DNA, releasing the damaged segment. Thus for this system, the UvrABC and UvrD proteins carry out a series of steps in the cutting phase of excision repair. This leaves a gapped substrate for copying by DNA polymerase and pasting by DNA ligase.

The UvrABC proteins form a dynamic complex that recognizes damage and makes endonucleolytic cuts on both sides. The two cuts around the damage allow the single-stranded segment containing the damage to be excised by the helicase activity of UvrD. Thus the UvrABC dynamic complex and the UvrBC complex can be called excinucleases. After the damaged segment has been excised, a gap of 12 to 13 nucleotides remains in the DNA. This can be filled in by DNA polymerase and the remaining nick sealed by DNA ligase. Since the undamaged template directs the synthesis by DNA polymerase, the resulting duplex DNA is no longer damaged.

In more detail, the process goes as follows (Figure 7.14). UvrA2 (a dimer) and Uvr B recognize the damaged site as a (UvrA)2UvrB complex. UvrA2 then dissociates, in a step that requires ATP hydrolysis. This is an autocatalytic reaction, since it is catalyzed by UvrA, which is itself an ATPase. After UvrA has dissociated, UvrB (at the damaged site) forms a complex with UvrC. The UvrBC complex is the active nuclease. It makes the incisions on each side of the damage, in another step that requires ATP. The phosphodiester backbone is cleaved 8 nucleotides to the 5' side of the damage and 4-5 nucleotides on the 3' side. Finally, the UvrD helicase then unwinds DNA so the damaged segment is removed. The damaged DNA segment dissociates attached to the UvrBC complex. Like all helicase reactions, the unwinding requires ATP hydrolysis to disrupt the base pairs. Thus ATP hydrolysis is required at three steps of this series of reactions.

Figure 7.14.The Uvr(A)BC excinuclease of E. coli recognizes AP sites, thymine dimers, and other structural distortions and makes nicks on both sides of the damaged region. The 12-13 nucleotide-long fragment is released together with the excinuclease by helicase II action.

How does an excinuclease differ from an exonuclease and an endonuclease?

Nucleotide excision repair is very active in mammalian cells, as well as cells from may other organisms. The DNA of a normal skin cell exposed to sunlight would accumulate thousands of dimers per day if this repair process did not remove them! One human genetic disease, called xeroderma pigmentosum (XP), is a skin disease caused by defect in enzymes that remove UV lesions. Fibroblasts isolated from individual XP patients are markedly sensitive to UV radiation when grown in culture, similar to the phenotype shown by E. coliuvrmutants. These XP cell lines can be fused in culture and tested for the ability to restore resistance to UV damage. XP cells lines that do so fall into different complementation groups. Several complementation groups, or genes, have been defined in this way. Considerable progress has been made recently in identifying the proteins encoded by each XP gene (Table 7.2). Note the tight analogy to bacterial functions needed for NER. Similar functions are also found in yeast (Table 7.2). Additional proteins utilized in eukaryotic NER include hHR23B (which forms a complex with the DNA-damage sensor XPC), ERCCI (which forms a complex with the XPF to catalyze incision 5&rsquo to the site of damage), the several other subunits of TFIIH (see Chapter 10) and the single-strand binding protein RPA.

Table 7.2: Genes affected in XP patients, and encoded proteins
Human Gene Protein Function Homologous to S. cerevisiae Analogous to E. coli
XPA Binds damaged DNA Rad14 UvrA/UvrB
XPB 3&rsquo to 5&rsquo helicase, component of TFIIH Rad25 UvrD
XPC DNA-damage sensor (in complex with hHR23B) Rad4
XPD 5&rsquo to 3&rsquo helicase, component of TFIIH Rad3 UvrD
XPE Binds damaged DNA UvrA/UvrB
XPF Works with ERRC1 to cut DNA on 5&rsquo side of damage Rad1 UvrB/UvrC
XPG Cuts DNA on 3&rsquo side of damage Rad2 UvrB/UvrC

NER occurs in two modes in many organisms, including bacteria, yeast and mammals. One is the global repair that acts throughout the genome, and the second is a specialized activity is that is coupled to transcription. Most of the XP gene products listed in Table 2 function in both modes of NER in mammalian cells. However, XPC (acting in a complex with another protein called hHR23B) is a DNA-damage sensor that is specific for global genome NER. In transcription coupled NER, the elongating RNA polymerase stalls at a lesion on the template strand perhaps this is the damage recognition activity for this mode of NER. One of the basal transcription factors that associates with RNA polymerase II, TFIIH (see Chapter 10), also plays a role in both types of NER. A rare genetic disorder in humans, Cockayne syndrome (CS), is associated with a defect specific to transcription coupled repair. Two complementation groups have been identified, CSAand CSB. Determination of the nature and activity of the proteins encoded by them will provide additional insight into the efficient repair of transcribed DNA strands. The phenotype of CS patients is pleiotropic, showing both photosensitivity and severe neurological and other developmental disorders, including premature aging. These symptoms are more severe than those seen for XP patients with no detectable NER, indicating that transcription-coupled repair or the CS proteins have functions in addition to those for NER.

Other genetic diseases also result from a deficiency in a DNA repair function, such as Bloom's syndrome and Fanconi's anemia. These are intensive areas of current research. A good resource for updated information on these and other inherited diseases, as well as human genes in general, is the Online Mendelian Inheritance in Man, or OMIM, accessible at http://www.ncbi.nlm.nih.gov.

Ataxia telangiectasia, or AT, illustrates the effect of alterations in a protein not directly involved in repair, but perhaps signaling that is necessary for proper repair of DNA. AT is a recessive, rare genetic disease marked by uneven gait (ataxia), dilation of blood vessels (telangiectasia) in the eyes and face, cerebellar degeneration, progressive mental retardation, immune deficiencies, premature aging and about a 100-fold increase in susceptibility to cancers. That latter phenotype is driving much of the interest in this locus, since heterozygotes, which comprise about 1% of the population, also have an increased risk of cancer, and may account for as much as 9% of breast cancers in the United States. The gene that is mutated in AT (hence called "ATM") was isolated in 1995 and localized to chromosome 11q22-23.

The ATM gene does not appear to encode a protein that participates directly in DNA repair (unlike the genes that cause XP upon mutation). Rather, AT is caused by a defect in a cellular signaling pathway. Based on homologies to other proteins, the ATM gene product may be involved in the regulation of telomere length and cell cycle progression. The C-terminal domain is homologous to phosphatidylinositol-3-kinase (which is also a Ser/Thr protein kinase) - hence the connection to signaling pathways. The ATM protein also has regions of homology to DNA-dependent protein kinases, which require breaks, nicks or gaps to bind DNA (via subunit Ku) binding to DNA is required for the protein kinase activity. This suggests that ATM protein could be involved in targeting the repair machinery to such damage.

Base Excision Repair

Base excision repair differs from nucleotide excision repair in the types substrates recognized and in the initial cleavage event. Unlike NER, the base excision machinery recognizes damaged bases that do not cause a significant distortion to the DNA helix, such as the products of oxidizing agents. For example, base excision can remove uridines from DNA, even though a G:U base pair does not distort the DNA. Base excision repair is versatile, and this process also can remove some damaged bases that do distort the DNA, such as methylated purines. In general, the initial recognition is a specific damaged base, not a helical distortion in the DNA. A second major difference is that the initial cleavage is directed at the glycosidic bond connecting the purine or pyrimidine base to a deoxyribose in DNA. This contrasts with the initial cleavage of a phosphodiester bond in NER.

Cells contain a large number of specific glycosylases that recognize damaged or inappropriate bases, such as uracil, from the DNA. The glycosylase removes the damaged or inappropriate base by catalyzing cleavage of the N-glycosidic bond that attaches the base to the sugar-phosphate backbone. For instance, uracil-N-glycosylase, the product of the ung gene, recognizes uracil in DNA and cuts the N-glycosidic bond between the base and deoxyribose (Figure 7.15). Other glycosylases recognize and cleave damaged bases. For instance methylpurine glycosylase removes methylated G and A from DNA. The result of the activity of these glycosylases is an apurinic/apyrimidinic site, or AP site (Figure 7.15). At an AP site, the DNA is still an intact duplex, i.e. there are no breaks in the phosphodiester backbone, but one base is gone.

Next, an AP endonuclease nicks the DNA just 5&rsquo to the AP site, thereby providing a primer for DNA polymerase. In E. coli, the 5' to 3' exonuclease function of DNA polymerase I removes the damaged region, and fills in with correct DNA (using the 5' to 3' polymerase, directed by the sequence of the undamaged complementary strand).

Additional mechanisms have evolved for keeping U&rsquos out of DNA. E. colialso has a dUTPase, encoded by the dutgene, which catalyzes the hydrolysis of dUTP to dUMP. The product dUMP is the substrate for thymidylate synthetase, which catalyzes conversion of dUMP to dTMP. This keeps the concentration of dUTP in the cell low, reducing the chance that it will be used in DNA synthesis. Thus the combined action of the products of the dut+ unggenes helps prevent the accumulation of U's in DNA.

In base excision repair, which enzymes are specific for a particular kind of damage and which are used for all repair by this pathway?

Figure 7.15. Base excision repair is initiated by a glycosylase that recognizes and removes chemically damaged or inappropriate bases in DNA. The glycosylase cleaves the glycosidic bond between the base and the sugar, leaving an apurinic/apyrimidinic site. The AP endonuclease can then nick the phosphodiester backbone 5&rsquo to the AP site. When DNA polymerase I binds the free primer end at the nick, its 5'-3' exonuclease activity cuts a few nucleotides ahead of the missing base, and its polymerization activity fills the entire gap of several nucleotides.

Mismatch Repair

The third type of excision repair we will consider is mismatch repair, which is used to repair errors that occur during DNA synthesis. Proofreading during replication is good but not perfect. Even with a functional e subunit, DNA polymerase III allows the wrong nucleotide to be incorporated about once in every 108 bp synthesized in E. coli. However, the measured mutation rate in bacteria is as low as one mistake per 1010 or 1011 bp. The enzymes that catalyze mismatch repairare responsible for this final degree of accuracy. They recognize misincorporated nucleotides, excise them and replace them with the correct nucleotides. In contrast to nucleotide excision repair, mismatch repair does not operate on bulky adducts or major distortions to the DNA helix. Most of the mismatches are substitutes within a chemical class, e.g. a C incorporated instead of a T. This causes only a subtle helical distortions in the DNA, and the misincorporated nucleotide is a normal component of DNA. The ability of a cell to recognize a mismatch reflects the exquisite specificity of MutS, which can distinguish normal base pairs from those resulting from misincorporation. Of course, the repair machinery needs to know which of the nucleotides at a mismatch pair is the correct one and which was misincorporated. It does this by determining which strand was more recently synthesized, and repairing the mismatch on the nascent strand.

In E. coli, the methylation of A in a GATC motif provides a covalent marker for the parental strand, thus methylation of DNA is used to discriminate parental from progeny strands. Recall that the dam methylase catalyzes the transfer of a methyl group to the A of the pseudopalindromic sequence GATC in duplex DNA. Methylation is delayed for several minutes after replication. IN this interval before methylation of the new DNA strand, the mismatch repair system can find mismatches and direct its repair activity to nucleotides on the unmethylated, newly replicated strand. Thus replication errors are removed preferentially.

The enzyme complex MutH-MutL-MutS , or MutHLS, catalyzes mismatch repair in E. coli. The genes that encode these enzymes, mutH, mutLand mutS, were discovered because strains carrying mutations in them have a high frequency of new mutations. This is called a mutator phenotype, and hence the name mutwas given to these genes. Not all mutator genes are involved in mismatch repair e.g., mutations in the gene encoding the proofreading enzyme of DNA polymerase III also have a mutator phenotype. This gene was independently discovered in screens for defects in DNA replication (dnaQ ) and mutator genes (mutD). Three complementation groups within the set of mutator alleles have been implicated primarily in mismatch repair these are mutH, mutLand mutS.

MutS will recognize seven of the eight possible mismatched base pairs (except for C:C) and bind at that site in the duplex DNA (Figure 7.16). MutHand MutL (with ATP bound) then join the complex, which then moves along the DNA in either direction until it finds a hemimethylated GATC motif, which can be as far a few thousand base pairs away. Until this point, the nuclease function of MutH has been dormant, but it is activated in the presence of ATP at a hemimethylated GATC. It cleaves the unmethylated DNA strand, leaving a nick 5' to the G on the strand containing the unmethylated GATC (i.e. the new DNA strand). The same strand is nicked on the other side of the mismatch. Enzymes involved in other processes of repair and replication catalyze the remaining steps. The segment of single-stranded DNA containing the incorrect nucleotide is to be excised by UvrD, also known as helicase II and MutU. SSB and exonuclease I are also involved in the excision. As the excision process forms the gap, it is filled in by the concerted action of DNA polymerase III (Figure 7.16.).

Figure 7.16 (part 1). Mismatch Repair by MutHLS: recognition of mismatch (shown in red), identifying the new DNA strand (using the hemimethylated GATC shown in blue) and cutting to encompass the unmethylated GATC and the misincorporated nucleotide (red G).

Figure 7.16 (part 2). Mismatch Repair: excision of the DNA with the misincorporated nucleotide bu Uvr D (aided by exonuclease I and SSB), gap filling by DNA polymerase III and ligation.

Mismatch repair is highly conserved, and investigation of this process in mice and humans is providing new clues about mutations that cause cancer.Homologs to the E. coli genes mutLand mutShave been identified in many other species, including mammals. The key breakthrough came from analysis of mutations that cause one of the most common hereditary cancers, hereditary nonpolyposis colon cancer(HNPCC). Some of the genes that, when mutated, cause this disease encode proteins whose amino acid sequences are significantly similar to those of two of the E. colimismatch repair enzymes. The human genes are called hMLH1(for human mutLhomolog 1), hMSH1, and hMSH2(for human mutS homolog 1 and 2, respectively). Subsequent work has shown that these enzymes in humans are involved in mismatch repair. Presumably the increased frequency of mutation in cells deficient in mismatch repair leads to the accumulation of mutations in proto-oncogenes, resulting in dysregulation of the cell cycle and loss of normal control over the rate of cell division.

The human homologs to bacterial enzymes involved in mismatch repair are also implicated in homologous functions. Given the human homologs discussed above, which enzymatic functions found in bacterial mismatch repair are also found in humans? What functions are missing, and hence are likely carried out by an enzyme not homologous to those used in bacterial mismatch repair?

Recombination Repair (Retrieval system)

In the three types of excision repair, the damaged or misincorporated nucleotides are cut out of DNA, and the remaining strand of DNA is used for synthesis of the correct DNA sequence. However, this complementary strand is not always available. Sometimes DNA polymerase has to synthesize past a lesion, such as a pyrimidine dimer or an AP site. One way it can do this is to stop on one side of the lesion and then resume synthesis about 1000 nucleotides further down. This leaves a gap in the strand opposite the lesion (Figure 7.17).

The information needed at the gap is retrieved from the normal daughter molecule by bringing in a single strand of DNA, using RecA-mediated recombination (see Chapter VIII). This fills the gap opposite the dimer, and the dimer can now be replaced by excision repair (Figure 7.17). The resulting gap in the (previously) normal daughter can be filled in by DNA polymerase, using the good template.

Figure 7.17. Recombination repair, a system for retrieval of information

Translesion Synthesis

As just described, DNA polymerase can skip past a lesion on the template strand, leaving behind a gap. It has another option when such a lesion is encountered, which is to synthesis DNA in a non-template directed manner. This is called translesion synthesis, bypass synthesis, or error-prone repair. This is the last resort for DNA repair, e.g. when repair has not occurred prior to replication. In translesion replication, the DNA polymerase shifts from template directed synthesis to catalyzing the incorporation of random nucleotides. These random nucleotides are usually mutations (i.e. in three out of four times), hence this process is also designated error-prone repair.

Translesion synthesis uses the products of the umuCand umuDgenes. These genes are named for the UV nonmutable phenotype of mutants defective in these genes

Question 7.11. Why do mutations in genes required for translesion synthesis (error prone repair) lead to a nonmutable phenotype?

UmuD forms a homodimer that also complexes with UmuC. When the concentration of single-stranded DNA and RecA are increased (by DNA damage, see next section), RecA stimulates an autoprotease activity in UmuD2 to form UmuD&rsquo2. This cleaved form is now active in translesional synthesis. UmuC itself is a DNA polymerase. A multisubunit complex containing UmuC, the activated UmuD&rsquo2 and the a subunit of DNA polymerase III catalyze translesional synthesis. Homologs of the UmuC polymerase are found in yeast (RAD30) and humans (XP-V).

The SOSresponse

A coordinated battery of responses to DNA damage in E. coliis referred to as the SOS response. This name is derived from the maritime distress call, &ldquoSOS&rdquo for "Save Our Ship". Accumulating damage to DNA, e.g. from high doses of radiation that break the DNA backbone, will generate single-stranded regions in DNA. The increasing amounts of single-stranded DNA induce SOS functions, which stimulate both the recombination repair and the translesional synthesis just discussed.

Key proteins in the SOS response are RecA and LexA. RecA binds to single stranded regions in DNA, which activates new functions in the protein. One of these is a capacity to further activate a latent proteolytic activity found in several proteins, including the LexA repressor, the UmuDprotein and the repressor encoded by bacteriophage lambda (Figure 7.18). RecA activated by binding to single-stranded DNA is not itself a protease, but rather it serves as a co-protease, activating the latent proteolytic function in LexA, UmuD and some other proteins.

In the absence of appreciable DNA damage, the LexA protein represses many operons, including several genes needed for DNA repair: recA, lexA, uvrA, uvrB, and umuC.When the activated RecA stimulates its proteolytic activity, it cleaves itself (and other proteins), leading to coordinate induction of the SOS regulated operons (Figure 7.18).

Figure 7.18. RecA and LexA control the SOS response.


Background

Protein synthesis is at the core of cellular life. It is carried out by the ribosome, a highly conserved molecular machine with the same basic architecture in all free-living organisms [1–3]. In humans, the ribosome is composed of four ribosomal RNAs (rRNAs) and 80 ribosomal proteins (RPs), and its structure is believed to be largely invariant [4]. However, recent studies have started to uncover some degree of variability in ribosomal components, such as at the level of rRNA modifications and RP expression. These have also been linked to both ribosomal function and the physiological state of cells (reviewed in [5, 6]).

Variability in ribosomal components could lead to a vast number of ribosome variants. Alternatively, the different components may have extra-ribosomal functions, as some ribosomal proteins do. Since synthesis of translational machinery components represents a large part of the energetic cost of cellular life, the abundance of ribosomal proteins is expected to be under tight control. Indeed, many feedback mechanisms have been discovered that link the production of different ribosomal components to maintain an appropriate stoichiometry [7] a number of RPs act in negative feedback loops to control their own expression as well as the expression of other RPs, either at the level of splicing [8, 9] or at the level of mRNA decay [10]. In bacteria, RPs frequently regulate, in negative feedback, the translation of entire RP operons [11, 12]. In eukaryotes, imbalanced RP levels frequently engage the p53 pathway [13–15] to cause cell cycle arrest and apoptosis. Aside from the feedback on ribosome biogenesis, perturbed expression of distinct RPs elicits a broad spectrum of phenotypes, from developmental defects to diseases [5, 6].

Interestingly, analysis of mRNA abundance revealed considerable differences in RP expression across human tissues [16], in mouse development [17], and in cancers [18–24]. However, the functional significance of such variation, as well as the underlying RP-dependent regulatory mechanisms, has remained insufficiently studied. Insights into the physiological roles of specific RPs have mostly come from naturally occurring phenotypes or diseases associated with RP loss of function. For instance, Rpl38, a component of the large ribosomal subunit, is essential for the appropriate axial skeleton formation in mouse embryonic development [17]. The 5′ untranslated regions (5′UTRs) of Hox mRNAs contain sequence elements that prevent translation of the corresponding transcripts unless the Rpl38 protein enables the recognition of their internal ribosome entry site (IRES)-like elements [25]. Furthermore, a striking number of human hematological disorders such as Diamond-Blackfan anemia (DBA) [26], T-cell acute lymphoblastic leukemia [27], and the 5q- syndrome [28] have been linked to mutations or chromosomal deletions which cause RP deficiencies. The consequences can be remarkably circumscribed, as in the case of RPS19, an RP frequently mutated in DBA patients, whose haploinsufficiency leads to reduced translation of GATA1 mRNA [29] and subsequent defects in erythrocyte maturation.

Cancer cells have a remarkable ability to evade anti-tumorigenic signals that control normal tissue architecture and progress into a chronic proliferation program [30]. The high demand for protein synthesis in rapidly dividing malignant cells leads to increased ribosome biogenesis [31]. Surprisingly, however, dysregulation of specific RPs has been observed in both cancer cell lines and patient samples [18–24]. The roles of individual RPs seem rather difficult to predict. For example, by binding to the 5′UTR of p53 mRNA and enhancing its translation, RPL26 can trigger programmed cell death [21]. The ectopically overexpressed RPL36A has an entirely different function, localizing to nucleoli and increasing colony formation and cell growth of hepatocellular carcinoma lines, presumably through a more rapid cell cycling program [20]. Thus, some RPs can act as tumor suppressors, whereas others promote tumorigenesis.

Despite the increasing body of evidence that individual RPs have cell-type-specific functions, a comprehensive study of RP expression heterogeneity across human cells has not been carried out so far. Furthermore, the factors that drive differential RP expression in distinct cellular contexts remain largely unknown. Through a comprehensive analysis of human RP expression pattern across 28 tissues, more than 300 primary cells, and 16 tumor types, we here estimate that about a quarter of RP genes exhibit tissue-specific expression. We find a particularly high RP expression heterogeneity in the hematopoietic system, where a small number of RP genes unequivocally discriminate cells of distinct lineages and developmental stages. Our analysis of transcription regulatory elements located in the promoters of RP genes indicates that key hematopoietic transcription factors could orchestrate the observed patterns of RP expression. Strikingly, we uncover a consistent dysregulated expression of individual RPs across cancers, which can be partially explained by copy number alterations. Our analysis suggests prominent roles of specific RPs in health and disease.


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Regulator Molecules of the Cell Cycle

In addition to the internally controlled checkpoints, there are two groups of intracellular molecules that regulate the cell cycle. These regulatory molecules either promote progress of the cell to the next phase (positive regulation) or halt the cycle (negative regulation). Regulator molecules may act individually, or they can influence the activity or production of other regulatory proteins. Therefore, the failure of a single regulator may have almost no effect on the cell cycle, especially if more than one mechanism controls the same event. Conversely, the effect of a deficient or non-functioning regulator can be wide-ranging and possibly fatal to the cell if multiple processes are affected.

Positive Regulation of the Cell Cycle

Two groups of proteins, called cyclins and cyclin-dependent kinases (Cdks), are responsible for the progress of the cell through the various checkpoints. The levels of the four cyclin proteins fluctuate throughout the cell cycle in a predictable pattern (Figure 2). Increases in the concentration of cyclin proteins are triggered by both external and internal signals. After the cell moves to the next stage of the cell cycle, the cyclins that were active in the previous stage are degraded.

Figure 2. The concentrations of cyclin proteins change throughout the cell cycle. There is a direct correlation between cyclin accumulation and the three major cell cycle checkpoints. Also note the sharp decline of cyclin levels following each checkpoint (the transition between phases of the cell cycle), as cyclin is degraded by cytoplasmic enzymes. (credit: modification of work by “WikiMiMa”/Wikimedia Commons)

Figure 3. Cyclin-dependent kinases (Cdks) are protein kinases that, when fully activated, can phosphorylate and thus activate other proteins that advance the cell cycle past a checkpoint. To become fully activated, a Cdk must bind to a cyclin protein and then be phosphorylated by another kinase.

Cyclins regulate the cell cycle only when they are tightly bound to Cdks. To be fully active, the Cdk/cyclin complex must also be phosphorylated in specific locations. Like all kinases, Cdks are enzymes (kinases) that phosphorylate other proteins. Phosphorylation activates the protein by changing its shape. The proteins phosphorylated by Cdks are involved in advancing the cell to the next phase. (Figure 3). The levels of Cdk proteins are relatively stable throughout the cell cycle however, the concentrations of cyclin fluctuate and determine when Cdk/cyclin complexes form. The different cyclins and Cdks bind at specific points in the cell cycle and thus regulate different checkpoints.

Since the cyclic fluctuations of cyclin levels are based on the timing of the cell cycle and not on specific events, regulation of the cell cycle usually occurs by either the Cdk molecules alone or the Cdk/cyclin complexes. Without a specific concentration of fully activated cyclin/Cdk complexes, the cell cycle cannot proceed through the checkpoints.

Although the cyclins are the main regulatory molecules that determine the forward momentum of the cell cycle, there are several other mechanisms that fine-tune the progress of the cycle with negative, rather than positive, effects. These mechanisms essentially block the progression of the cell cycle until problematic conditions are resolved. Molecules that prevent the full activation of Cdks are called Cdk inhibitors. Many of these inhibitor molecules directly or indirectly monitor a particular cell cycle event. The block placed on Cdks by inhibitor molecules will not be removed until the specific event that the inhibitor monitors is completed.

Negative Regulation of the Cell Cycle

The second group of cell cycle regulatory molecules are negative regulators. Negative regulators halt the cell cycle. Remember that in positive regulation, active molecules cause the cycle to progress.

The best understood negative regulatory molecules are retinoblastoma protein (Rb), p53, and p21. Retinoblastoma proteins are a group of tumor-suppressor proteins common in many cells. The 53 and 21 designations refer to the functional molecular masses of the proteins (p) in kilodaltons. Much of what is known about cell cycle regulation comes from research conducted with cells that have lost regulatory control. All three of these regulatory proteins were discovered to be damaged or non-functional in cells that had begun to replicate uncontrollably (became cancerous). In each case, the main cause of the unchecked progress through the cell cycle was a faulty copy of the regulatory protein.

Rb, p53, and p21 act primarily at the G1 checkpoint. p53 is a multi-functional protein that has a major impact on the commitment of a cell to division because it acts when there is damaged DNA in cells that are undergoing the preparatory processes during G1. If damaged DNA is detected, p53 halts the cell cycle and recruits enzymes to repair the DNA. If the DNA cannot be repaired, p53 can trigger apoptosis, or cell suicide, to prevent the duplication of damaged chromosomes. As p53 levels rise, the production of p21 is triggered. p21 enforces the halt in the cycle dictated by p53 by binding to and inhibiting the activity of the Cdk/cyclin complexes. As a cell is exposed to more stress, higher levels of p53 and p21 accumulate, making it less likely that the cell will move into the S phase.

Rb exerts its regulatory influence on other positive regulator proteins. Chiefly, Rb monitors cell size. In the active, dephosphorylated state, Rb binds to proteins called transcription factors, most commonly, E2F (Figure 4). Transcription factors “turn on” specific genes, allowing the production of proteins encoded by that gene. When Rb is bound to E2F, production of proteins necessary for the G1/S transition is blocked. As the cell increases in size, Rb is slowly phosphorylated until it becomes inactivated. Rb releases E2F, which can now turn on the gene that produces the transition protein, and this particular block is removed. For the cell to move past each of the checkpoints, all positive regulators must be “turned on,” and all negative regulators must be “turned off.”

Figure 4. Rb halts the cell cycle and releases its hold in response to cell growth.

Rb and other proteins that negatively regulate the cell cycle are sometimes called tumor suppressors. Why do you think the name tumor suppressor might be appropriate for these proteins?


Dataset: 1000 Genomes Project

We used the short RNA-seq datasets that were released by the 1KG Project [32] and were derived from the lymphoblastoid cell lines (LCL) of individuals belonging to five population groups: CEU (Utah Residents with Northern and Western European Ancestry), FIN (Finnish in Finland), GBR (British from England and Scotland), TSI (Toscani in Italia), and YRI (Yoruba in Ibadan, Nigeria). The 1KG Project released 452 total short RNA-sequencing datasets (and 35 technical replicates). The samples were sequenced at seven facilities (Geuvadis Consortium). The 48 samples that were sent to one of the facilities (number “six”) were sequenced using 47 cycles of sequencing whereas all other samples were sequenced using 33 cycles. In order to be consistent, we removed all samples that came from facility “six”—this left us with 434 LCL datasets for our downstream analyses (83 CEU, 94 FIN, 88 GBR, 87 TSI, and 82 YRI). We used the 35 technical replicates (1 CEU, 1 FIN, 1 GBR, 1 TSI, and 1 YRI sequenced at seven facilities) for the rRF correlations.

Other datasets: Gene Expression Omnibus and The Cancer Genome Atlas

We analyzed short RNA-seq for six samples from the Gene Expression Omnibus (GEO) data (GSE99430) [34] which looked at the 293T cells and their derived extracellular vesicles (EV). 293T cell samples are as follows: SRR5628228, SRR5628229, and SRR5628230. The EV samples are as follows: SRR5628231, SRR5628232, and SRR5628233. The abundances of the rRFs found in these datasets can be found in Additional file 4. We also analyzed short RNA-seq data for the 80 uveal melanoma (UVM) samples from The Cancer Genome Atlas (TCGA) [33].

Reference rRNAs

We used the GenBank 45S (RNA45SN1), 5S (RNA5S12), 12S (MT-RNR1), and 16S (MT-RNR2) rRNAs as our reference rRNA sequences for this analysis. The GenBank accession numbers are as follows: NR_145819.1, NR_023374.1, NR_137294.1, and NR_137295.1, respectively. RNA45SN1 was chosen as a representative 45S and is 13,351 nucleotides (nts) long. RNA5S12 was chosen as a representative 5S rRNA and is 121 nts long. MT-RNR1 and MT-RNR2 are the two consensus MT rRNAs and are 954 and 1,559 nts long, respectively.

Defining the “rRNA space”

We define “rRNA space” as the union of (a) the genomic regions that comprise the six rRNAs (see previous paragraph), (b) all rRNA repeats that are listed in RepeatMasker [59] including partial instances, and (c) any additional genomic regions that are identified via a glsearch [60] search of the genome using the six rRNAs as queries, default parameters, and an E value cutoff of 1E−08. An rRF that can be found in the union of the genomic regions obtained through steps a, b, and c above as well as elsewhere in the genome is referred to as an “ambiguous” rRF. Otherwise, it is referred to as being “exclusive” to the rRNA space. This is analogous to our definition of tRNA space and our analyses of tRFs [26, 30, 36, 48].

Mapping

We first processed the 434 short RNA-seq datasets using cutadapt [61] to quality-trim and remove adapters from the sequenced reads. The reads were then mapped to the genome using a brute-force, deterministic, and exhaustive approach that enforced exact matching to the genome. Only reads with a minimum of 16 nts were kept and analyzed further. During mapping, we catalogued reads which are exclusive to the rRNA space and which are ambiguous. We also kept track of reads that straddle either the left or the right boundary of any of the six rRNAs (Fig. 1a blue box).

Thresholding

We thresholded the rRFs using the Threshold-seq tool [35] and default parameter settings. Threshold-seq calculates an adaptive sequence read cutoff that is different for each sample (Fig. 1a green box). We also calculated a ≥ 10 RPM threshold by first normalizing each rRF’s abundance to reads-per-million (RPM) by dividing the number of reads that support the rRF by the total number of sequenced short RNA reads (i.e., read depth) and multiplying by 1 million then keeping only unique rRFs that passed a threshold of ≥ 10 RPM. (Fig. 1a orange box).

Determining length cutoffs

As might be expected, shorter sequences are more likely than longer sequences to have many genomic instances that are not part of the rRNA space. In fact, we find that many of the identified rRFs with lengths ≥ 16 nts are ambiguous. Thus, for each rRNA in turn, we identified the minimum length at which fewer than 2% of the genomic instances of an rRNA’s rRFs fall outside of the rRNA space. To do this, we first examined rRFs from the same rRNA if and only if their sequence lengths ranged from 16 through 33 nts inclusive. Next, for each rRF, we counted the number of its instances that fall inside the rRNA space, outside the rRNA space, and across the whole genome. For all rRFs from a given rRNA, and for each sequence length value (16–33 nts), we calculated the ratio of the number of instances that fall inside of the rRNA space over the total number of rRFs that fall outside of the rRNA space and call this the signal to noise ratio (S/N). We identified the minimum rRF length for which the S/N becomes ≥ 50 (the number of instances that fall outside of the rRNA space over the total number of genomic instances is ≤ 2%). We repeated this calculation separately for each of the six rRNAs (Fig. 1a red box).

Analysis

Differential abundances were calculated using the Significance Analysis of Microarrays (SAM) package in R using a stringent false discovery rate (FDR) cutoff of 0.01. Partial least squares-discriminant analysis (PLS-DA) was carried out in R using the default settings and a VIP cutoff of 1.5. Pearson correlations were calculated using R.

RNA isolation

For total RNA preparation, cells were grown in suspension using RPMI 1640 media with 30% non-heat inactivated FBS + glutamate (Sigma-Aldrich). After seeding, cells were grown for 3–5 days and harvested. RNA was isolated using TRIzol extraction (Invitrogen).

Northern blotting

We purchased commercially available lymphoblastoid cell lines (Coriell Institute) derived from 18 total people from the CEU, GBR, and YRI populations. For each population, we purchased three male samples and three female samples. The cell lines are the following: CEU females (GM12769, GM12807, GM12837) CEU males (GM12884, GM12905, GM12919), YRI females (GM18487, GM18523, GM18870), YRI males (GM18907, GM19203, GM19239), GBR females (HG00122, HG00134, HG00137), and GBR males (HG00243, HG00264, HG01789). As per Coriell’s policy, all cell lines were tested and found to be mycoplasma-free. 5μg of RNA from each cell line was run on a 15% acrylamide/8 M urea gel at 250 V for 45 min. 100 nmol of RNA target cDNA (5.8S 24-mer, GGGCTACGCCTGTCTGAGCGTCGC 5.8S 21-mer, TACGCCTGTCTGAGCGTCGCT 5S 18-mer, ACCGGGTGCTGTAGGCTT 28S 20-mer, CGCGACCTCAGATCAGACGT) served as positive control. Gel was transferred to Hybond™-N + membrane (Amersham Biosciences, catalog number: RPN303B) and transferred at 400 mA for 10 min. Membrane was dried and then cross-linked twice at 120,000 μJ/cm 2 . All membranes were cut so that the top portion could be probed with the 5S rRNA probe (ACGTCTGATCTGAGGTCGCGT)—the loading control, and the bottom portion was probed with the 5.8S 24-mer (GCGACGCTCAGACAGGCGTAGCCC), 5.8S 21-mer (AGCGACGCTCAGACAGGCGTA), 5S 18-mer (ACCGGGTGCTGTAGGCTT), and 28S 20-mer (ACGTCTGATCTGAGGTCGCG). Membranes were pre-hybridized in hybridization buffer (PerfectHyb™ Plus Hybridization Buffer: H7033-1 L) for 30 min rotating at 37 °C. Northern probes were made using the DIG labeling kit (DIG Oligonucleotide 3′-End Labeling Kit, 2nd Gen: 3353575910). For Fig. 5, the 9 LCL female and 9 LCL male RNAs were run on two different gels and the top portions of each membranes were incubated with 2.5 μl of 5S probe and the lower portions of the membranes were incubated with 5 μl of 5.8S 24-mer probe for 16 h rotating at 37 °C. For Additional file 6: Figure S5, female CEU (GM12769), GBR (HG0112), and YRI (GBM18523) RNA was used and uncut membranes were incubated with 5 μl of the corresponding probes. Detection of membranes was done using the DIG detection kit (DIG Wash and Block Buffer Set: 11585762001, Anti-Digoxigenin-AP, Fab fragments: 11093274910, CDP-Star Chemiluminescent Substrate: C0712-100ML) following the manufacturer’s instructions.

Secondary structures

Secondary structures were generated using the Vienna RNAFold Web Server http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi [62] with default settings. The sequences for which we predicted secondary structures are listed in the “Reference rRNAs” section.

Deep sequencing of independently obtained commercial cell lines

We purchased commercially available lymphoblastoid cell lines (Coriell Institute) derived from two individuals: one who was a 63-year-old African American male (ND02672) and one who was a 66-year-old Caucasian American male (ND07114). As per Coriell’s policy, all cell lines were tested and found to be mycoplasma-free. Two different libraries were created for each sample: Illumina’s TruSeq Small RNA Library Prep Kit Set (#RS-200) and NEB’s NEBNext Small RNA Prep Set for Illumina (#E7330) at the Jefferson Genomics Core Facility according to the standard kit protocols, which size select for small RNAs. The Illumina NextSeq 3′-adapter is TGGAATTCTCGGGTGCCAAGG, and the NEBNext 3′-adapter is AGATCGGAAGAGCACACGTCT. The samples were all sequenced using the Illumina NextSeq 500 sequencing platform at 75 cycles and 30 million reads.


Newly discovered DNA repair mechanism

Tucked within its double-helix structure, DNA contains the chemical blueprint that guides all the processes that take place within the cell and are essential for life. Therefore, repairing damage and maintaining the integrity of its DNA is one of the cell's highest priorities.

Researchers at Vanderbilt University, Pennsylvania State University and the University of Pittsburgh have discovered a fundamentally new way that DNA-repair enzymes detect and fix damage to the chemical bases that form the letters in the genetic code. The discovery is reported in an advanced online publication of the journal Nature on Oct. 3.

"There is a general belief that DNA is 'rock solid' -- extremely stable," says Brandt Eichman, associate professor of biological sciences at Vanderbilt, who directed the project. "Actually DNA is highly reactive."

On a good day about one million bases in the DNA in a human cell are damaged. These lesions are caused by a combination of normal chemical activity within the cell and exposure to radiation and toxins coming from environmental sources including cigarette smoke, grilled foods and industrial wastes.

"Understanding protein-DNA interactions at the atomic level is important because it provides a clear starting point for designing drugs that enhance or disrupt these interactions in very specific ways," says Eichman. "So it could lead to improved treatments for a variety of diseases, including cancer."

The newly discovered mechanism detects and repairs a common form of DNA damage called alkylation. A number of environmental toxins and chemotherapy drugs are alkylation agents that can attack DNA.

When a DNA base becomes alkylated, it forms a lesion that distorts the shape of the molecule enough to prevent successful replication. If the lesion occurs within a gene, the gene may stop functioning. To make matters worse, there are dozens of different types of alkylated DNA bases, each of which has a different effect on replication.

One method to repair such damage that all organisms have evolved is called base excision repair. In BER, special enzymes known as DNA glycosylases travel down the DNA molecule scanning for these lesions. When they encounter one, they break the base pair bond and flip the deformed base out of the DNA double helix. The enzyme contains a specially shaped pocket that holds the deformed base in place while detaching it without damaging the backbone. This leaves a gap (called an "abasic site") in the DNA that is repaired by another set of enzymes.

Human cells contain a single glycosylase, named AAG, that repairs alkylated bases. It is specialized to detect and delete "ethenoadenine" bases, which have been deformed by combining with highly reactive, oxidized lipids in the body. However, AAG also handles many other forms of akylation damage. Many bacteria, however, have several types of glycosylases that handle different types of damage.

"It's hard to figure out how glycosylases recognize different types of alkylation damage from studying AAG since it recognizes so many," says Eichman. "So we have been studying bacterial glycosylases to get additional insights into the detection and repair process."

That is how they discovered the bacterial glycosylase AlkD with its unique detection and deletion scheme. All the known glycosylases work in basically the same fashion: They flip out the deformed base and hold it in a special pocket while they excise it. AlkD, by contrast, forces both the deformed base and the base it is paired with to flip to the outside of the double helix. This appears to work because the enzyme only operates on deformed bases that have picked up an excess positive charge, making these bases very unstable. If left alone, the deformed base will detach spontaneously. But AlkD speeds up the process by about 100 times. Eichman speculates that the enzyme might also remain at the location and attract additional repair enzymes to the site.

AlkD has a molecular structure that is considerably different from that of other known DNA-binding proteins or enzymes. However, its structure may be similar to that of another class of enzymes called DNA-dependent kinases. These are very large molecules that possess a small active site that plays a role in regulating the cells' response to DNA damage. AlkD uses several rod-like helical structures called HEAT repeats to grab hold of DNA. Similar structures have been found in the portion of DNA-dependent kinases with no known function, raising the possibility that they play an additional, unrecognized role in DNA repair.

The new repair mechanism may also prove to be the key to understanding the differences in the way that the repair enzymes identify and repair toxic and mutagenic lesions. That is important because mutagenic lesions that the repair mechanisms miss are copied to daughter cells and so can spread whereas the deleterious effects of toxic lesions are limited to the original cell.

Understanding these differences could lead to more effective chemotherapy agents, Eichman points out. These drugs are strong alkylating agents designed to induce lesions in a cancer patient's DNA. Because cancer cells are reproducing more rapidly than the body's normal cells, the agent kills them preferentially. However, in addition to toxic lesions that kill the cell, the agent also produces lesions that cause mutations, which can lead to additional complications. Additionally, the efficacy of these drugs is low because they are working against the body's repair mechanisms. If it were possible to design a chemo drug that predominantly creates toxic lesions, however, it should be more effective and have fewer harmful side-effects. Alternatively, if we understood how glycosylases recognize alkylation damage, it may be possible to design a drug that specifically inhibits repair of toxic, but not mutagenic lesions.

Vanderbilt graduate student Emily H. Rubinson, A.S. Prakasha Gowda and Thomas E. Spratt from Pennsylvania State University College of Medicine and Barry Gold from the University of Pittsburgh contributed to the study, which was supported by grants from the American Cancer Society, National Institutes of Health and U.S. Department of Energy.

Story Source:

Materials provided by Vanderbilt University. Original written by David F. Salisbury. Note: Content may be edited for style and length.


Introduction

The sequencing of whole genomes represents a landmark in modern biology (Adams et al., 2000 Goffeau et al., 1996 Lander et al., 2001 Venter et al., 2001 Waterston et al., 2002), revolutionizing the way genes are found, classified and analyzed. It has also brought about a shift in how biological problems are approached. It has encouraged us to move beyond the limitations of understanding single processes and inspired us to ask how biological events occur at the systems level rather than analyzing the behavior of a single signaling kinase, for example, we now seek to understand how all elements in a signaling pathway interact rather than asking how a gene responds to an extracellular cue, we now want to know how the genome as a whole responds. These types of global approach represent the first steps towards understanding biological functions as they really occur – in the context of biological systems.

While the sequencing of genomes has influenced virtually all fields of biology, it has had the most profound impact on the study of gene expression itself. This is particularly true because the availability of genome sequence information has coincided with the development of microarray analysis, which allows us to interrogate gene expression at a system level (Schena et al., 1995). Although most genome-wide analysis methods are largely descriptive and generally only provide lists of what parts of the genome undergo changes in activity, we can now routinely mine genome-wide expression data, using computational tools to predict biological pathways involved in a particular physiological response or to group samples, for example, normal and malignant tissues, according to expression patterns (Slonim, 2002). Despite these successes, a key realization has been that even these comprehensive approaches cannot answer some of the most fundamental questions in genome biology, such as why more advanced organisms do not necessarily use more genes to achieve complexity how gene expression programs are defined in a tissue- and cell-type-specific manner and how the spatial and temporal organization of transcription, RNA processing, RNA degradation, export, DNA replication or DNA repair affects genome function. It seems clear now that, apart from genome sequence, additional aspects of genome biology must be considered if we are to understand how genomes actually work.

A key emerging contributor to genome function and regulation is the spatial and temporal arrangement of the genome and gene expression processes in nuclear space (Misteli, 2001 Spector, 2003). Dramatic developments in high-resolution and live-cell imaging have revealed that the cell nucleus is a highly heterogeneous and complex organelle, and that global genome architecture changes during processes such as differentiation and development (Misteli, 2001 Spector, 2003). One unique feature of the mammalian cell nucleus is the presence of structural and functional domains that lack membrane boundaries (Lamond and Earnshaw, 1998 Matera, 1999). Spatial organization of the genome is achieved by a non-random arrangement of chromosomes in the interphase nucleus, with chromosomes occupying preferential intranuclear positions (Cremer and Cremer, 2001 Parada et al., 2004). Chromosomes, genome domains and gene loci may congress in space to form functional chromatin neighborhoods, such as transcriptionally silent heterochromatin regions or clusters of active genes. In addition to the non-random spatial arrangement of genomes, the nucleus also contains numerous proteinaceous domains, such as the nucleolus and splicing factor compartments, which represent distinct structural, and probably functional, subcompartments (Misteli, 2005). Although the full contribution of the spatial organization of the genome and nuclear proteins is still unknown, it seems clear that we must understand genome function in the context of this architectural organization to answer some of the key questions in genome biology.

The ultimate goal of a systems biology view of the cell nucleus is to understand genome function within the architectural framework of the nucleus. Gaining such a systems view of nuclear function will involve several steps. First, we must generate proteomic and genomic inventories of nuclear components, including genome sequence elements, epigenetic modifications, higher-order chromatin structure, chromatin-binding complexes and nuclear compartments. Second, we must understand the cell biological properties of nuclear processes in living cells in terms of characteristics such as their spatial organization and dynamic properties. Third, we must integrate experimental data on process dynamics and spatial organization, using computational approaches (Fig. 1). Several technological developments now make this a realistic, although still highly challenging, goal. On the one hand, proteomic and genomic approaches can provide complete lists of components present in particular nuclear structures, and identify what transcription factors are bound where throughout the genome, and what coding and non-coding genome regions are active at any given time. On the other hand, quantitative in vivo microscopy methods provide the first glimpse of how DNA, RNA and proteins behave inside the nuclei of living cells. Combining these methods and mining the data by emerging computational approaches will eventually lead to a realistic picture of gene expression. We review here how far we have progressed on the long road towards achieving a systems biology view of the cell nucleus and of genome function.


6 POST-TRANSLATION REGULATION OF RPGS

Once translated, RPs may undergo a number of post-translational modifications including phosphorylation, ubiquitination, methylation, acetylation, and SUMOylation (Dalla Venezia, Vincent, Marcel, Catez, & Diaz, 2019 Genuth & Barna, 2018a ). Unlike other regulatory steps in RPG production, most post-translational modifications appear to be protein-specific (D. Simsek & Barna, 2017 ). Indeed, the dependence of these modifications on the amino acid sequence makes them highly suitable for gene-specific regulation. In general, RP modifications can be divided into two groups the first includes modifications regulating protein stability like the proteasome inducing ubiquitination. The second includes modifications that alter the function or the behavior of the proteins, like phosphorylation, which may alter subcellular localization or protein interactions of RPs. Phosphorylation can also alter ribosome biogenesis or even lead to extra ribosomal functions. These protein modifications may occur either co-translationally or post-translationally, and they are considered the best source for a potential ribosome specialization (Genuth & Barna, 2018b Ruiz-Canada, Kelleher, & Gilmore, 2009 Sauert, Temmel, & Moll, 2015 C. I. Yang, Hsieh, & Shan, 2019 ). In the following section, we will discuss the impact of specific modifications on RP regulation, functions, and stability.

The very first RP modification was discovered in RPS6/eS6 more than 4 decades ago by the Wool lab, and it remains highly studied and functionally relevant (Gressner & Wool, 1974 Khalaileh et al., 2013 Ruvinsky et al., 2009 ). The phosphorylation of eS6 is implicated in cell size control, pancreatic cancer, glucose homeostasis, activation of neurons, integration of light signals, and circadian clock signals (Enganti et al., 2017 Khalaileh et al., 2013 Z. A. Knight et al., 2012 Ruvinsky et al., 2005 ). The small subunit protein eS6 is highly conserved from yeast to human and several of the phosphorylated residues are also conserved. In mammals, the two serine residues close to the carboxy-terminus of eS6 are directly phosphorylated by S6K in response to mTORC1 (Nakashima & Tamanoi, 2010 ). In yeast, the conserved serine residues (Ser232 and Ser233) are also phosphorylated, likely by the functional S6K homolog Sch9 (Gonzalez et al., 2015 ). However, mutation of this residue in yeast did not have major effect on growth in rich media (Johnson & Warner, 1987 ). In contrast, The role of phosphorylation in mammalian cells remains unclear since mutation in these residues had little phenotypic effect (Ruvinsky et al., 2009 ).

Phosphorylation is not restricted to eS6 but was also detected in a large number of RPs, and several of these modifications altered the function of their respective proteins. For example, in the case of RPL12/uL11, phosphorylation altered translation during mitosis while phosphorylation of RPS15/uS19 resulted in LRRK2 neurodegeneration in Parkinson's disease (Imami et al., 2018 I. Martin et al., 2014 ). In yeast, phosphorylation of Ser223 of RPS7/eS7 is implicated in the biogenesis of the small ribosomal subunit, translation, and cellular proliferation (Tomioka et al., 2018 ). Eventually, phosphorylation was found in almost all RPs tested, increasing the spectrum of RP regulation (Dinman, 2016 Ferretti & Karbstein, 2019 ). Notably, phosphorylation may also expand the function of RPs beyond their function in the ribosome. For example, stoichiometric phosphorylation of RPL13A/uL13 at a single serine triggers its release from assembled ribosomes to function as an essential component of the interferon-ϒ activated inhibitor of translation complex (Mazumder et al., 2003 Mukhopadhyay et al., 2008 ). In time, it is likely that more extra-ribosomal functions will be discovered. In addition to protein phosphorylation, other types of modifications also alter the function of RPs. For example, methylation of RPL42/eL42 modulates translation and cellular proliferation in S. pombe, while methylation of RPL3/uL3 promotes translational elongation fidelity, and histidine methylation of uL3 contributes to the assembly of the 60S ribosomal subunit in S. cerevisiae (Al-Hadid et al., 2014 Shirai, Sadaie, Shinmyozu, & Nakayama, 2010 ). SUMOylation is another common RP modification that alters the subcellular localization of RPL22/eL22 in Drosophila, and contributes to RPL11/uL5-mediated activation of p53 in mice (El Motiam et al., 2019 Kearse, Ireland, Prem, Chen, & Ware, 2013 ).

One of the most recent developments in the study of post-translational modification of RPs is the discovery of the association of the UFMylation enzyme (UFL1) with the assembled 60S LSU and 80S ribosome and its involvement in metazoan-specific post-translational modifications (PTM) of RPs including RPL26/uL24 (Deniz Simsek et al., 2017 Xu & Barna, 2020 ). UFMylation of uL24 plays a direct role in co-translational protein translocation through the degradation of a translocation-arrested endoplasmic reticulum protein by targeting it to the lysosomes (Walczak et al., 2019 L. Wang et al., 2020 ). Finally, glycosylation, hydroxylation, and acetylation can modulate RP function by altering their secretion, RNA binding, and protein synthesis properties (Kamita et al., 2011 Y. Kim, Lee, Kim, & Kim, 2016 Yanshina, Bulygin, Malygin, & Karpova, 2015 ). Despite these numerous examples of RP modifications, the mechanistic details and impact on protein synthesis are mostly unknown leading to a debate. Indeed, the capacity of a single or a cluster of protein modifications to alter translation is contested given that the peptidyl transferase center of the ribosome is made mostly of rRNA (Dinman, 2016 Ferretti & Karbstein, 2019 ). The challenge now is not to find more RP modifications but rather to better understand their contribution to the functions of RPs and ribosomes.


Ribosome Functions on Endoplasmic Reticulum

What is different about the protein that is destined for the rough endoplasmic reticulum?

[Note: This section describes work that led to a Nobel Prize in Medicine and Physiology to Dr. Gunter Blobel. For more information about Dr. Blobel's work and the pioneering discoveries, click: http://www.nobel.se/medicine/laureates/1999/ ]

The major difference is the fact that it has a hydrophobic signal sequence. This simplified cartoon shows that this is the first part of the protein produced. After the signal sequence is completed, protein synthesis is further inhibited. This is to allow the interaction of the signal sequence with a complex on the rough endoplasmic reticulum. In the above cartoon, note that the signal peptide is allowed to enter and essentially guide the protein into the lumen of the rough endoplasmic reticulum. Once the signal sequence is detected, protein synthesis resumes and the rest of the protein is inserted in the lumen. Note that a signal peptidase near the inner surface of the membrane works to cleave the signal sequence from the growing peptide.

The text reading for this discussion is Alberts et al, Molecular Biology of the Cell, third edition, Garland Publishing, 1994, pp 577-588 (Chapter 12) and pp 599-616.

]

The complex is actually more complicated than the above. The cartoon to the left shows a view of the signal sequence binding and interaction. Note that the signal sequence is recognized by a Recognition Particle, or SRP. This is then bound to a receptor. This complex guides the protein through a channel like region. It also consists of a docking site for the ribosome.

Another cartoon view of this process shows the signal receptor peptide (SRP) that associates with the large subunit of the ribosome that allows binding to the receptor on the rough endoplasmic reticulum.

After the protein is synthesized, the ribosome dissociates into large and small subunits and the SRP also looses its attachment to the receptor.

Current studies of ribosomal interactions with ER :

Andrea Neuhof, M.M. Rolls, B. Jungnickel, K-U Kalies and T A Rapoport, Binding of Signal Recognition particle gives ribosome/nascent chain complexes a competitive advantage in endoplasmic reticulum membrane interaction. Molecular Biology of the Cell, 9: 103-115. 1997

  • Ø Proteins destined for RER sorting make a signal sequence.
  • Ø As signal sequence elongates, it is bound by the signal recognition particle (SRP54) (GTP dependent binding).
  • Ø SRP then binds to the SRP receptor (docking protein) on the ER membrane.
  • Ø At the same time, ribosomes bind to the RER translocation channel formed by the Sec61p complex.
  • Ø This Sec61p complex is a major component of a protein-conducting channel which also includes the “translocating chain-associating membrane protein” or TRAM. This conducts the protein into the RER sac.

Neuhof et al, 1997 have asked the following question: What stimulates the specificity of ribosomal docking?

  • Ø Question was asked because ribosomes dock to the Sec61p complex even without the signal sequence. Some clues:
  • Ø As the signal sequence begins to appear (short) Ø it can be removed from the ER membrane with high salt concentrations.
  • Ø As the signal sequence elongates, Ø ribosome binding is stronger and ribosome complex becomes insensitive to proteases and high salt.

Ø Neuhof's study hypothesized that the presence of the signal peptide was crucial for specific binding. Study Design: ü Added nontranslating ribosomes to compete with translating ribosomes in an in vitro system.

  • ü If Signal receptor protein (SRP) was absent, ü the nontranslating ribosomes bound to the Sec61p receptor on ER membranes.
  • ü Also, the nontranslating ribosomes competed with the translating ribosomes.

ü Added SRP to bind to the signal peptide.

  • ü The translating ribosomes bound tightly and were not displaced.
  • ü Then, nontranslating ribosomes failed to compete for the Sec61p receptor sites.

Hence, SRP gives the translating ribosome a competitive edge once it starts translating the signal sequence.

You can see a better surface view in this cartoon. The cartoon is from your text. It shows the Ribosome sitting on the receptor next to the pore. The signal peptide is noted in red. The remainder of the code is read as the ribosome moves along the mRNA. The fluidity of the membrane allows the ribosome to be docked at its receptor site and also move along the mRNA. Each amino acid is added to the growing chain and the polypeptide gets longer.

This cartoon is also from your text. It shows the system without the ribosome. Here you get a better view of the pore through which the protein projects into the lumen and the signal sequence.

How are newly synthesized proteins inserted in the membrane?

Mechanism varies with the type of protein.

Type I: Signal sequence on amino terminus enters first and continues to elongate. Protein is threaded through the translocating channel (open area in rer membrane) until a hydrophobic stop sequence is reached. That hydrophobic stop sequence (seen as a hatched region in the protein) is then inserted in the membrane and forms the anchor for that protein. Signal is cleaved by protease inside the lumen. Type II: No cleavable signal sequence. These proteins have rather long hydrophobic regions that will be anchored in the membrane. Type II proteins are threaded into the lumen with the C terminus leading. Protein continues to be inserted until it reaches the hydrophobic stop signal sequence. Type III: Same as Type II, only the N terminus leads into the lumen.

What regulates the orientation of Type II and III proteins?

Wahlberg, JM. And Spiess, M. Multiple determinants direct the orientation of signal anchor proteins: The topogenic role of the hydrophobic signal domain. J Cell Biology 137: 555-562.

Tested charged amino acids and length of hydrophobic signal sequence. The "positive inside rule" states that amino acid residues nearest the cytosolic side of the hydrophobic anchor sequence are more positive than those nearest the lumenal side. So, whichever end has the least positive charges near the signal anchor patch would go into the ER lumen. One can change the direction of translocation of a protein (reverse it) by mutating the protein and making more positively charged groups near the anchor patch of the other end. Below, the cartoon shows that this can be done to change a Type II protein (COOH end enters ER lumen) to a Type III (which has its amino terminal entering the lumen).

Washburn and Speiss (JCB 137: 555-562, 1997) also tested the length of the hydrophobic signal anchor sequence. The following cartoon shows that a longer hydrophobic anchor sequence (seen as the portion running through the membrane) promotes entry with the amino terminal leading into the lumen.

Proteins destined for insertion into membranes, such as ion channels or receptors have mRNA codes for start and stop sequences that allow multiple passes through the membrane. Signalling sequences (patches) can be formed as described in the above cartoon. It shows the insertion of a double pass transmembrane protein with the loop inside the rough endoplasmic reticulum. The red signal patch has the + charges near the cytosol and starts the insertion process. This continues until the hydrophobic stop signal patch is reached. That anchors the second membrane passage. Note, that both C and N terminal portions are in the cytosol Thus, if this protein is destined for the plasma membrane, that loop in the ER lumen will eventually project outside the cell

Membrane proteins that pass through the membrane multiple times (called "multipass transmembrane proteins) have multiple start and stop signals. They are aligned with the hydrophilic and hydrophobic portions of the lipid bilayer as described in the lecture on membranes. This is shown in the following cartoon