Telomere elongation methods?

Telomere elongation methods?

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What sort of telomere elongation methods are there currently?

Would this stop aging? (edit: No, probably)

I couldn't turn up anything good on google. I was thinking that maybe you could sequence the telomeres, trim them all at a certain point, and then engineer a polymerase molecule to extend from that same point. Is this how it's done?

It would be simpler to simply activate telomerase genes or insert them using some vector virus. However, telomerase is a key component in the process of tumoral transformation. Basically, if you don't let cells die they will stack mutations until they become tumoral.

A statistical approach to distinguish telomere elongation from error in longitudinal datasets

Telomere length and the rate of telomere attrition vary between individuals and have been interpreted as the rate at which individuals have aged. The biology of telomeres dictates shortening with age, although telomere elongation with age has repeatedly been observed within a minority of individuals in several populations. These findings have been attributed to error, rather than actual telomere elongation, restricting our understanding of its possible biological significance. Here we present a method to distinguish between error and telomere elongation in longitudinal datasets, which is easy to apply and has few assumptions. Using simulations, we show that the method has considerable statistical power (>80 %) to detect even a small proportion (6.7 %) of TL increases in the population, within a relatively small sample (N = 200), while maintaining the standard level of Type I error rate (α ≤ 0.05).

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Germline mutations of regulator of telomere elongation helicase 1, RTEL1, in Dyskeratosis congenita

Dyskeratosis congenita (DC) is an inherited bone marrow failure and cancer predisposition syndrome caused by aberrant telomere biology. The classic triad of dysplastic nails, abnormal skin pigmentation, and oral leukoplakia is diagnostic of DC, but substantial clinical heterogeneity exists the clinically severe variant Hoyeraal Hreidarsson syndrome (HH) also includes cerebellar hypoplasia, severe immunodeficiency, enteropathy, and intrauterine growth retardation. Germline mutations in telomere biology genes account for approximately one-half of known DC families. Using exome sequencing, we identified mutations in RTEL1, a helicase with critical telomeric functions, in two families with HH. In the first family, two siblings with HH and very short telomeres inherited a premature stop codon from their mother who has short telomeres. The proband from the second family has HH and inherited a premature stop codon in RTEL1 from his father and a missense mutation from his mother, who also has short telomeres. In addition, inheritance of only the missense mutation led to very short telomeres in the proband’s brother. Targeted sequencing identified a different RTEL1 missense mutation in one additional DC proband who has bone marrow failure and short telomeres. Both missense mutations affect the helicase domain of RTEL1, and three in silico prediction algorithms suggest that they are likely deleterious. The nonsense mutations both cause truncation of the RTEL1 protein, resulting in loss of the PIP box this may abrogate an important protein–protein interaction. These findings implicate a new telomere biology gene, RTEL1, in the etiology of DC.

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Telomere extension turns back aging clock in cultured human cells, study finds

Researchers delivered a modified RNA that encodes a telomere-extending protein to cultured human cells. Cell proliferation capacity was dramatically increased, yielding large numbers of cells for study.

A new procedure can quickly and efficiently increase the length of human telomeres, the protective caps on the ends of chromosomes that are linked to aging and disease, according to scientists at the Stanford University School of Medicine.

Treated cells behave as if they are much younger than untreated cells, multiplying with abandon in the laboratory dish rather than stagnating or dying.

The procedure, which involves the use of a modified type of RNA, will improve the ability of researchers to generate large numbers of cells for study or drug development, the scientists say. Skin cells with telomeres lengthened by the procedure were able to divide up to 40 more times than untreated cells. The research may point to new ways to treat diseases caused by shortened telomeres.

Telomeres are the protective caps on the ends of the strands of DNA called chromosomes, which house our genomes. In young humans, telomeres are about 8,000-10,000 nucleotides long. They shorten with each cell division, however, and when they reach a critical length the cell stops dividing or dies. This internal “clock” makes it difficult to keep most cells growing in a laboratory for more than a few cell doublings.

‘Turning back the internal clock’

“Now we have found a way to lengthen human telomeres by as much as 1,000 nucleotides, turning back the internal clock in these cells by the equivalent of many years of human life,” said Helen Blau, PhD, professor of microbiology and immunology at Stanford and director of the university’s Baxter Laboratory for Stem Cell Biology. “This greatly increases the number of cells available for studies such as drug testing or disease modeling.”

A paper describing the research was published today in the FASEB Journal. Blau, who also holds the Donald E. and Delia B. Baxter Professorship, is the senior author. Postdoctoral scholar John Ramunas, PhD, of Stanford shares lead authorship with Eduard Yakubov, PhD, of the Houston Methodist Research Institute.

The researchers used modified messenger RNA to extend the telomeres. RNA carries instructions from genes in the DNA to the cell’s protein-making factories. The RNA used in this experiment contained the coding sequence for TERT, the active component of a naturally occurring enzyme called telomerase. Telomerase is expressed by stem cells, including those that give rise to sperm and egg cells, to ensure that the telomeres of these cells stay in tip-top shape for the next generation. Most other types of cells, however, express very low levels of telomerase.

Transient effect an advantage

The newly developed technique has an important advantage over other potential methods: It’s temporary. The modified RNA is designed to reduce the cell's immune response to the treatment and allow the TERT-encoding message to stick around a bit longer than an unmodified message would. But it dissipates and is gone within about 48 hours. After that time, the newly lengthened telomeres begin to progressively shorten again with each cell division.

The transient effect is somewhat like tapping the gas pedal in one of a fleet of cars coasting slowly to a stop. The car with the extra surge of energy will go farther than its peers, but it will still come to an eventual halt when its forward momentum is spent. On a biological level, this means the treated cells don’t go on to divide indefinitely, which would make them too dangerous to use as a potential therapy in humans because of the risk of cancer.

The researchers found that as few as three applications of the modified RNA over a period of a few days could significantly increase the length of the telomeres in cultured human muscle and skin cells. A 1,000-nucleotide addition represents a more than 10 percent increase in the length of the telomeres. These cells divided many more times in the culture dish than did untreated cells: about 28 more times for the skin cells, and about three more times for the muscle cells.

“We were surprised and pleased that modified TERT mRNA worked, because TERT is highly regulated and must bind to another component of telomerase,” said Ramunas. “Previous attempts to deliver mRNA-encoding TERT caused an immune response against telomerase, which could be deleterious. In contrast, our technique is nonimmunogenic. Existing transient methods of extending telomeres act slowly, whereas our method acts over just a few days to reverse telomere shortening that occurs over more than a decade of normal aging. This suggests that a treatment using our method could be brief and infrequent.”

Potential uses for therapy

“This new approach paves the way toward preventing or treating diseases of aging,” said Blau. “There are also highly debilitating genetic diseases associated with telomere shortening that could benefit from such a potential treatment.”

Blau and her colleagues became interested in telomeres when previous work in her lab showed that the muscle stem cells of boys with Duchenne muscular dystrophy had telomeres that were much shorter than those of boys without the disease. This finding not only has implications for understanding how the cells function — or don’t function — in making new muscle, but it also helps explain the limited ability to grow affected cells in the laboratory for study.

The researchers are now testing their new technique in other types of cells.

“This study is a first step toward the development of telomere extension to improve cell therapies and to possibly treat disorders of accelerated aging in humans,” said John Cooke, MD, PhD. Cooke, a co-author of the study, formerly was a professor of cardiovascular medicine at Stanford. He is now chair of cardiovascular sciences at the Houston Methodist Research Institute.

“We’re working to understand more about the differences among cell types, and how we can overcome those differences to allow this approach to be more universally useful,” said Blau, who also is a member of the Stanford Institute for Stem Cell Biology and Regenerative Medicine.

“One day it may be possible to target muscle stem cells in a patient with Duchenne muscular dystrophy, for example, to extend their telomeres. There are also implications for treating conditions of aging, such as diabetes and heart disease. This has really opened the doors to consider all types of potential uses of this therapy.”

Other Stanford co-authors of the paper are postdoctoral scholars Jennifer Brady, PhD, and Moritz Brandt, MD senior research scientist Stéphane Corbel, PhD research associate Colin Holbrook and Juan Santiago, PhD, professor of mechanical engineering.

The work was supported by the National Institutes of Health (grants R01AR063963, U01HL100397 U01HL099997 and AG044815), Germany’s Federal Ministry of Education and Research, Stanford Bio-X and the Baxter Foundation.

Ramunas, Yakubov, Cooke and Blau are inventors on patents for the use of modified RNA for telomere extension.


Based on our findings that 9 of 19 ESCRT genes are significantly enriched within the subset of short tlm mutants (with a P value of 8.84E�, Fisher’s exact test) ( Fig.ꀚ ), we examined the entire ESCRT family for its involvement in telomere length maintenance. To this end, we (i) analyzed protein-protein interaction (PPI) data and (ii) investigated the telomeric system in the context of single ESCRT gene deletions.

ESCRT genes are involved in telomere length maintenance. (A) Venn diagram depicting the overlap of ESCRT genes and short tlm mutants, whose P value (P) was calculated with a Fisher’s exact test. The set sizes are given per set, and the total number of genes that were considered for this test is stated as U (reference set size). (B) A traverse protein is defined as a protein that links two other proteins in the protein-protein interaction network. To reach protein C from A (or vice versa), protein B has to be traversed. (C) Matrix of shortest-path distances, given as the number of traverse proteins, between members of the ESCRT family (columns) and central telomere proteins (rows). Shortest-path investigation was done using the igraph library of program R. Boldface marks members of the ESCRT family whose corresponding mutants showed shortened telomeres.

In order to gain insight into the connections of telomere-related proteins and the ESCRT family, we explored a manually curated Saccharomyces cerevisiae PPI network (5,592 proteins and 28,581 interactions). This network consisted exclusively of experimentally verified binary PPIs, rendering it a highly reliable interaction source (compiled analogously to the human interactome in Chapple et al. [14]). We defined a set of central telomere proteins (CTPs) (5, 6), consisting of all subunits of the CST (Cdc13, Stn1, and Ten1) capping complex, the Ku complex (Yku70 and Yku80), the MRX complex (Mre11, Rad50, and Xrs2), and the proteins Rif1, Rif2, Rap1, Exo1, Est1, Est2, Tel1, and Mec1. These proteins are part of the basic machinery involved in telomere length maintenance. We then carried out a shortest-path analysis, measuring the distances between ESCRT components and CTPs within the PPI network. Our results revealed that most ESCRT components were connected by at least two in-between (traverse) ( Fig.ꀛ ) proteins to CTP members ( Fig.ꀜ ). Remarkably, however, six ESCRT factors had a distance of only one traverse protein to a central telomere protein. Figure S1 in the supplemental material shows the induced subnetwork for all of those PPIs (31 proteins and 64 interactions). Interestingly, Cdc13 and the ESCRT-0 complex, especially Vps27, form a dense subnetwork whose traverse proteins are all protein kinases (see Fig. S1, orange). This analysis therefore suggests a strong association of ESCRT-0 to the telomeric system via Cdc13. We thus decided to utilize VPS27 for a further in-depth investigation of the link between telomere shortening and the ESCRT machinery.

Initially, we measured telomere length after at least 150 generations (six serial restreaks) by telomere PCR (15) for different telomeres (Y'-containing telomeres and telomere 1L) in wild-type and Δvps27 cells. Figureꀪ shows the gel quantification for the telomere PCR, and Fig.ꀫ a representative Southern blot to measure telomere lengths for Y' telomeres only. The shortening of telomeres in Δvps27 cells was striking, as previously reported (5, 16). As telomere length in budding yeast is primarily maintained by telomerase, we explored whether the loss of telomerase function affected the same pathway as that impaired in Δvps27 cells. We deleted the EST2 gene, encoding the catalytic subunit of telomerase, and recorded the growth potential of cells (relative cell density) and the corresponding telomere-shortening rate in cells with or without the deletion of the VPS27 gene. Due to their lack of telomerase-dependent telomere elongation, 㥎st2 mutants senesce after a certain number of passages rare survivors appear later and take over the population. We found that the onset of senescence in 㥎st2 Δvps27 double mutants was similar to that seen in the single 㥎st2 mutants ( Fig.ꀬ ) and that the rates of telomere shortening were comparable in both mutants ( Fig.ꀭ ). We thus conclude that the telomere shortening in Δvps27 cells is due to an effect on a telomerase-mediated mechanism.

Telomerase-dependent telomere elongation is disturbed in vps27 mutants. (A) Telomere length was measured by telomere PCR for wild-type and Δvps27 cells after growth to at least 150 generations (six serial restreaks). Length was examined for six Y' telomeres and the 1L telomere. Horizontal bars represent the medians of the respective data points. (B) Representative Southern blot that could be used to measure Y' telomere lengths in wild-type and Δvps27 cells. (C) Senescence curves of 㥎st2 single and 㥎st2 Δvps27 double mutants. For each mutant type, senescence was recorded for six different spore colonies (n = 6). Error bars represent the standard errors of the means. Two fragments, 2044 and 779 bp long, serve as size markers in telomere Southern blots. (D) Relative base pair loss of six Y' telomeres, as well as the 1L telomere, in 㥎st2 single and 㥎st2 Δvps27 double mutants. Days 1 to 5 correspond to the first five time points of the senescence curve in panel C. Relative base pair loss was calculated as the ratio of the number of base pairs on day x to the number of base pairs on day 1. The average relative base pair loss in three tetrads (n = 3) per day is shown. Error bars indicate means ± standard deviations. Figure S3 in the supplemental material shows the individual data averaged in panel D.

In order to further confirm a defect in telomerase-mediated elongation in 㥎SCRT mutants, we took advantage of previous work, which demonstrated that the exposure of cells to ethanol stress leads to increased telomere elongation via telomerase (17). We measured telomere length by Southern blot analysis in wild-type cells and 㥎SCRT mutants exposed to ethanol (5% ethanol in liquid glucose-based YP medium) over 60 generations. The average telomere length was calculated using TelQuant (18). As expected, 㥎SCRT mutants exhibited shorter telomeres than wild-type cells. Moreover, 㥎SCRT mutants showed a weaker response to ethanol than the wild-type cells in terms of telomere elongation, with Δvps27, Δstp22, and Δsnf8 mutants exhibiting the strongest effects ( Fig.ꀺ and ​ andB B see also Fig. S2 in the supplemental material). This observation suggests that the entire ESCRT family is involved in telomerase-dependent elongation and that it is required for normal telomere maintenance, as well as for the physiological response to external signals.

Decreased elongation rates of 㥎SCRT mutants in response to ethanol stress. (A) Telomere length was measured by TelQuant (18). Standard deviations, as well as values for individual measurements (grey circles), are shown. The elongation rate was calculated as the difference between the final telomere length (after exposure to 5% ethanol over 60 generations) and the initial telomere length (before applying ethanol stress), divided by the initial length of each strain. Afterward, the elongation rate was normalized to the wild-type elongation rate, which was taken as one. (B) Southern blot showing wild-type and Δsnf8 mutant telomere lengths before (−) and after (+) exposure to ethanol (EtOH) stress (5% ethanol in standard YP medium) of three independent cultures each.

A bioinformatics analysis of gene expression in 㥎SCRT deletion mutants did not reveal dramatic changes in the expression of telomere-related genes. Given the strong connectivity of Vps27 to Cdc13 in the protein-protein interaction network reported above, we investigated this link in further detail. Cdc13 is the major telomere ssDNA binding protein in yeast and regulates the access of telomerase to the chromosomal ends (19). Depending on the cell cycle stage, Cdc13 is bound to the telomere in different complexes. Either it is bound to the telomeric overhang as a member of the CST capping complex or it interacts with Est1 to promote telomerase recruitment (19). Est1 is a subunit of the telomerase ribonucleoprotein complex and is important for in vivo telomerase activity at telomeres (20). We forced telomerase to be tethered to the telomeric overhang by using a Cdc13-Est1 fusion protein, resulting in vigorous telomere elongation in wild-type cells. This fusion protein can be used to distinguish between defective telomerase recruitment and malfunctioning telomerase activation, although it does require the correct generation of a G overhang, which provides a Cdc13 binding site. If the absence of the ESCRT subunits impairs telomere elongation due to reduced telomerase recruitment, tethering telomerase to the telomere by expressing the Cdc13-Est1 fusion may bypass the problem and lead to wild-type telomere elongation. If, on the other hand, telomerase activity itself is impaired in the absence of ESCRT subunits, telomere elongation will be still reduced in the presence of the Cdc13-Est1 fusion protein. We expressed this fusion protein in six 㥎SCRT mutants (Δvps27, Δsnf8, Δvps20, Δsnf7, 㥍id4, and 㥍oa4 mutants) and evaluated the kinetics of telomere elongation. We observed that in comparison to that in wild-type cells, telomere elongation was reduced in all mutants, despite the 𠇏orced” recruitment ( Fig.਄ ). These data suggest that in 㥎SCRT mutants, either the activity of telomerase is compromised or the G overhang is not properly regulated, in turn preventing telomerase recruitment even when it is forced to be present at telomeres.

Reduced telomere elongation in 㥎SCRT mutants despite forced telomerase recruitment. Kinetics of telomere elongation for mutants with the 㥎SCRT mutations shown and the wild type. Strains carrying plasmids expressing the Cdc13-Est1 fusion protein (or an empty vector control) were streaked on –LEU plates for eight passages. On the indicated days, DNA was extracted, digested with XhoI, and analyzed by Southern blotting. Days 4, 8, 12, and 16 correspond to passages 2, 4, 6, and 8. Error bars indicate means ± standard deviations.

We set out to test whether end resection and, hence, G tail formation is affected in Δvps27 mutants. Using cdc13-1, a temperature-sensitive allele of CDC13, telomere uncapping can be induced by changing temperatures. After shifting cdc13-1 cells to their nonpermissive temperature (㸧ଌ), telomeres become uncapped and extensively long G overhangs are generated in a nuclease-dependent manner, resulting in a checkpoint-mediated cell cycle arrest. Indeed, when nucleases like Exo1 are deleted in cdc13-1 cells, the cells are viable even at temperatures above 27ଌ. We examined cdc13-1 Δvps27 double mutants for their viability at the permissive (23ଌ and 25ଌ) and nonpermissive (27ଌ and 28ଌ) temperatures. Deleting VPS27 allowed the growth of cdc13-1 cells at elevated temperatures ( Fig.ꁚ ). This finding is in agreement with the results of Addinall et al., who reported that a deletion of HSE1 (a Vps27 interactor) suppresses the temperature sensitivity of cdc13-1 (21). Hence, the deletion of ESCRT-0 seems to protect the cells from uncapped telomeres. This finding holds true for almost all ESCRT gene deletions (see Fig. S3 in the supplemental material).

Deletion of VPS27 rescues cdc13-1 capping-defective telomeres. (A) Cells with the indicated genotypes were spotted in 10-fold serial dilutions onto standard YPD plates and incubated at different temperatures for 3ꃚys. Two biological replicates are shown (N1 and N2). (B) Boxplot showing the amount of telomeric overhang for cdc13-1 single and cdc13-1 Δvps27 double mutants at permissive temperature (in green) and after heat-shock treatment (1 h at 30ଌ in blue). Green dots indicate the individual data points. (C) As described for the experiment whose results are shown in panel A, the indicated mutants were spotted onto plates containing the indicated media. Cells contained either an Exo1 overexpression plasmid (OE) or the corresponding vector control (empty vector [EV]). Exo1 overexpression was induced by growth on galactose-containing plates. Plates were incubated at the indicated temperatures for 3ꃚys. SD-Leu, yeast synthetic dropout medium without leucine (control) SGalRaf-Leu, SD-Leu medium containing 1% raffinose and 2% galactose.

Both reduced Exo1-mediated resection and/or defective cell cycle checkpoint activation could potentially account for the increased growth of cdc13-1 cells at elevated temperature. First, we explored whether the deletion of VPS27 influences Exo1-mediated resection. Degradation of the 5′ end of uncapped telomeres leads to increased amounts of 3′ telomeric single-stranded overhang. We measured the amount of telomeric ssDNA in cdc13-1 and cdc13-1 Δvps27 cells at 23ଌ or after 1 h of incubation at 30ଌ to induce telomere uncapping. As expected, we saw elevated levels of 3′ ssDNA in cdc13-1 cells at high temperature using a dot blot approach under native and denaturing conditions ( Fig.ꁛ see also Fig. S4 in the supplemental material). The amount of 3′ telomeric overhang was decreased in the double mutant at both temperatures ( Fig.ꁛ ). This observation suggests a compromised Exo1-mediated resection in cdc13-1 Δvps27 double mutants. In addition, overexpression of Exo1 in cdc13-1 Δvps27 cells (but not an empty vector) abolished the rescue effect ( Fig.ꁜ ), supporting the idea of a defective Exo1-mediated resection upon VPS27 deletion. In order to test whether Δvps27 mutants may have lower expression of EXO1, we assessed the protein levels of Exo1 in Δvps27 single mutants and cdc13-1 Δvps27 double mutants compared to the levels in wild-type cells after the induction of telomere uncapping by transfer to high temperature (1 h at 30ଌ). We also examined the degradation kinetics of Exo1 in the double mutants using cycloheximide chase experiments. The Exo1 levels were not altered by the deletion of VPS27, and there were no apparent differences in Exo1 protein degradation kinetics between cdc13-1 and cdc13-1 Δvps27 mutants. Together, these results suggest that the rescue of cdc13-1 cells by the deletion of ESCRT components may be due to impaired resection of the telomere, although differences in EXO1 expression cannot be held accountable.

Other than a defective Exo1-mediated resection, improper DNA damage checkpoint activation could also explain the apparent rescue of cdc13-1 capping-defective telomeres. An up-down assay ( Fig.ꁪ ) was previously developed in which cells are subjected to cycles of high and low temperature (21). As the temperature sensitivity of cdc13-1 mutants is reversible, the cells can maintain viability upon short exposures to the nonpermissive temperature if returned to permissive temperature afterward. Mutants defective for the DNA damage checkpoint activation fail to arrest in response to DNA damage, and recovery is not possible (21). Under these conditions, mutations in EXO1 suppress cdc13-1 defects, whereas a deletion of the RAD9 checkpoint gene is unable to do so (21). The results in Fig.ꁫ show that the cdc13-1 Δvps27 mutants were viable in this assay, in contrast to checkpoint-defective Δrad9 cells, indicating that checkpoint activation is normal in the absence of VPS27.

cdc13-1 Δvps27 double mutants are viable in a up-down assay. (A) Schematic of the up-down assay employed. Cells were incubated at permissive temperature (23ଌ) for 5 h, followed by a phase of nonpermissive temperature (36ଌ) for 5 h. After three cycles, plates were kept on hold at 23ଌ. (B) Cells were spotted in 10-fold serial dilutions onto standard YPD plates that were incubated at oscillating temperatures for 3ꃚys. Two biological replicates were spotted. Controls were incubated at 23ଌ.

Human ageing reversed in ‘Holy Grail’ study, scientists say

Scientists claim to have successfully reversed the biological ageing process in a group of elderly adults.

In a first of a kind study, researchers from Tel Aviv University and the Shamir Medical Center used a form of oxygen therapy to reverse two key indicators of biological ageing: Telomere length and senescent cells accumulation.

As the human body gets older, it experiences the shortening of telomeres – the protective caps found at the end of chromosomes – and an increase in old, malfunctioning senescent cells.

A clinical trial involving 35 adults over the age of 64 sought to understand whether a method called Hyperbaric Oxygen Therapy could prevent the deterioration of these two hallmarks of the ageing process.

The subjects were placed in a pressurised chamber and given pure oxygen for 90 minutes a day, five days a week for three months.

At the end of the trial, the scientists reported that the participants’ telomeres had increased in length by an average of 20 per cent, while their senescent cells had been reduced by up to 37 per cent.

This is the equivalent to how their bodies were at a cellular level 25 years earlier, the researchers reported.

“Since telomere shortening is considered the ‘Holy Grail’ of the biology of ageing, many pharmacological and environmental interventions are being extensively explored in the hopes of enabling telomere elongation,” said Shai Efrati, a professor at the Faculty of Medicine and Sagol School of Neuroscience at Tel Aviv University, and co-author of the study.

“The significant improvement of telomere length shown during and after these unique HBOT protocols provides the scientific community with a new foundation of understanding that ageing can, indeed, be targeted and reversed at the basic cellular-biological level.”


It is the latest in a series of radical anti-ageing treatments, which seek to increase life expectancy and even make people look and feel younger.

The idea is that ageing is a disease that can be cured just like any other.

In 2015, the head of a biotech company made headlines after becoming patient zero in a novel gene therapy she claimed could make permanent changes to her DNA in order to combat muscle loss and other age-related conditions.

BioViva chief executive Liz Parrish received criticism from scientists for her experimental drug trial but claims to have increased the length of her telomeres in the five years since and recently claimed that death is optional.

During the latest trial in Israel, the participants did not undergo any lifestyle, diet or medication adjustments, which have previously been found to have moderate effects on a person’s biological age.

It is understood that instead the effects were the result of the pressurised chamber inducing a state of hyperoxia, or high-levels of oxygen in the blood, which caused the cell regeneration.

“Until now, interventions such as lifestyle modifications and intense exercise were shown to have some inhibition effect on the expected telomere length shortening,” said Dr Amir Hadanny, co-author of the study.

“However, what is remarkable to note in our study, is that in just three months of therapy, we were able to achieve such significant telomere elongation – at rates far beyond any of the current available interventions or lifestyle modifications.”

Recombinational Telomere Elongation Promoted by DNA Circles

FIG. 1 . Repeating structure within telomeres of ter1-Δ survivors. (A) Strategy for construction of ter1-Δ strains with two types of telomeric repeats. The ter1-Δ strain with wild-type telomeric repeats at the base and Bcl telomeric repeats at the tips was derived by forming a ter1-Δ/TER1-Bcl heteroallele. Plating on 5-FOA selected for cells that had looped out either the TER1-Bcl allele or the ter1-Δ allele. Clones containing only the ter1-Δ allele were identified by their senescent rough colony phenotype. (B) Classes of outcomes observed in postsenescence survivors derived from ter1-Δ strains with wild-type and Bcl repeats. Light gray boxes indicate wild-type repeats, dark gray boxes indicate Bcl repeats, and white boxes indicate partial repeats not distinguishable as either wild-type or Bcl. Thin lines represent subtelomeric sequence. Telomere structures shown for outcomes 1 and 2 are approximate based upon BclI restriction digestion and not sequencing. Telomere structures for outcome 3 are cloned and sequenced examples of recombinationally elongated telomeres from three independent postsenescence survivors. There is no sequence variation from wild-type telomeric repeats in the cloned telomeres except for the position that is expected to create a BclI restriction site. (C) Southern blot, hybridized with a telomeric probe, of a senescent ter1-Δ strain (lane Δ) and 11 postsenescence survivors derived from it that retained Bcl repeats (lanes 1 to 11). Pairs of lanes show DNA from individual survivors digested with EcoRI and EcoRI-BclI. Among the 12 telomeres, subtelomeric EcoRI sites are present ∼1 to 3.5 kb from telomeric ends. The double digest yields blocks of wild-type repeats. The lower panel shows these blocks resolved on a 4% NuSieve agarose gel. Size markers for both panels are indicated. Cloned telomeres in panel B (1a, 1b, and 1c and 3a, 3b, and 3c) came from clones 1 and 3, respectively, of panel C. Cloned telomere 12a of panel B was isolated from a clone not shown in panel C. FIG. 2 . Long tandem arrays formed at telomeres after transformation with a DNA circle containing URA3 and telomeric repeats. (A) Southern blot, hybridized with a subtelomeric probe, of EcoRI-digested DNA from wild-type TER1 (WT) and ter1-Δ (Δ) strains untransformed (lanes 1 and 2) and after transformation (lanes 3 to 6) with a 1.6-kb URA3-telomere circle. (B) Same filter as in panel A after stripping and reprobing with a URA3 probe. (C) Southern blot, hybridized to a telomeric probe, of uncut genomic DNA from TER1 (WT) and ter1-Δ (Δ) strains transformed with the 1.6-kb URA3-telomere circle. Transformants shown are the same as those shown in panels A and B. (D) Southern blot, hybridized with a URA3 probe, of EcoRV-digested DNA from wild-type TER1 (WT) and ter1-Δ (Δ) strains untransformed (lanes 1 and 2) and after transformation (lanes 3 to 6) with a 1.6-kb URA3-telomere circle. (E) Diagram of 1.6-kb URA3-telomere circle transformation and structures of single and multiple tandem inserts and a telomere. Gray boxes indicate blocks of telomeric repeats, black boxes indicate URA3, white boxes indicate a short subtelomeric sequence present on DNA circles, and stippled boxes indicate subtelomeric sequence used as a probe in panel A and not present on the circles. Subtelomeric EcoRI sites are 1 to 3.5 kb from telomeric ends in untransformed K. lactis cells. Positions of EcoRI sites(RI) and EcoRV (RV) sites are indicated. Abbreviations: J, centromere-proximal junction fragment T, telomeric fragment. FIG. 3 . Transformation with two species of circle produces arrays derived from only one species. (A) Diagram of telomere structures before and after introduction of a mixture of two species of 1.6-kb URA3-telomere circles that differ only by a single restriction site. Gray and black boxes are blocks of telomeric repeats and URA3, respectively. White boxes are subtelomeric sequence present on DNA circles, and stippled boxes are subtelomeric sequence not present on the circles. Abbreviations: R, S, and P, sites for EcoRI, SalI, and PvuI, respectively S/P, sites that will either be SalI or PvuI depending upon which circle the site is derived from J and T, junction fragment with subtelomeric sequences and terminal telomeric fragment, respectively. (B) Southern blots of representative clones of TER1 (top) and ter1-Δ (bottom) transformed with either circle S or circle P are shown hybridized with subtelomere, URA3, or telomeric probe, as indicated. Untransformed control is shown digested with EcoRI, and transformants are shown digested with EcoRI (-), EcoRI-SalI (S), or EcoRI-PvuI (P). The type of transforming circle used is indicated on top. A faint band at 3.2 kb in URA3-probed lanes containing the dark 1.6-kb fragment are trace partials left over from cleaving the tandem arrays. Positions of molecular weight markers (in kilobase pairs) are indicated. (C) Southern blots of two representative clones each of TER1 (top) and ter1-Δ (bottom) transformed with both circle S and circle P are shown hybridized with subtelomere, URA3, or telomeric probe, as indicated. The two clones represent one example each of clones exhibiting tandem arrays of either an S version or a P version. Digests were done as for panel B. (B and C) Junction fragments (J) are marked with arrows in the URA3. FIG. 4 . URA3-telomere circle transformation into rad52 and RAD52 strains. Photographs show sections of plates with Ura + transformants. Equal amounts of both the URA3-telomere (Tel.) circle and the autonomously replicating ARS plasmid control were used for both strains. FIG. 5 . Long tandem arrays at telomeres can be formed in a TER1 rad52 strain transformed with a URA3-telomere circle. Shown is a Southern blot of untransformed control (C) and three rad52 clones transformed with a URA3-telomere circle. The untransformed control is shown digested with EcoRI, and the transformed clones are shown digested with EcoRI and EcoRI-PvuI, as indicated. The same filter is shown hybridized with subtelomeric, URA3, and telomeric probes. Faint bands at 1.6 kb in EcoRI-PvuI-digested samples hybridized with the subtelomeric sequence are residual signal from prior URA3 hybridization. Size markers (in kilobases) are shown at left. FIG. 6 . Roll-and-spread model. The formation of one long telomere is postulated to occur via a rolling-circle gene conversion, copying either the 1.6-kb circle (circle transformants) or a very small telomeric circle (ter1-Δ survivors). The inset depicts a telomeric end processed to have a 3′ single strand overhang (shaded thin boxes) that strand invade a telomeric circle. In ter1-Δ cells, the very high rate of telomeric gene conversion can spread sequence from one long telomere onto many or all other telomeres of the cell under selective pressure for postsenescence survivors. The net result is that a common pattern is present in most or all of the elongated telomeres.


The telomerase components TERT and TERC can be reliably detected using RNAscope

We chose to work with HeLa cells as a model system as they represent one of the few cell lines where telomerase dynamics have been previously assessed at the single cell level. Single cell cloning experiments suggested that significant heterogeneity exists both in terms of telomere length and telomerase activity within a HeLa population with stable mean overall telomere length [23]. Furthermore, a recent study using a TRAP assay variant based on droplet PCR suggested that

30% of HeLa cells lack TRAP activity [16], and we have reported that the majority of telomere elongation in HeLa cells occurs within a small subset of cells [17]. Together, these results suggest that there is significant heterogeneity in both telomere length and telomerase activity within individual cells of a HeLa population, but the regulatory mechanisms underlying this heterogeneity are uncertain.

We hypothesized that the heterogeneous telomere elongation patterns seen in HeLa cells in our previous work would be driven at least in part by heterogeneous TERT expression. To assess TERT expression, we used RNAscope in situ hybridization detection [18, 24]. By employing extensive signal amplification, this proprietary technique enables detection of mRNA at the single molecule level.

To validate RNAscope detection of telomerase components, we first tested RNAscope probes for TERC and TERT in control HeLa cells and in HeLa cells overexpressing TERT (HeLa TERT) and/or mutant TSQ1 TERC (HeLa TSQ1 HeLa TERT TSQ1). Consistent with published data demonstrating that TERC is ubiquitously expressed while TERT levels are typically rate limiting [5𠄷, 14], TERC expression was much higher than TERT expression in the control HeLa cell population ( Fig 1 ). TERT expression was both low and heterogeneous, with approximately 30% of cells negative for TERT RNAscope. When either telomerase component was exogenously overexpressed, the RNAscope assay showed a corresponding increase in signal intensity. In each case, “vec” refers to the empty vector control for TSQ1 infection. The subcellular localization of the two telomerase components differed, with TERT mRNA detected in both nucleus and cytoplasm and TERC RNA predominantly seen in the nucleus. Taken together, these results demonstrate that RNAscope enables sensitive detection of both TERC and TERT in individual cells of a heterogeneous population. To further confirm the specificity of the RNAscope assay, we analyzed TERT expression in two cancer cell lines known to express telomerase (LOX and HCT116) [17, 25] and two fibroblast cell lines known to be telomerase negative (WI38 and MRC5) [26, 27]. Robust RNAscope TERT signal was observed in the cancer cell lines, while only extremely rare RNAscope TERT spots were seen in the fibroblast cell lines ( Fig 2A and 2B ).

A. Representative images showing HeLa cells and HeLa cells overexpressing TERT (HeLa TERT), stained for TERT mRNA and TERC. Each of these cell types was infected with a lentiviral plasmid expressing the TSQ1 mutant TERC or a vector control (vec). Scale bars denote 10μM. B. qPCR to measure TERT and TERC expression in HeLa vec, HeLa TSQ1, HeLa TERT vec and HeLa TERT TSQ1 cells. In each case, levels are expressed as fold change over control HeLa vec levels. C. Frequency distribution of RNAscope TERT foci in populations of HeLa and HeLa TERT cells. The data is from 3 sets of biological replicates containing 100 cells each for either cell type.

A. RNAscope for TERT expression in telomerase negative (MRC5 and WI38 fibroblast) and positive (HCT116 and LOX) cell lines. B. Frequency distribution of TERT RNAscope signals within populations of MRC5, WI38, HCT 116 and LOX cells. The data is from 3 sets of biological replicates each containing 100 cells for all cell types. Scale bars denote 10μM.

To rule out that detection of genomic DNA, rather than mRNA transcripts, contributed to the nuclear TERT RNAscope signal, we ran the TERT RNAscope assay after RNAse-treating HeLa TERT cells post-fixation. RNAse treatment completely eliminated the TERT RNAscope signal, indicating that the RNAscope spots represent mRNA rather than genomic DNA (S1A Fig). Finally, since our ultimate goal was to combine TERT detection and PNA-FISH, we tested whether the brown RNAscope diaminobenzidine (DAB) reaction product was stable through the PNA-FISH protocol. We performed TERT RNAscope on HeLa TERT cells, imaged them in bright-field and subsequently performed PNA-FISH on the same slides. As shown in S1B Fig, the DAB reaction product is stable through the PNA-FISH procedure, although the hematoxylin staining intensity is reduced substantially post PNA-FISH.

Combining RNAscope and PNA-FISH TSQ1 analysis enables detection of TERT expression, telomere length, and telomere elongation in single cells

The observed heterogeneity of TERT RNA in HeLa cells parallels the heterogeneity of telomere elongation previously reported by our laboratory [17], suggesting that TERT levels may be an underlying driver of heterogeneous telomerase activity across the population. To test this hypothesis, we developed a combined RNAscope TSQ1 assay. In brief, TSQ1 TERC is overexpressed in HeLa or HeLa TERT cells for 5𠄷 days, after which RNAscope detection of TERT transcripts followed by fluorescence in situ hybridization detection of wild-type telomeric sequence (TTAGGG repeats) and TSQ1 telomeric sequence (TTGCGG) is performed. Subsequent brightfield and fluorescence imaging enables single cell detection of TERT mRNA (RNAscope spots in brightfield), telomere length (wild-type telomere fluorescence signal), and telomere elongation (TSQ1 telomere fluorescence signal). Representative images from the combined RNAscope/TSQ1 assay are shown in Fig 3 , with additional images shown in S2 Fig. Incorporation of TSQ1 telomeric repeats, which reflects telomere elongation by telomerase, can be seen in both HeLa and HeLa TERT cells, but the degree of TSQ1 incorporation is much greater in the HeLa TERT cells ( Fig 4 ). Altogether, 93% of HeLa TERT cells are positive for TSQ1 incorporation versus 44% of HeLa cells. Additionally, there are 4-fold more TSQ1 spots per TSQ1-positive cell in HeLa TERT cells versus HeLa cells (pπ.0001 Mann-Whitney test). In all, 171 cells from at least two independent experiments were assayed for each cell type to determine these data. Importantly, almost every cell treated with the TSQ1-expressing virus shows marked TERC overexpression relative to control (S3 Fig).

Cells were assayed 7 days post-TSQ1 or vector infection. They were imaged via fluorescence for wild-type telomere (green) and TSQ1 (red) signal and then bright-field for the brown TERT DAB reaction product. TSQ1 spots co-localizing at telomeres are marked with arrows. Representative images are shown and scale bars denote 10μM.

Swarm plots showing the number of TSQ1 spots co-localizing with telomeres in HeLa cells and HeLa cells overexpressing TERT. 171 cells from at least 2 separate experiments were assayed for each group. Means (horizontal black lines) and SEM (red lines) are shown for each population. P values (Mann-Whitney test) are provided and significant differences are marked with asterisks.

We further observed that some HeLa cells that express TERT show TSQ1 incorporation ( Fig 5A , upper panels), while other cells show significant levels of RNAscope TERT signal but no detectable TSQ1 incorporation ( Fig 5A , lower panels). Across the entire HeLa cell population, a weak but statistically significant correlation is seen between TSQ1 incorporation and RNAscope TERT levels (Spearman r = 0.275 p < 0.003) ( Fig 5B , left panel), demonstrating that variable TERT expression is one determinant of the heterogeneous telomere elongation pattern observed in a HeLa cell population. However, a significant number of cells with TERT expression that is low or undetectable by RNAscope nevertheless shows robust TSQ1 incorporation at the telomeres, while many cells with multiple RNAscope TERT spots lack detectable TSQ1 incorporation. The presence of such cells strongly suggests that regulatory mechanisms other than TERT expression level also regulate the extent of telomerase function in individual cells of the population.

A. Representative images of HeLa cells with robust TERT expression and either robust TSQ1 incorporation (upper panel of images) or no TSQ1 incorporation (lower panel of images). Arrows indicate TSQ1 spots that co-localize with telomeres. Enlarged images of the boxed regions are in the lower right-hand corner of each corresponding image. Scale bars denote 10μM. B Scatter plot demonstrating the correlation between TSQ1 incorporation and TERT expression in HeLa (left panel) and HeLa POT1-ΔOB cells (right panel). 171 cells from at least 2 separate experiments were assayed for each group. C. Swarm plots showing number of TSQ1 spots co-localizing with telomeres (left panel) and RNAscope TERT expression (right panel) in HeLa cells and HeLa cells overexpressing POT1-ΔOB. 171 cells from at least 2 separate experiments were assayed for each group. Means (horizontal black lines) and SEM (red lines) are shown for each population. P values are provided and significant differences are marked with asterisks, with ns denoting a non-significant difference. Of note, the HeLa cells quantified in this figure are the same as the cohort shown in Fig 4 .

The absence of detectable telomere elongation in many of the TERT-positive cells may be due to negative regulation of telomerase activity. Several shelterin components have been implicated as negative regulators of telomere elongation [28], and overexpression of a mutant form of POT1 lacking the OB fold domain (POT1-ΔOB) disrupts this negative regulation and induces telomere elongation [29]. We tested the role of shelterin regulation by performing combined RNAscope/TSQ1 analysis in HeLa cells overexpressing POT1-ΔOB, in parallel with the HeLa cell experiment described in the paragraph above.

POT1-ΔOB overexpression induced bulk telomere lengthening as measured by Southern blot (S4 Fig), confirming its expected impact on telomere length regulation. Just like the control HeLa cells, the HeLa cells with POT1-ΔOB overexpression ( Fig 5B ., right panel) demonstrate a weak but statistically significant positive correlation between TERT expression as measured by RNAscope spot number and telomere elongation as measured by TSQ1 spot number. However, the average number of TSQ1 spots increased from 5.7 in HeLa cells to 9.4 in HeLa cells overexpressing POT1-ΔOB (p = 0.0013 Mann-Whitney test). This increase in TSQ1 incorporation was not the result of increased TERT expression, as the level of TERT RNAscope signal did not significantly differ (p = 0.8881 Mann-Whitney Test) between HeLa and HeLa POT1-ΔOB cells ( Fig 5C , right panel). Altogether, this result suggests that the lack of robust TSQ1 incorporation in many TERT-positive cells is the result of negative regulation by the telomeric shelterin complex, and that disruption of this negative regulation leads to more telomerase-directed telomere elongation across many cells of the population.

Finally, we examined the correlation between the intensity of TERT RNAscope signal and telomere length in HeLa cells to determine if variable TERT RNA levels drive telomere length heterogeneity. We found no correlation between the number of RNAscope TERT spots in a cell and the average telomere length in that cell (S5A Fig). This observation is true with or without correction for centromere fluorescence intensity, indicating that differential probe access is not responsible for the observed result (S5B Fig). Thus, the telomere length in individual cells of the population does not correlate with TERT expression as measured at a single time point.

Methods for estimating telomere length

There are several methods available for telomere length measurement. These involve varying degrees of technical difficulty and background information on the genome of the species involved. The methods also vary in the amount of detail they provide, in the time and equipment required to process each sample, and in the financial costs involved. In Table 1, we offer a brief, overarching summary of the main differences among these methods, and below we explain each method in more detail, providing key references for obtaining more information.

Telomere restriction fragment assay

The TRF assay was developed over 20 years ago to measure mean telomere length from the distribution of telomere restriction fragments produced by digesting DNA with restriction enzymes that do not cut within the telomere sequence (Harley, Futcher & Greider 1990 ). It continues to be considered as the ‘golden standard’ method for measuring TL and is widely used to validate and optimize new methods or their application in new species or settings (Criscuolo et al. 2009 Kimura & Aviv 2011 Aubert, Hills & Lansdorp 2012 ). The key stages in the process of TRF are (i) restriction enzyme digest of gDNA, (ii) agarose gel electrophoresis of the digested DNA, (iii) hybridization using either traditional denaturing blots or non-denaturing, in-gel hybridization techniques and (iv) image analysis of telomeric smears on the resulting gels to generate telomere length estimates. TRF is a technically demanding method and requires relatively high concentrations of DNA, a high level of expertise and investment to set up in a new laboratory and is low throughput even in the hands of experts. However, it has many advantages, including providing a readily quantifiable distribution of TLs in kb units, which can be compared across populations and species and used to estimate both mean, medians and variance in TLs within a sample of cells (Table 1). There is a tremendous variability in telomere lengths among taxa (Gomes, Shay & Wright 2010b ). The likely upper and lower ranges of a study species TLs is a particularly important consideration when using the TRF method, as we discuss in more detail below. We also discuss the relative merits of the denaturing gel and in-gel hybridization methods below, and recommend reading Kimura et al. ( 2010b ) for full methodological details of the former, and Haussmann & Mauck ( 2008 ) for the latter.

The first step in TRF is the restriction digest of extracted gDNA. Most studies using TRF methods apply several of the available suitable restriction enzymes (which include HinfI, RsaI, HaeIII and MspI) with the combined use of just HinfI and RsaI being particularly common (see Delany, Krupkin & Miller 2000 Haussmann & Mauck 2008 Kimura et al. 2010b for further information). It is essential to digest all samples with the same combination and not to change the chosen restriction enzymes during the analysis. Digested DNA is then resolved using agarose gel electrophoresis. It is important to standardize the DNA concentrations prior to loading of samples onto the gel Kimura et al. ( 2010b ) have recommended standardization to with the 300–500 ng μl −1 range. Because TRF analysis depends entirely on the position of the telomere sequence within a gel, appropriate steps should be taken so that it is possible to diagnose gel inconsistencies both within and among gels. Within a gel, the molecular weight marker should be evenly-spaced in 5–10 wells across the gel to insure consistent DNA migration in all parts of the gel (Kimura et al. 2010b ). In addition, loading the same sample multiple times within and among gels allow for intra- and interassay variability to be assessed and reported (Kimura et al. 2010b ). Different types of gel electrophoresis are recommended depending on the range of telomeres found in the species studied. Where TL is typically <20 kb constant-field gel electrophoresis (CFGE) provides good resolution (Haussmann & Mauck 2008 ) and has typically been used in studies of humans (Kimura et al. 2010a b ). Where TLs are typically >20 kb pulsed-field gel electrophoresis (PFGE) can be used to provide better resolution of large DNA fragments up to 10 Mb (Haussmann & Mauck 2008 ). Whichever method is used, it is very helpful to report key electrophoretic parameters used in the methods of any publication using TRF (e.g. voltage/cm, run duration, gel concentration for both methods and electronic field inversion switch times got PFGE). Kimura et al. ( 2010b ) also provide advice on the percentage of agarose gel best suited to analysing telomeres of different lengths.

After gel electrophoresis, hybridization is then undertaken using a telomere probe that is complementary to the telomere sequence repeats (CCCTAAn or TTAGGGn), which is labelled with either chemicals for chemiluminescent detection (e.g. digoxigenin) or radiochemicals for radioactive detection (e.g. 32P). Whether a denaturing on non-denaturing gel is used will influence the probe binding, and it is very important that, once chosen, the probe should not be changed within a study. Radioactive probes enhance the sensitivity of detection, but also require more safety precautions (Kimura et al. 2010b ). Currently, denaturing blots are widely used in human TL studies. In a denaturing blot, the electrophoretically separated DNA fragments are transferred to a hybridization membrane. The double-stranded DNA is denatured in the process, so the probe is able to bind to all of the telomere sequences in the TRF. With this method, longer telomeres will bind more probe, so it is necessary to correct for this during analysis (Kimura et al. 2010b ). The in-gel hybridization approach involves drying the gel and then directly probing it rather than transferring DNA fragments to a hybridization membrane (Haussmann & Mauck 2008 ). The result is that telomere sequences are not denatured, so that only the CCCTAAn probe binds to the telomere single-strand overhang (Haussmann & Vleck 2002 ). The great advantage of the in-gel technique is that it will only bind terminal telomeres (i.e. it will not bind any interstitial telomeric sequence present, see ‘Which method to choose…’ section below for further discussion), but that comes at the price of less bound probe and the possibility of reduced sensitivity. Regardless which is used, it is important to wash the membrane or gel adequately to reduce non-specific binding of the probe, which results in background during TRF analysis (Kimura et al. 2010b ).

Once the membrane or gel has been exposed on X-ray film or phosphor screen, several approaches have been used to quantify TLs from the resulting image. In general, TRF measurement is accomplished by estimating telomere fragment size by comparison with molecular weight markers on the gel and relating this to the optical densities (OD) down the telomeric smear in each lane (Kimura et al. 2010b Haussmann, Salomons & Verhulst 2011 ). Obtaining OD data from telomere images is not a trivial task. There are numerous issues to consider, including whether and when to exclude lanes from analyses, which software to use to obtain OD values from a gel image, how to select a background OD to subtract from lane or gel ODs, and the analysis window to use to calculate the TL distribution. Different laboratories have used different methods in all respects, and the crucial thing here is to clearly explain the method in full in any publication and to be totally consistent with the method throughout a study. There has been some debate over the use of the program ‘Telometric’ to analyse gels in the recent literature (Horn, Robertson & Gemmell 2010 ), and a complete description of the issues with this software have now been presented (Haussmann, Salomons & Verhulst 2011 ). Our consensus is that, because of the potential for bias in its calculation methods, in its current form Telometric should not be used to analyse TRF gels. Free-to-download image analysis software, such as imagej (National Institute for Health, Bethesda, MA, USA), can be used to estimate OD variation across gel images, but further analyses of this data needs to be conducted by the researchers themselves. For a worked example of such an analysis, we refer the reader to the online appendix of Haussmann, Salomons & Verhulst ( 2011 ). The most appropriate method for a given study or type of gel may depend on the question and study system, and every researcher should therefore develop, justify and completely explain their approach to analysing TRF gels in any published article.

QPCR assay

The qPCR-based method for measuring TL was developed by Richard Cawthon in part to overcome the problem that TL measured using the TRF method can vary somewhat depending on the restriction enzymes used, and because of the limits that the amount of DNA and time required for the TRF assay can place on feasible sample sizes (Cawthon 2002 , 2009 ). Unlike TRF, which yields an estimate of the average or range of TLs in kb present in the sample of cells, qPCR provides an estimate of the amount of telomere sequence present in the sample relative to the amount of a specified non-telomeric reference sequence that is autosomal and non-variable in copy number (Cawthon 2002 ). qPCR is the most time efficient and high-throughput method currently available and requires less DNA than TRF (Table 1), which is important when extracting DNA from small amounts of tissue or whole blood, or when using blood samples from species without nucleated RBCs. However, expertise, diligence and high-quality DNA are still required for qPCR optimization and to ensure target specificity and assay precision. Much of the general advice on gene expression and qPCR analysis, such as on primer selection and optimization (e.g. Derveaux, Vandesompele & Hellemans 2010 ) and the minimum information for publication of quantitative real-time PCR experiments (MIQE) guidelines (Bustin et al. 2009 ), is equally relevant to the telomere qPCR assay and should be consulted before attempting to develop these assays. Important steps in the development and validation of a qPCR telomere assay include: (i) identifying an appropriate non-variable copy number gene sequence (ii) checking the amplification efficiency and melt-curve specificity of both non-variable copy number gene and telomere sequence during qPCR (iii) establishing high within- and among-plate repeatability of the assay.

The qPCR assay follows the general principle of polymerase chain reaction (PCR) where DNA acts as a template for its own amplification. The exponential nature of the PCR means that the number of thermal cycles (Cq) it takes for product amplification (measured by an intercalating dye, such as SYBR green, that fluoresces when bound to the newly generated double-stranded DNA) to cross a set threshold in the exponential growth phase (Nq) is proportional to the quantity of the original template DNA. In the telomere assay, there are two targets for amplification: the telomere sequence (T) and the non-variable copy number gene sequence (N). Cawthon ( 2002 ) originally referred to these as T and S (for single copy gene), rather than N, but in fact the reference sequence need not be in single copy or part of a gene (Smith, Turbill & Penn 2011 ). This non-variable copy number gene is used to account for the fact that, however carefully the researcher attempts to use the same concentration of DNA in each reaction, the number of cells will differ. As long as the N sequence is represented in an identical way in each genome represented in the samples, it will fulfil this function. The conservation of telomeric sequence means that the T primers (tel 1 and tel 2), originally designed by Cawthon ( 2002 ) and then modified for greater efficiency (tel 1b and tel 2b) by Epel et al. 2004 should work in all vertebrates. However, identifying an appropriate N sequence and designing primers to sequence will need to be undertaken de novo for any new study species. Importantly, even if a potential N gene that is found in all animals has been used before, the sequence and copy number may vary, even among closely related species. One method to select a non-variable copy number gene sequence is to test 3–5 candidate sequences on a range of samples representing both sexes and all populations used in the final sample set and checking for copy number variation or lack of amplification specificity (as outlined in Smith, Turbill & Penn 2011 ).

If the T and N sequences will amplify under the same PCR conditions, then reactions should be run on the same plate, because within-plate normalization can increase between-plate repeatability (Barrett et al. 2012 ). Furthermore, a reference (or ‘golden’) sample is typically included on every plate, and T:N ratios presented relative to that of the plate reference sample, thus accounting for among-plate variation (Cawthon 2002 ). These reference samples can be taken from a large volume single sample or pooled from multiple samples to ensure there is enough for all the planned assays and should be stored frozen in multiple small volume ‘single-use’ aliquots to prevent repeated freeze-thawing that might influence reaction efficiency. It is recommended that both T and N amplification is run in triplicate for each sample. The mean value across the replicates can then be used (e.g. Barrett et al. 2012 ), although we would strongly advocate calculating and reporting the measurement error among replicates. Recently, Cawthon ( 2009 ) proposed a monochrome multiplex qPCR approach that would in principal offer reduced measurement error and increased throughput. To date, this method has not been widely applied outside of human studies, although two recent studies have used it in dairy cattle (Brown et al. 2012 ) and humpback whales (Olsen et al. 2012 ) without validation against a non-qPCR method. One advantage is that the method allows a relative TL to be calculated for each well. Thus, rather than simply averaging over sample replicates within a plate and thereby ignoring the measurement error associated with among-replicate variation, this variation can be included and accounted for in subsequent analyses, for instance in a mixed-effects model (see Brown et al. 2012 for an illustration).

For precise and reproducible data one must achieve specific amplification and high amplification efficiencies for both the T and N amplicons. Amplification specificity can be determined by analysing the derivative melt-curve, which should show a single peak for each of the T and N sequence amplicons. Multiple peaks indicate non-specific amplification and primer-dimer formation that may result from poor primer selection and/or PCR optimization (Bustin et al. 2009 ). Amplification efficiency is the relative increase in amplicon concentration per cycle where doubling is 100% efficiency. Efficiency can be estimated per amplicon using standard curves (Pfaffl 2001 ) or by fitting regressions to the loglinear phase of individual reactions (Ruijter et al. 2009 ). The efficiencies between T and N usually differ, and small errors in efficiency estimation are compounded exponentially into very large errors in calculations of initial sequence quantity, so it is important not to use an analysis method that assumes equal efficiencies for T and N (e.g. the ‘delta-delta method’, which was used in Cawthon's 2002 article). We advocate a method that initially subtracts baseline variation in fluorescence, as this can bias estimated efficiencies and increase among-plate variation (Ruijter et al. 2009 ), and then also accounts for differences in efficiencies among samples (e.g. Pfaffl 2001 ). The freeware programme LinRegPCR is able to perform just such calculations using raw data from a variety of qPCR platforms (Ruijter et al. 2009 ), as can other commercially available programs. Various methods have been used to calculate relative TL from the Cq and efficiency data produced by software packages (e.g. Barrett et al. 2012 Olsen et al. 2012 Turbill et al. 2012 ). These appear to produce closely correlated results (Olsen et al. 2012 ), but it is important to report the exact method used in any publication.

One major drawback of the relative qPCR telomere assay is that it gives a within-study relative value of telomeric sequence per genome rather than an average telomere length in kb. As such, it cannot be used to compare TL or telomere dynamics among studies, populations or species. O'Callaghan et al. 2008 adapted the relative qPCR telomere assay by comparing sample amplification with that of synthesized telomere oligomers of known length, to yield an estimated TL in kb per diploid genome scale (the ‘absolute qPCR’ method O'Callaghan et al. 2008 ). Whether this approach renders comparison among studies meaningful is currently open to debate. The method has been criticized for providing unrealistic estimates of telomere lengths, suggesting this could be due to differences in efficiencies between samples and the external oligomer references (Horn, Robertson & Gemmell 2010 ). Barrett et al. ( 2012 ) modified the method to account for differences in efficiencies between samples and oligomers. The results from relative and absolute were almost perfectly correlated, presumably because the absolute method does little more than rescale the original relative TL data (e.g. r = 0·99, Barrett et al. 2012 ). Before considering the use of absolute qPCR data in comparative studies, it remains crucial to validate absolute qPCR-based TL estimates by comparing among study, individuals or species differences to those obtained using a more direct TL measurement method, such as TRF or flow-fluorescent in situ hybridization (FISH) to ensure that the variation measured reflects variation in the amount of telomeric sequence at the chromosome ends.

Q-FISH and flow-FISH

There are now four different protocols documented to measure telomere length (TL) that use FISH (Aubert, Hills & Lansdorp 2012 ). They are all adaptations of the original method, quantitative FISH (Q-FISH), which was developed by Lansdorp (Lansdorp et al. 1996 ). Q-FISH is a powerful but technically challenging procedure. It requires cultured cells or fixed tissue sections. Then, using a fluorescently labelled peptide nucleic acid (PNA) probe (CCCTAA)3, which specifically hybridizes to denatured telomere DNA, the TL of each chromosome end can be measured. Fluorescence intensity of bound probe is directly proportional to TL this quantitative relationship is the basis of all FISH protocols to measure TL. In Q-FISH, a fluorescent microscope and sensitive CCD camera creates digital images of metaphase spreads and specialized software is used to analyse them. Telomere intensities are normalized to samples or standards of known TL (Poon et al. 1999 ). When cells arrested in metaphase are used, Q-FISH provides quantitative information on TL distributions within a sample and can detect critically short telomeres. When fixed tissue samples are used, Q-FISH provides information about average telomere length. This information is of great importance in human studies as the accumulation of critically short telomeres, rather than short average TL, has been demonstrated to cause genetic instability, limiting cell survival and tissue renewal (Hemann et al. 2001 Hao et al. 2005 ). This technique has provided the opportunity to analyse telomeres of individual chromosomes separately, including differentiation between p and q arms of sister chromatids (giving 4 telomeric measurements per chromosome). It also allows for simultaneous karyotyping and identification of chromosomal abnormalities such as end-to-end fusions (Lansdorp et al. 1996 Poon et al. 1999 ).

Q-FISH achieves high resolution, but it is labour intensive, time-consuming and requires viable cell samples or fixed tissue sections (Table 1). Flow-FISH was developed to overcome some of these limitations and is now quite widely used in studies of human LTL dynamics (Aubert & Lansdorp 2008 Aubert, Hills & Lansdorp 2012 ). Here, interphase cells in suspension are hybridized with a PNA telomere specific probe and average TL is measured by fluorescence intensity using flow-cytometry (Rufer et al. 1998 ). This technique allows for a larger number of cells to be analysed in a much shorter time. Using antibody staining, different cell types within one blood sample can be sorted and compared. However, blood samples have to be fresh, and the process is still requires considerable expertise (Table 1). It is not surprising, given the complexity and specialized nature of FISH protocols, that they are rarely utilized by investigators seeking to measure TL in non-model organisms. Access to basic laboratory facilities can be limited when sampling wild populations, sometimes in remote places, so it is most likely to be useful for laboratory studies using captive animals, or were viable cell cultures can be readily established from sampled tissues. Being able to sample or culture live cells are all fundamental prerequisites for FISH techniques as too are the dedicated, and often expensive, laboratory equipment. However, the ability to study telomere dynamics in non-model organisms at this in depth level could expedite our understanding of the interactions between biological state and life histories tremendously.

Single telomere length analysis

Single telomere length analysis (STELA) is a high-resolution single-molecule PCR-based approach to determine telomere length (Baird et al. 2003 ). STELA is targeted to specific chromosome ends for which telomere-adjacent sequence is available. Originally developed to analyse the human XpYp telomere, STELA has now been extended to several additional human chromosome ends and has been adapted for use in Caenorhabditis elegans (Cheung et al. 2004 Britt-Compton et al. 2006 ). STELA utilizes the unique structure of the 3′ G-rich overhang at the telomeric terminus: a linker (telorette) anneals to this sequence and is ligated onto the end of the C-rich strand. Long-range PCR is then used to amplify between a specific telomere-adjacent PCR primer and a second primer (teltail) composed of the sequence of the 5′ end of the telorette linker. The PCRs are undertaken at the single-molecule level with amplification from typically 6–10 amplifiable molecules per reaction, each sample is analysed with up to six separate reactions to provide a large enough sample size. The amplified telomeric molecules are detected by Southern hybridization with telomere-adjacent and telomere repeat containing hybridization probes. This single-molecule approach yields a banding pattern, each band representing the telomere length of a single input telomere.

STELA requires only small amounts of input DNA, in humans typically <2 ng of DNA is analysed per sample. However the key advantage of this approach is that the very shortest telomeres are readily detectable, indeed telomeres composed of a single double-stranded telomere repeat can be detected telomeres in these length ranges are not currently detectable with any other method. These short telomeres are biologically important as they are observed in senescent cells, cells undergoing crisis in cancer and following sporadic telomere deletion (Baird et al. 2003 Baird 2008 Lin et al. 2010 ). Thus provided the longest telomeres are within the PCR amplifiable length range of up to 25 kb, the full spectrum of telomere lengths can be detected using STELA. Many organisms contain complex subtelomeric repeat sequence structures and interstitial telomere repeats, which can confound the interpretation of TRF-, Q-FISH- and Q-PCR-based approaches. By reducing the complexity and analysing specific chromosome ends, STELA could in principle obviate these issues. However, the success of STELA is dependent upon the existence of unique telomere-adjacent sequence and the lack of these sequences is likely to be the key factor limiting STELA for use in additional organisms. Telomere-adjacent sequences are not easy to characterize and are often not represented in genome sequencing projects, indeed many of these regions of the human genome are still yet to be fully characterized (Riethman 2008 ). However, simple PCR-based strategies have been used to characterize telomere-adjacent sequences in humans and related species (Royle, Hill & Jeffreys 1992 Royle, Baird & Jeffreys 1994 Baird & Royle 1997 ), and these approaches could be used to characterize sufficient telomere-adjacent sequences for STELA in organisms with poorly characterized genomic sequence.

The dot blot telomere assay

Which method to choose, and is one method enough?

although the qPCR methods are very attractive for their short timeline and costs, variability within and between samples remains relatively high. Each laboratory adopting a qPCR method should therefore conduct an initial calibration to a non-PCR-based telomere length measurement, [and] optimize the technique until a high r 2 coefficient is reached (Aubert, Hills & Lansdorp 2012 ).

To date, studies have compared TRF and qPCR methods in humans and birds and found strong correlations between the resulting estimates of average TL (e.g. Criscuolo et al. 2009 Aviv et al. 2011 Angelier et al. 2013 ). However, a growing number of published studies using qPCR in non-human animals have not validated their qPCR methodology against TRF. Our feeling is that the qPCR method can be validated internally and used alone, as long as: (i) full methodological details are presented, including complete descriptions of how amplification specificities and efficiencies were determined and used in quality control and calculations of TL, (ii) high within and among-plate repeatability can be demonstrated, and (iii) analyses and interpretations do not stretch beyond relative differences in TL among the samples in the specific study or experiment. That said, there are important reasons other than simply producing cross-method correlations that researchers might want to have more than one weapon in their methodological arsenal. While capable of generating large data sets rapidly, qPCR gives only a narrow window on telomere dynamics compared with some of the other available methods. It estimates average genomic telomere sequence content and does not capture the variation in TL present within a sample, which all other methods except the dot blot technique do provide in some form (Table 1). Growing evidence points to important links between the range of TLs and cellular function, in particular the presence of critically short TLs (Hemann et al. 2001 ). Indeed, a recent study using a high-throughput adaptation of the Q-FISH method provides the first link between an increase in the number of very short telomeres and survival in laboratory mice (Vera et al. 2012 ). It may ultimately prove very important to move beyond the qPCR methodology if we want to address the importance of variation in TL or the presence of very short telomeres. Furthermore, although techniques other than qPCR and TRF may require considerable additional investment of time and money to set up and validate, it is important to appreciate the additional insights such techniques could offer. For instance, STELA could provide important insights into the relevance of critically short telomeres for whole organism function and fitness, while flow-FISH could provide a means of dissecting similarities and differences in the telomere dynamics among different kinds of blood cell.

A further consideration when choosing a telomere measurement technique and interpreting its results is the presence of interstitial telomeric repeats, which are found within the chromosomes of some organisms including many birds and mammals (Delany, Krupkin & Miller 2000 Ruiz-Herrera et al. 2009 ). Measurements using the qPCR, dot blot and denaturing TRF methods will incorporate both terminal and interstitial telomeric sequences (Table 1). Non-denaturing in-gel hybridization TRF methods measure only terminal sequences, as do STELA and FISH techniques. Notably, a recent small-scale study of several passerine species used sequential application of non-denaturing and denaturing TRF gels to infer the relative amount of interstitial telomere sequence present (Foote, Vleck & Vleck 2013 ). The results suggest variation in interstitial telomere signal can be present at species, among- and within-individual levels, and may add noise to TL data possibly making it harder to find patterns. However, how this finding generalizes to other species or the mechanisms responsible evident variation in interstitial telomeric sequence are currently unclear (Foote, Vleck & Vleck 2013 ).

Materials and Methods

Cell culture and cryopreservation

Human bone marrow CD34 + hematopoietic stem/progenitor cells were obtained from AllCells and Fred Hutchinson Cancer Research Center. CD34 + cells were maintained in StemSpan SFEM II medium supplemented with CC110 (StemCell Technologies). K562 cells were cultured in IMDM supplemented with 10% FBS and 1% penicillin/streptomycin. Frozen stocks were prepared with 10% DMSO and 30% FBS in K562 medium and stored in liquid nitrogen prior to use. Genome editing experiments in hESCs were performed as previously described (Hockemeyer et al, 2009 Soldner et al, 2009 Hockemeyer et al, 2011 ) in the WIBR#3 line (Lengner et al, 2010 ) and NIH stem cell registry # 0079. Cell culture was carried out as previously described in Boyle et al ( 2020 ).

Guide RNA design and preparation

  • AAVS1 sgRNA-1 oligo: ggatcctaatacgactcactataggCCGGCCCTGGGAATATAAGGgttttagagctagaa
  • POT1 sgRNA1 oligo: ggatcctaatacgactcactatagGAGATCTTGCCACATGAACAgttttagagctagaa
  • POT1 sgRNA2 oligo: ggatcctaatacgactcactatagGTGATTTAAGTCACATCCATgttttagagctagaa
  • (sgRNA sequences are in capital letters)
  • POT1 Y223C for insertion of PGK-Puro-pA cassette: GAGATCTTGCCACATGAACA
  • POT1 Y223C targeting removal of drug resistance via de novo protospacer adjacent motive (PAM) sites: GAGATCTTGCCACATGACCA and GTCTGCGATAATCATGTCCA

Electroporation for genome editing

Genome editing by electroporation using Lonza 4D nucleofector was performed as described by the manufacturer’s protocol (Lonza, Inc.). To validate sgRNA in K562, approximately 200,000 cells were pelleted and resuspended in 20 µl of Lonza SF buffer containing supplement solution. The RNP complex was prepared by slowly adding 60 pmol of synthesized sgRNA to 100 pmol of purified CAS9 protein in CAS9 buffer. The RNP complex was incubated at room temperature for 20 min and was added to the cell suspension. To edit hCD34 + cells, 1 million cells were resuspended in 100 µl of Lonza P3 buffer containing supplement solution. RNP complex was prepared with 300 pmol of synthesized sgRNA and 500 pmol of purified CAS9 buffer as described above. The electroporation of K562 and hCD34 + was done using a K562-specific program or program ER100, respectively.

For “scarless” genome editing in hESCs, cells were first co-electroporated with a sgRNA-expressing plasmid (pX330) targeting POT1 and a donor plasmid. The donor plasmid contained a PGK-Puro-pA cassette flanked by de novo NcoI sites and the Y223C mutation in one of the homology arms. After selection with puromycin for 10 days, single cell-derived colonies were isolated, replicates were plated, and genomic DNA was isolated for confirmation of genotypes. The “scarless loopout” of correctly Puro-targeted clones was performed in a subsequent second step by co-electroporating a GFP expression plasmid (N2-GFP) with two px330 sgRNA-expressing plasmids targeting the two unique PAM sequences created by the NcoI sites. Cells were single cell-sorted for GFP expression and colonies were isolated and genotyped to confirm the removal of puromycin cassette while leaving behind the mutation (Y223C). Targeting was confirmed first by PCR and then by Sanger sequencing.

Genotyping and sequencing

  • F1: cggtttggagaagaaaaagc
  • R1: ccttcagagatcttgccaca
  • F2: tgccaatattcagaggcataa
  • R2: ccagtttaccaagcttagcattt

Q623H: Extracted genomic DNA was amplified by PCR with primers ttaaatttggaagggacgttt and acttttattaggttgaggtg and then digested with BglII for genotyping. Undigested PCR product was submitted for sequencing using one of the two primers. To ensure the accuracy of our genotyping and rule out the expansion of a subpopulation, we genotyped our cells at the end of the telomere length experiments. In addition, we subcloned genotyping PCR amplicons into PCR2.1. Sequencing of these plasmids supported all our genotyping results.

WT/Y223C: Initial insertion of the puromycin cassette was detected by PCR, where genomic DNA was extracted from individual clones and amplified by PCR using primers tgccaatattcagaggcataag and gcctttttcattctaaagcag, and amplified products were submitted for sequencing using one of the two primers. A correctly targeted clone was identified and subject to two CAS9 guide RNAs targeted the de novo NcoI sites flanking the puromycin cassette, removing this by “scarless loopout”. After this round of targeting, extracted genomic DNA was amplified by PCR using primers gtccgtctgcgagggtacta and gccatatctaaactgtgcacct, where a loss of a band indicated the removal of the puromycin cassette and successful targeting.

In vitro differentiation

hCD34 + cells were differentiated into erythroid lineage using established differentiation protocols (Giarratana et al, 2005 DeWitt et al, 2016 ). Briefly, hCD34 + cells were cultured in IMDM supplemented with 5% human AB serum, heparin (2 IU/ml), human insulin (10 ug/ml), human holo-transferrin (330 µg/ml), recombinant human erythropoietin (3 unit/ml), hydrocortisone (1 µM), recombinant human stem cell factor (100 ng/ml), and human interleukin-3 (5 ng/ml) for 7 days. For colony-forming clonal expansion, CD34 + cells were seeded in methylcellulose-based medium (MethoCult Express 04437, StemCell Technologies). In order to characterize colonies arising from single cells, cells were plated using limited dilution on 96-well plates. 2–3 weeks after seeding, single colonies were collected and genotyped by Sanger sequencing or NGS.


NBSGW mice from Jackson laboratory were used for the in vivo studies under the protocol approved by the office of laboratory animal care (OLAC) in UC Berkeley. Electroporated hCD34 + cells were injected to 6- to 12-week-old gender-matched mice via tail vein. To monitor human chimerism, mice blood was collected from submandibular vein into EDTA-coated collection tubes after transplantation. Red blood cells were lysed using EL buffer (QIAGEN) and washed twice with phosphate-buffered saline (PBS). Recipient mice were euthanized at weeks 16–20 post-transplantation. Bone marrow cells were collected from femur and tibia. In these isolations, we did not observe any overt indications for hematopoietic neoplasia. For ex vivo culture, hCD34 + cells from bone marrow were sorted using FACS Aria Fusion (BD Biosciences) and cultured using limited dilution culture method in methylcellulose-based medium on 96-well plate for 3 weeks.

Genotyping and NGS analysis

  • POT1 NGSR: GCTCTTCCGATCTaaatttacatgagcaaaaatcact
  • AAVS1 NGSF: GCTCTTCCGATCTcccctatgtccacttcagga
  • AAVS1 NGSR: GCTCTTCCGATCTggaatctgcctaacaggaggt

Flow cytometry and sorting strategy

100–200 µl of homogenized spleen or peripheral blood was treated with 2 ml of EL buffer (QIAGEN) for 1 min to lyse red blood cells. The reaction was quenched by adding 5–6 volume of chilled PBS. After centrifugation and removing supernatant, cells were stained with specific surface marker antibodies. The following antibodies (BD Biosciences) were used: V450 mouse anti-human CD19 (BD 560353), PE rat-anti-mouse CD45 (BD 553081), PE-Cy7 mouse anti-human CD34 (BD 348791), and FITC mouse anti-human CD45 (BD 555482). The cells were sorted using FACS Aria Fusion instrument. FACS data were analyzed using FlowJo software.

Single telomere length analysis (STELA)


Telomere restriction fragment analysis (TRF analysis)

TRF analysis was performed as previously described (Boyle et al, 2020 ). Briefly, genomic DNA was digested with MboI, AluI, and RNaseA overnight at 37°C and separated on a 0.75% agarose gel, dried under vacuum for 2 h at 50°C, denatured in 0.5 M NaOH and 1.5 M NaCl for 30 min, shaking at 25°C, and neutralized with 1 M Tris pH 6.0 and 2.5 M NaCl, shaking at 25°C, 2× for 15 min. Then, the gel was pre-hybridized in Church’s buffer (1% BSA, 1 mM EDTA, 0.5 M NaP04 pH 7.2, 7% SDS) for 1 h at 55°C before adding a 32 P-end-labeled (C3TG2)3 telomeric probe. The gel was washed 3 × 30 min in 4× SSC at 50°C and 1 × 30 min in 4× SSC + 0.1% SDS at 25°C before exposing on a phosphor imager screen.

T7 endonuclease I assay

Genomic locus targeted by sgRNA was amplified by PCR. The PCR products were prepared in 20 µl volume containing NEB buffer 2 (New English Biolabs, Inc). Prior to T7 endonuclease treatment, the purified PCR product was denatured at 95°C for 5 min and annealed back by slowly cooling down to room temperature. After treating with 5 units of T7 endonuclease I for 30 min at 37°C, the final product was separated by electrophoresis and visualized.

IF/TIF analysis

Analysis was carried out as previously described in Boyle et al ( 2020 ). For analysis by IF, cells were washed with PBS, fixed with 2% paraformaldehyde in PBS, permeabilized with 0.1% Triton X-100, and blocked with 1 mg/ml BSA, 3% v/v horse serum, and 1 mM EDTA in PBS. After blocking, cells were incubated with antibodies against TRF1 raised in rabbit against amino acid residues 17-41 (856-R1) and γ-H2AX (Millipore) in blocking solution followed by secondary antibodies. Scoring of TIF-positive cells was performed single blind. More than 50 cells were evaluated for each condition. p-values were determined using Prism 9’s Mann–Whitney test. As a positive control and to demonstrate that these cells are competent to from TIFs, we infected them with a lentivirus expressing TPP1∆PBD or an empty control virus and stained them for TIFs 72 h post-infection. Cells not infected with the virus remained TIF negative.

Metaphase Spreads/FISH

Analysis was carried out as previously described in Boyle et al, ( 2020 ). Cells were treated with colcemid at 100 ng/ml for 2 h. We collected the cells using trypsin and incubated at 37°C in prewarmed 75 mM KCl. The cells were spun down, and the KCl was removed. Cells were slowly resuspended in a fixative of 3:1 methanol:acetic acid. Cells were stored overnight at 4°C. The next day, cells were spread, dropwise, onto microscope slides and washed twice with 1 ml 3:1 methanol:acetic acid solution. Slides were then placed onto an 80°C humidified heat block for 5 min. Samples were fixed in 3.7% formaldehyde diluted in PBS and then treated with pepsin (1 mg/ml) prepared in 10 mM glycine pH 2 and warmed up to 37 degrees. After one more wash in 4% PFA, slides were washed with PBS and then dehydrated in an ethanol series. Each slide received 100 µl of hybridization mixture, was denatured at 80 degrees for 5 min, and then hybridized overnight with Cy3 Tel-C probes (PNA Bio) at 4 degrees in a hybridization chamber. The next day, the slides were washed with 70% formamide, 10 mM Tris–HCl pH 7.2, and 0.1% BSA solution, then with 0.1 M Tris–HCl pH 2, 0.15 M NaCl, and 0.08% Tween, and with DAPI (diluted 1:1,000 from 5 mg/ml stock) added to the second wash. Coverslips were mounted with ProLong® Gold Antifade Mountant (Thermo Fisher Scientific). All microscopy (IF and metaphase spreads) was imaged on a Nikon Eclipse TE2000-E epifluorescent microscope equipped with an Andor Zyla sCMOS camera.

Telomere length influences cancer cell differentiation

Researchers from the Japanese Foundation for Cancer Research in Tokyo have discovered that forced elongation of telomeres (extensions on the end of chromosomes) promotes the differentiation of cancer cells, probably reducing malignancy, which is strongly associated with a loss of cell differentiation. They report their findings in a manuscript published online ahead of print, in the journal Molecular and Cellular Biology.

"Cancer cells may maintain short telomeres to maintain their undifferentiated state," says Hiroyuki Seimiya, a researcher on the study.

Telomeres are protective extensions on the ends of chromosomes, which shorten as cells age, like an hourglass running down. They protect the end of the chromosome from deterioration or from fusion with neighboring chromosomes.Without telomeres chromosomes would progressively lose genetic information as cells divide and replicate.

Cancer cells have shorter telomeres compared to healthy cells, but they guard their immortality by maintaining these telomeres' length.

In the study, the forced elongation of cancer cells' telomeres suppressed a number of genes and proteins that appear to be involved in tumor malignancy, according to the report. For example, one of these factors, N-cadherin, is involved in prostate cancer metastasis.

Based on their results, the investigators now propose that telomeres also modulate the behavior of cells by controlling gene expression, by as yet unknown mechanisms, says Seimiya. His research, he says, may ultimately lead to new types of treatments for cancer.


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