1. Biochemistry and Chemical Biology
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Long-lived metabolic enzymes in the crystalline lens identified by pulse-labeling of mice and mass spectrometry

  1. Pan Liu
  2. Seby Louis Edassery
  3. Laith Ali
  4. Benjamin R Thomson
  5. Jeffrey N Savas  Is a corresponding author
  6. Jing Jin  Is a corresponding author
  1. Northwestern University, United States
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Cite this article as: eLife 2019;8:e50170 doi: 10.7554/eLife.50170

Abstract

The lenticular fiber cells are comprised of extremely long-lived proteins while still maintaining an active biochemical state. Dysregulation of these activities has been implicated in diseases such as age-related cataracts. However, the lenticular protein dynamics underlying health and disease is unclear. We sought to measure the global protein turnover rates in the eye using nitrogen-15 labeling of mice and mass spectrometry. We measured the 14N/15N-peptide ratios of 248 lens proteins, including Crystallin, Aquaporin, Collagen and enzymes that catalyze glycolysis and oxidation/reduction reactions. Direct comparison of lens cortex versus nucleus revealed little or no 15N-protein contents in most nuclear proteins, while there were a broad range of 14N/15N ratios in cortex proteins. Unexpectedly, like Crystallins, many enzymes with relatively high abundance in nucleus were also exceedingly long-lived. The slow replacement of these enzymes in spite of young age of mice suggests their potential roles in age-related metabolic changes in the lens.

Introduction

The lens is a transparent body with an essential role in visual acuity. It consists of an outer capsule of type IV collagen-laminin membrane, the cortex of lens epithelium, and denuclearized and organelle-free fiber cells at the core. A single layer of germinal cells beneath the anterior capsule gives rise to transitional cells which differentiate into elongating fiber cells and finally the mature lenticular fiber cells forming the nuclear mass of the lens. In this process, the human lens continues to grow slowly in its weight and size throughout life (Vavvas et al., 2002; Guirou et al., 2013; Augusteyn, 2007; Bassnett, 2002). Frequently associated with aging, lens disease, such as cataracts, account for approximately half of the global blindness (the World Health Organization data). However, the underlying molecular mechanisms for most cataracts remain poorly understood (Pescosolido et al., 2016). Evidence suggest that accumulation of oxidized proteins and lipids predisposes the lens to nuclear cataract development (Reddy, 1971; Williams, 2006). Despite the slow turnover of the lens tissue, it remains a site of biochemical activity (Reddy and Giblin, 1984; Hejtmancik et al., 2015), in which the production of reducing metabolites and perhaps local enzymatic reactions within the fiber cells are important in combating oxidative stress.

Previously, radiocarbon (14C) dating studies demonstrated that with respect of the total protein and lipid, there was little turnover at the nuclear core of lens (Lynnerup et al., 2008; Hughes et al., 2015; Nielsen et al., 2016). However, a recent single-fiber-cell transcriptome study of postnatal day 2 mice detected mRNA encoding proteins known to exist in anucleate lens fibers (Gangalum et al., 2018), implicating active protein synthesis. In order to gain insight into the protein dynamics of lenticular fiber cells, including their structural proteins, chaperones and enzymes, we performed whole organism pulse-labeling of mice with heavy nitrogen-15 (15N) supplied in the diet to assist distinguish newly synthesized proteins from their counterparts existing before labeling.

Results

The lens had extremely slow turnover of its proteome as compared to non-lens tissues in the eye

Between 3 and 15 weeks of age, mice were fed with exclusively 15N chow (Savas et al., 2012; Liu et al., 2018), following which the eye tissues were harvested. The entire lens was processed and then analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) (Figure 1A–C and Methods). In total, 535 proteins were identified at 1% FDR at the protein level, of which 248 proteins showed the presence of both fully 14N and 15N spectra for calculating their 14N/15N ratios (MS1 ratios of the old vs. the new protein. See Methods, Figure 1D and Supplementary file 1). These ratios reflected the proportions of individual proteins being replaced with new 15N proteins in addition to newly formed fiber layers being added to the growing lens. More than 50% of individual proteins in the lens were only detected in their 14N forms, as compared to 1.8% and 2.8% in the vitreoretinal and sclera/choroid tissues respectively (Figure 2A and Supplementary file 1). These non-lens tissues had a majority of individual proteins completely replaced by new 15N proteins, in contrast to the slow turnover of 1.7% of individual lens protein. While the determination of lack of 15N peptides is subjected to MS detection sensitivity, we listed only the most abundant proteins with the total absence of 15N labels (Figure 2B). These extremely long-lived proteins included structural proteins such as PE-binding protein 1 (PEBP-1), β-Catenin, Moesin, and enzymes that are involved in oxidoreduction such as Peroxiredoxin-2 (Prdx2), Farnesyl pyrophosphate synthase (FPS) and Aldehyde dehydrogenase (Aldh7A), and in glycolysis such as ATP-dependent 6-phosphofructokinase (ATP-PFK). For those proteins with both 14N and 15N peptides detected, lens proteins exhibited the most long-lived proteins with greater 14N proportions (Figure 2C).

The 15N-labeling workflow for measuring the protein dynamics.

(A) After weaning, C57BL/6J mice were subjected to an exclusively 15N chow diet starting at P21 for a total duration of 12 weeks. 15N was incorporated into newly synthesized proteins. (B) In LC-MS/MS, 14N- and 15N-peptides of the same sequence co-elute (left panel). Regardless of where MS/MS is triggered (arrows pointing at random positions), the MS1 peptide signal intensities between the 14N and 15N channels reflect of their relative abundance (right panel). (C) Representative proteins showed different turnover rates. D. Among 543 lens proteins (blue dots) that were quantified via their 14N vs. 15N ratios (y-axis), there was a wide range of total protein abundance as estimated by MS/MS spectral counts (x-axis). Note that Calpain protease was long-lived, and the highly abundant α-, β- and γ-Crystallin proteins each had different levels of 14N and 15N.

The lenticular proteins generally had longer life times than the vitreoretinal and sclera/choroid proteins.

(A) Inter-tissue comparison of protein longevity showing numbers of proteins based on 14N-peptides only, 15N-peptides only, or 14N/15N ratios calculated (hatched pie). While in the lens a large number of protein had a greater proportion of 14N, other ocular tissues had a faster protein turnover with more proteins completely labeled with 15N within 12 weeks. (B) A list of the most abundant proteins that were only detected by 14N peptides with the absence of 15N. (C) Among the proteins identified with both 14N and 15N peptides—248, 362 and 398 proteins in the lens, the vitreoretinal and the sclera/choroid, respectively, the distribution of 14N-to-15N ratios of the lens proteins was different than those of the other tissues. As expected, the lens had the highest proportion of its 14N-proteins remaining. (D) The distribution of 14N/15N ratios from low to high as in Figure 2C. There is a long list of 278 proteins with only their 14N-proteins detected (dotted blue line to upper right), indicating possibly less 14N to 15N conversion of these proteins than those measured with 14N/15N ratios. Proteins that are implicated in cataract including structural proteins, gap junction and water channels, and metabolic enzymes are listed with arrows pointing to their corresponding values. The family of Crystallin proteins are listed below. Benchmark Histones H3.3 and H3.1/3.2 are also listed, representing transcription vs. cell proliferation activities, respectively.

The longevity of proteins associated with fiber cell differentiation

Meanwhile, the histone variant H3.3 was among the fastest turned over proteins (14N/15N = 0.2, Figure 2D). H3.3 is associated with transcription loci in the chromosome (Szenker et al., 2011; Toyama et al., 2013) and its frequent replacement by newer H3.3 indicated active transcription and translation activities in the lens, most likely in the capsule and the cortex. By contrast, histone H3.1 and H3.2 in the heterochromatin regions that only renew during cell cycle replication (Hake and Allis, 2006) were found to be comprised of a greater proportion of older proteins (14N/15N = 2.98 and 4.02, respectively), consistent with the notion that most lens fiber cells are postmitotically differentiated and subsequently lose chromatin (Bassnett and Mataic, 1997). The overall rate of lens cell growth was estimated to be slow, with 1/5 to 1/4 of H3.2 and H3.1 being synthesized with full 15N during the 12 week period. However, in these fiber cells that had ceased to replicate, the beaded filament proteins of Phakinin and Filensin (Blankenship et al., 2001; Wenke et al., 2016) that are implicated in cataract development (Conley et al., 2000; Jakobs et al., 2000; Carter et al., 2000) were still being actively produced (14N/15N equals 2.02 and 1.02 respectively) (Figure 2D and Supplementary file 1).

A wide range of crystallin α, β and γ new protein synthesis

The γ-Crystallins A/E/F/N that are localized to the nuclear lens showed the greatest proportion of their 14N-proteins (14N/15N > 20), followed by phosphoglycerate mutase 2 (Pgm2) that catalyzes glycolysis (14N/15N > 20), and cysteine protease Calpain-3 (14N/15N = 18.8) responsible for protein degradation (Figure 2D). Crystallins are the most abundant proteins in the lens (Figure 1D), and they are divided into α, β and γ protein groups based on sequence homology. α- and β- Crystallins (Crya and Cryb) are chaperone proteins for protein refolding under conditions of oxidative stress (Hejtmancik et al., 2015; Horwitz et al., 1999; Andley, 2007), and the densely packed γ-Crystallins (Cryg) contribute to reflection and hardness of the lens. Interestingly, a range of 14N/15N ratios was detected among distinct family members of each class (Figure 2D and Supplementary file 1): from 1.4 to 3.01 for α-Crystallins, 1.16 to 9.13 for β-Crystallins, and 1.46 to >20 for γ-Crystallins. These results are in agreement with our previous analysis of Crystallin longevity in aged rats (Toyama et al., 2013).

The gap junctions, the water channels, and the extracellular matrices of the lens

Beside the Crystallins, cataract-linked mutations have been reported in other structural proteins (Shiels et al., 2010; Churchill and Graw, 2011), including those forming the connexin gap junction channel (Berthoud and Ngezahayo, 2017; Goodenough, 1992) and aquaporin water channel (Agre and Kozono, 2003) (A complete list of all identified proteins in Supplementary file 1 with selected examples shown in Figure 2D). In our dataset, Cx50 was among the longest-lived gap junction proteins with an 14N/15N ratio of 7.19, consistent with Cx50’s presence in mature fibers at the nucleus (White et al., 1992). This was in contrast with the water channel Aquaporins of Aqp0/Lim1/Mip (14N/15N = 1.34) (Bateman et al., 2000; Berry et al., 2000; Francis et al., 2000) and Lim2/MP19/Cataract19 (14N/15N = 3.25) (Pras et al., 2002). These gap junctions and Aquaporins form channels known to be critical for the passage of important small metabolites to the lens, and mutations of their genes predispose individuals to cataracts (Verkman et al., 2014; Liu et al., 2011; Chepelinsky, 2009).

Unlike the mature fibers that uniquely form the core of the lens, the outer capsule of the lens resembles other basement membranes such as the glomerular basement membrane of the kidney. Mutations in the major components of type IV Collagen cause Alport syndrome that concurrently affects the kidney, the eye including cataracts and the ear. These type IV Collagen proteins in the lens membrane matrix are produced by the adjacent epithelial cells (Arita et al., 1993). Collagen IV-α1, -α2 and -α3 all had balanced 14N/15N ratios of 1.52, 1.34 and 1.34 respectively (Supplementary file 1) that had greater proportions of older 14N-proteins than the majority of lens proteins, however remarkably similar to their counterparts in the kidney at 1.43, 1.43 and 1.16 respectively (not shown). By contrast, another basement membrane protein Perlecan/Hspg2 at the outer and inner surfaces that contributes to anionic charges (Danysh and Duncan, 2009) lived longer than Collagen IV (14N/15N = 4.11) (Figure 2D). This apparent contrast of having long-lived Perlecan may partly explain the phenomenon of the lens capsule losing its net anionic charges during aging (Winkler et al., 2001): the slow replacement Perlecan may contribute to the gradual loss of its sulfated glycosaminoglycan moieties.

Contrasting difference between the long preservation of proteins in the nucleus and a varying dynamic turnover of cortex proteins in the lens

Next, we sought to compare protein dynamics in the nucleus and in the cortex of lens. As expected, proteins extracted from the nucleus were mostly shared with their cortex counterparts (Figure 3A and B), and a majority of nuclear proteins had little or no protein turnover as determined by their 14N/15N ratios close to or above 100 (Figure 3B: upper limit set at 100). Meanwhile, proteins harvested from the cortex tend to have a wide range of new vs. old protein ratios (Figure 3B). This was also reflected among Crystallin isoforms (Figure 3B: highlighted), with α-Crystallins having the highest contents of 15N in the cortex (Figure 3C). Although all Crystallin isoforms appeared to contain fractions of newly expressed 15N-proteins in the cortex, their individual abundance at the total protein level vary substantially (Figure 3C). For instance, while α- and β-Crystallins had more balanced presence between cortex and nucleus fractions, γ-Crystallin levels in the cortex were very low (Figure 3C). When protein abundance of all proteins was compared, the cortex and the nucleus had comparable 14N levels, in contrast to very low new protein contents in the nucleus (Figure 3D, and Supplementary file 1).

Comparison of lens cortex and nucleus proteins by 14N/15N ratios.

(A) Lens tissues from the the cortex and the nucleus were separately harvested and subsequently resolved by SDS-PAGE. Prominent gel bands of Crystallins were present in both cortex and nucleus fractions, whereas in the higher molecular weight areas of the gel the cortex tissue appeared more intensely stained for its protein contents. (B) A direct comparison of 166 proteins identified in both cortex (red diamond) and nucleus (blue circle) plotted along the x-axis with their 14N/15N ratios separately plotted against the y-axis. In all proteins their 14N/15N ratios were higher in the nucleus (an arbitrary ceiling of the ratios was set at 100 that reflects no protein turnover). There was a wide range of the ratios among individual proteins in the cortex, including all subtypes of Crystalline (filled shapes in red). The ratio values for nuclear Crystallins are also indicated with filled circles at the corresponding x-axis positions (example illustrated by the dotted line). (C) When individual Crystallin isoforms are compared with respect to their abundance (circle size) in the cortex and the nucleus, there is a general trend of more γ-Crystallins (Cryg) in the nucleus with similar α- and β-Crystallin (Crya and Cryb) contents as compared to the cortex. The 14N/15N ratio indices (pie-chart) among these isoforms in the cortex were also different. Asterisks: Crystallins that are not expressed in human lens. (D) Total spectra counts that reflect the relative abundance of individual proteins were plotted for cortex vs. nucleus distributions. Among the old 14N-proteins there was a relatively balanced distribution between the two fractions (left panel). In contrast, the newer 15N-proteins were mostly concentrated only in the cortex (right panel).

Very slow turnover of enzymes for Redox and glycolysis

The most unexpected finding of this 15N-labeling study was that metabolic enzymes in the lens were remarkably long-lived, particularly those catalyzing electron transport chain (ETC) in glycolysis and redox reactions (Figure 4 and Supplementary file 1). For instance, phosphoglycerate mutase 2 (Pgam2) that catalyzes the conversion of 3-phosphoglycerate to 2-phosphoglycerate had an 14N/15N ratio of >20, comparable to those of γ-Crystallin. A number of other enzymes in glycolysis (such as Pgk1,2, 6-Phosphogluconolactone, β-Enolase and γ-Enolase) also had 14N/15N ratios greater than that of histone H3.2 (14N/15N = 4.02), the benchmark protein that had ceased to renew following fiber cell differentiation. It can be inferred that these enzymes were preserved beyond the point of fiber cell differentiation, which is consistent with the notion that biochemical activity continues in mature fiber cells. Glycolysis that generates electron transport and ATP is an integral process of the overall redox reaction. Given the importance of maintaining a reduced cellular environment, redox enzymes such as glutathione S-transferases (GST) and S-synthases (GSS), and alcohol dehydrogenase class-3 (Adh5) were not only abundantly present in the lens but also long-lived with their 14N/15N ratios between 4.45 and 5.94 after 12 weeks of labeling (Figure 2D, Figure 4 and Supplementary file 1). It is important to note that a majority of these enzymes were still preserved in the nuclear lens (Figure 4 and Supplementary file 1) with most of them having predominately 14N contents. This observation strongly indicates active enzymatic activities at the core of the lens attributable to these extremely long-lasting enzymes.

Pulse-labeling of the lenticular proteome showed the longevity of metabolic enzymes for redox and glycolysis reactions.

Enzymes for energy metabolism and oxidoreduction-detoxification were being measured for their 14N vs. 15N abundance in the lens. Marked in red font are proteins that had their 14N/15N ratios successfully measured (with their values in parenthesis; followed by a second set of ratios for their nucleus counterparts marked by asterisks).

Discussion

We performed 15N-labeling of mice in conjunction with mass spectrometry-based measurement of 15N- vs. 14N-protein ratios. These ratios to a great extent reflected the turnover rates of individual proteins in the lens. The results illustrated a range of new protein synthesis activities, as well as an unexpected panel of proteins that were preserved long after terminal differentiation of the fiber cells, particularly in the nuclear lens. In this latter category, besides structural, water channel and chaperone proteins, metabolic enzymes that catalyze glycolysis and redox reactions were long-lived, and therefore may have implications for age-related cataract formation.

Although the mouse model is our convenient choice for the labeling protocol that is associated with a high cost of 15N-chow, there are notable limitations in addressing the protein basis for cataract. For instance, certain Crystallin isoforms do not express in human (Figure 3C). In addition, the choice of rather young animals between 3 and 15 weeks was not ideal for understanding the disease. Instead, the results are more relevant to lens development from post-weaning, through sexual maturity (by 4 weeks) to fully grown adult (by 12–24 weeks), which is equivalent for human age of 20–30 years (information from jax.org) (Dutta and Sengupta, 2016). However, the most common presenile cataracts have much later onset. Therefore the protein turnover indices only reveal a narrow spectrum of the changes in protein dynamics in the lens, and the observed preservation of redox enzymes in the nucleus core might not last as long as some Crystallins at old age. In addition to oxidation in cataract lens, many other biochemical changes also occur. Spontaneous conversion of L- to D-amino acids in proteins contributes to racemization in cataract lens (Hooi and Truscott, 2011), and protein isomerase activities are thought to have a role counteracting cataract development (Lyon et al., 2018; Lyon et al., 2019). Related to point that older proteins tend to accumulate post-translational modifications, our mass spec-based approach was not set up to detect all relevant modifications such as non-enzymatic deamidation of Gln and Asn sidechains that occurs more often in old age (Forsythe et al., 2019). This omission of modified peptides would have affected the calculation of 14N/15N ratios, particularly when the types of modifications were more prevalent in the older 14N-proteins.

Although we only included other non-lens tissues such as the retinal, the sclera and the choroid as controls for having faster turnover dynamics, proteins such as laminin, collagen and fibrillin elastic fibers in these tissues were found to be long-lived (not shown). It should be noted that since we selected a relatively long duration of the labeling process (12 weeks in total), we have passed the most dynamic phase of 14N-to-15N transition in non-lens tissues. It is however anticipated that 15N pulse-labeling, when the duration is adjusted based on the target tissue, can provide valuable information about protein dynamics, which will be particularly useful in comparing normal and disease tissues for insight on pathogenic transformation or adaptation.

Materials and methods

Stable isotope labeling in mouse (SILAM)

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The general method of raising 15N-labeled mice was described previously (Savas et al., 2012; Liu et al., 2018). In brief, starting at postnatal day 21 after weaning, C57BL/6J mice were fed exclusively with a 15N-raised spirulina diet (from Cambridge Isotopes and Harlan Laboratories) for 12 consecutive weeks. At this time, the 15N-proteins in the serum was determined to be greater than 99% by mass spectrometry (Liu et al., 2018).

Harvest of the crystallin lens

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Immediately after cervical dislocation of the mice, eye globes were surgically removed and then dissected for collecting the lens. For total protein extraction of the lens, the intact lens was first washed in phosphate-buffered saline, and then submerged into 100 μL of 2x concentrated SDS sample buffer containing 4% SDS, 20% glycerol, 10% 2-mercaptoethanol, 0.004% bromphenol blue and 0.125 M Tris HCl, pH = 6.8. The lens tissue was dissolved following sonication on ice. After the solution turned completely clear, the samples were let to be further dissolved at 4°C for overnight. On the next day, the tissue homogenates from three mice were combined and were resolved by SDS-PAGE. Following staining of the gel with GelCode Blue (Thermo Fisher Scientific), the gel lanes were excised and further divided into ~1 mm3-sized gel cubes. These gel cubes were subsequently subjected to a standard in-gel trypsin/lys-C digestion (Promega), reduction and iodoacetamide alkylation protocol following the manufacturer’s instruction.

Separation of cortex and nucleus tissues

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Lenses retrieved from frozen stock formed clear separation between their cortex and nucleus tissues. The cortex in association with the lens capsule were fragile, whereas the nuclear core tissue remained rigid and was picked out using a pair of tissue forceps. The collected nucleus specimens (combined from three eyes) were washed three times in PBS solution before submerged in SDS sample buffer. The lens cortex (also combined from three eyes) was collected without the lens capsule, and then dissolved in SDS sample buffer. Following sonication until the tissue homogenates turned clear, the samples were loaded on an SDSPAGE for protein separation. Proteins were subsequently digested from the gel with Trypsin/LysC as described above.

Mass spectrometry

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The general procedures for conducting 15N- vs. 14N-based proteomics were described previously (Liu et al., 2018; Savas et al., 2017). In brief, 3 μg of the peptides in Buffer A solution (94.785% H2O, 5% ACN, 0.125% FA) was loaded onto a nanoViper C18 trap column. The peptides were resolved following a 2 hr gradient following an increase Buffer B (99.875% ACN, 0.125% FA) concentration. Peptides were elctrosprayed from the Nanospray Flex Ion Source and analyzed on the Orbitrap Fusion Tribrid mass spectrometer. MS parameters were as follows: ion transfer tube temp = 300°C, Easy-IC internal mass calibration, default charge state = 2. Detector type set to Orbitrap, with 60K resolution, wide quad isolation, mass range = normal, scan range = 300–1500 m/z. Max injection time = 50 ms, AGC target = 200,000, microscans = 1, S-lens RF level = 60. Without source fragmentation, datatype = positive and centroid, MIPS was on, included charge states = 2–6 (reject unassigned). Dynamic exclusion enabled with n = 1. Precursor selection decision = most intense, top 20, isolation window = 1.6, scan range = auto normal, first mass = 110, collision energy 30%, CID, Detector type = ion trap, max injection time = 75 ms, AGC target – 10,000, inject ions for all available parallelizable time.

Spectral analysis and protein quantification

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Spectral analysis was done using Integrated Proteomics Pipeline (IP2), including running ProLuCID searches against the RefSeq mouse dataset. Basic parameters of 10 ppm precursor mass tolerance and 600 ppm for fragmented ions were used. Searches were filtered with DTAselect containing one peptide per protein, at least one tryptic end and unlimited missed cleavages of a minimum of 6 amino acid, with a false discovery rate (FDR) < 0.001, fixed modification of +57.02146 Da on cysteine residues, and all precursor mass within 10 ppm of expected. To estimate peptide FDRs accurately (set at <1%), target/decoy database was used containing the reversed sequences of all the proteins appended to the target database (Elias and Gygi, 2007). Searches were done for combined light and heavy peptides and Census quantified (Savas et al., 2017).

To calculate the 14N/15N peptide ion intensity, the ProLuCID results were used to reconstruct MS1 ion chromatograms in the m/z range that included both the heavy and light peptide (Liu et al., 2018; Park et al., 2008). The intensity ratios were then calculated per peptide using the reconstructed chromatogram. Peptide ratios with correlation values greater than 0.5 were used to remove poor-quality peptide ratio measurements. When more than two peptides were found for the same protein, Census removed outliers based on the Grubbs test (p value < 0.01) by calculating the SDs for the proteins. With QuantCompare, the final peptide ratios were generated. For each protein, its heavy vs. light ratios were represented by the composite of all peptide ratios identified by MS that are assigned to the protein. In cases of extremely low signals in one of the two channels, which will render extremely high or low ratio values mathematically, we arbitrarily set upper and lower limits of the protein ratios at 20 and 0.05. For the cortex vs. nucleus comparison, because of the extreme longevity of nucleus proteins we raised the ceiling to 100 for 14N/15N ratios. The final list of RefSeq protein entries were searched against the UniProtKB database to obtain a non-redundant set of proteins based on their unique gene identifiers (listed in Supplementary file 1).

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Decision letter

  1. Jeremy Nathans
    Reviewing Editor; Johns Hopkins University School of Medicine, United States
  2. Michael A Marletta
    Senior Editor; University of California, Berkeley, United States
  3. Ryan Julian
    Reviewer; UC Riverside, United States
  4. Eugene I Shakhnovich
    Reviewer; Harvard University, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Thank you for submitting your manuscript "Long-lived metabolic enzymes in the crystalline lens identified by pulse-labeling of mice and mass spectrometry" to eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Michael Marletta as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Ryan Julian (Reviewer #1); Eugene I Shakhnovich (Reviewer #2).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

The reviewers and I were impressed with the work, but each reviewer also had specific and useful comments for improving the manuscript. Specifically, the data interpretation would be substantially clarified if an analysis could be conducted on the separated nucleus and cortex of the lens. Additionally, the paper would be strengthened with a more critical discussion of the data as it relates to longer lived species and to the existing literature on lens and non-lens protein turnover.

I am including the two reviews at the end of this letter. I appreciate that the reviewers' comments cover a range of suggestions for improving the manuscript. We look forward to receiving your revised manuscript.

Reviewer #1:

This manuscript examines protein turnover in the mouse lens by heavy atom labelling followed by mass spectrometric proteomic analysis. The results confirm previous findings; many proteins in the lens are long-lived and not subject to turnover, including enzymes. The results are interesting and certainly worthy of publication, but some of the data is difficult to interpret due to the experimental approach and the work is not adequately placed in the larger context of previous work on long-lived proteins in the lens.

1) The major difficulty here arises from examination of the whole, intact lens, which contains fiber cells in various stages of development. Some of these cells will contain a host of functional organelles and others will not. When combined with the excellent sensitivity of mass spectrometry, the detection of protein turnover becomes difficult to interpret. These proteins may originate primarily from the periphery of the lens where the newest fiber cells are still capable of turnover. Therefore the question of whether fully mature fiber cells allow any protein turnover cannot be answered. Separation of the nucleus and cortex would have allowed analysis of mature fiber cells independently.

2) The timescale should also be explicitly discussed in terms of relevance to the human lens. Although 12 weeks is a long time in the normal sense of protein turnover, it is still not very long compared to 50 years that it might typically take for cataract to occur. Some enzymatic activity could persist for a few weeks, but maybe not over decades.

3) The detection of long-lived proteins outside the lens is interesting and could use more discussion or elaboration in the figures.

4) In relation to cataract, the paper only mentions oxidative markers that correlate with cataract. Recent results have also shown that racemization is also higher in cataract. Hooi and Truscott, 2011. In connection with this, the activity of enzymes (which is mentioned as an unknown) for combating racemization has also been studied as a function of location and therefore longevity within the lens. Lyon, Sabbah and Julian 2018. Cataract is very complicated and connected to many factors. A broader discussion would be useful.

5) It would be valuable to show some of the data for 14N/15N ratios obtained from different peptides for the same protein to allow readers to evaluate the variation in the data. Perhaps the standard deviation for each value could be given in addition to the average.

Reviewer #2:

(This review was written in collaboration with Eugene Serebryany, a postdoc in the lab who is an expert in crystallins).

This is an interesting and important paper which uses an ingenious isotope labeling approach to determine the lifetimes of proteins in mouse lens in vivo. The findings are not exactly "unexpected" – yes, cytoskeletal proteins and the few enzymes left over in the lens fiber cells don't turn over, because no proteins there turn over – but they seem to be more comprehensive and quantitative than other existing datasets, and nicely presented, too. The Supplementary file 1 that breaks things down by protein is an important resource for future investigators.

There are a couple of important limitations to this study, which the authors should point out explicitly in discussing their results:

First, the lenses were not separated into cortex vs. nucleus. That's a problem, because in neonate and very young mice the outer regions of the lens have not yet completed their differentiation process (not yet enucleated) – see the figure and references in Bassnett, 2002. So, when the authors observe some turnover in crystallins – notably γ-S crystallin, which is preferentially expressed in the cortical region – that could be due to this subpopulation of cells that are still metabolically active, on the background of much more quiescent nuclear cells. Even in adult animals the lens cortex retains some protein turnover, so it would have been really nice to see them separate the lens capsule from cortex from nucleus and mass spec those separately rather than all together.

Second, there are some limitations in how the results from mice translate to humans, and those should be discussed more. Just off the top of my head: the γ-A, E, F, and N crystallins they mention in the paper are present in mice, but humans don't express them.

Finally, the authors should address the following technical yet important problem. It is known that many old proteins, and certainly the lens crystallins, undergo deamidation (when Gln and Asn are gradually, nonenzymatically converted to Glu and Asp). This modification has been found even in quite young lenses, at least in humans. As it happens, deamidation increases molecular weight of the deamidated residue by 1 Da – the same as if an atom of 15N were incorporated into the side chain in place of 14N. Does the authors' dataset have the resolution to distinguish between deamidated and 15N-amide side chains? And have they looked? There is a tiny difference in molecular weight between the two, but many mass spec peak assignment algorithms by default might ignore it. In case they haven't considered deamidation so far, the authors could go back through their data on low-turnover proteins and see whether the apparent 14N/15N ratios change if all peptides containing Gln or Asn are excluded from the analysis.

https://doi.org/10.7554/eLife.50170.sa1

Author response

The reviewers and I were impressed with the work, but each reviewer also had specific and useful comments for improving the manuscript. Specifically, the data interpretation would be substantially clarified if an analysis could be conducted on the separated nucleus and cortex of the lens. Additionally, the paper would be strengthened with a more critical discussion of the data as it relates to longer lived species and to the existing literature on lens and non-lens protein turnover.

We have incorporated these suggestions in the revised manuscript with the addition of new experimental results, and included more discussion points. During the revision we focused on generating new data to describe the differences between lens cortex and nucleus. The analysis is summarized in the new Figure 3. In addition, the RAW MS data were deposited to MassIVE database (doi:10.25345/C5H09K).

Reviewer #1:

This manuscript examines protein turnover in the mouse lens by heavy atom labelling followed by mass spectrometric proteomic analysis. The results confirm previous findings; many proteins in the lens are long-lived and not subject to turnover, including enzymes. The results are interesting and certainly worthy of publication, but some of the data is difficult to interpret due to the experimental approach and the work is not adequately placed in the larger context of previous work on long-lived proteins in the lens.

1) The major difficulty here arises from examination of the whole, intact lens, which contains fiber cells in various stages of development. Some of these cells will contain a host of functional organelles and others will not. When combined with the excellent sensitivity of mass spectrometry, the detection of protein turnover becomes difficult to interpret. These proteins may originate primarily from the periphery of the lens where the newest fiber cells are still capable of turnover. Therefore the question of whether fully mature fiber cells allow any protein turnover cannot be answered. Separation of the nucleus and cortex would have allowed analysis of mature fiber cells independently.

Both reviewers suggested the separation of the cortex and the nucleus. We have conducted new 15N-based MS experiments on separately extracted cortex and nucleus samples. We retrieved frozen eye globes from previously labeled mice and subjected them to surgical separation of cortex and nucleus tissues. After thawing, the cortex turned ‘mushy’, and we were able to cleanly separate the nucleus that remained rigid from the cortex. We were also able to collect clean cortex free from cross-contamination from the capsule. It was however difficult to harvest clean capsule without contamination from cortex residues on it. Therefore, we only subjected the nucleus and the cortex for proteomic analysis.

We included the new data in Figure 3, in which we presented both 14N/15N MS1-based ratio analysis and total spectra count for longevity and overall abundance of each protein, respectively. We have also updated the Supplementary file 1 to include these new results and added new text in the Materials and methods accordingly.

In our revised text:

In Abstract: “Direct comparison of lens cortex versus nucleus revealed little or no 15N-protein contents in most nuclear proteins, while there were a broad range of 14N/15N ratios in cortex proteins. Unexpectedly, like Crystallins, many enzymes with relatively high abundance in nucleus were also exceedingly long-lived.”

In Results:

“Contrasting difference between the long preservation of proteins in the nucleus and a varying dynamic turnover of cortex proteins in the lens.

Next, we sought to compare protein dynamics in the nucleus and in the cortex of lens. As expected, proteins extracted from the nucleus were mostly shared with their cortex counterparts (Figure 3A and 3B), and a majority of nuclear proteins had little or no protein turnover as determined by their 14N/15N ratios close to or above 100 (Figure 3B: upper limit set at 100). […] When protein abundance of all proteins were compared, the cortex and the nucleus had comparable 14N levels, in contrast to very low new protein contents in the nucleus (Figure 3D, and Supplementary file 1).”

And:

“It is important to note that a majority of these enzymes were still preserved in the nucleus of the lens (Figure 4 and Supplementary file 1) with most of them having predominately 14N contents. This observation strongly indicates active enzymatic activities at the core of the lens attributable to these extremely long-lasting enzymes.”

2) The timescale should also be explicitly discussed in terms of relevance to the human lens. Although 12 weeks is a long time in the normal sense of protein turnover, it is still not very long compared to 50 years that it might typically take for cataract to occur. Some enzymatic activity could persist for a few weeks, but maybe not over decades.

We added a paragraph to the Discussion section to state the limitations of our mouse study, including the comparison of mouse and human age equivalence.

In our revised text:

In Discussion:

“Although the mouse model is our convenience choice for the labeling protocol that is associated with a high cost of 15N-chow, there are notable limitations in addressing the protein basis for cataract. […] Therefore the protein turnover indices only reveal a narrow spectrum of the changes in protein dynamics in the lens, and the observed preservation of redox enzymes in the nucleus core might not last as long as some crystallins at old age.”

3) The detection of long-lived proteins outside the lens is interesting and could use more discussion or elaboration in the figures.

We included a short discussion about long-lived proteins in the sclara, the choroid and the retina. For the reason that a majority of them are extracellular matrix proteins, we didn’t further elaborate them in the figures.

In our revised text:

In Discussion:

“Although we only included other non-lens tissues such as the retina, the sclara and the choroid as controls for having faster turnover dynamics, proteins such as laminin, collagen and fibrillin elastic fibers in these tissues were found to be long-lived (not shown). […] It is however anticipated that 15N pulse-labeling, when the duration is adjusted based on the target tissue, can provide valuable information about protein dynamics, which will be particularly useful in comparing normal and disease tissues for insight on pathogenic transformation or adaptation.”

4) In relation to cataract, the paper only mentions oxidative markers that correlate with cataract. Recent results have also shown that racemization is also higher in cataract. Hooi and Truscott 2011. In connection with this, the activity of enzymes (which is mentioned as an unknown) for combating racemization has also been studied as a function of location and therefore longevity within the lens. Lyon, Sabbah and Julian 2018. Cataract is very complicated and connected to many factors. A broader discussion would be useful.

We thank Dr. Julian for pointing out this caveat, and Dr. Shakhnovich for reminding us of another important modification that we will respond to his point below. We have added new discussion on protein racemization and the potential enzymes involved.

In our revised text:

In Discussion:

“In addition to oxidation in cataract lens, many other biochemical changes also occur. Spontaneous conversion of L- to D-amino acids in proteins contributes to racemization in cataract lens (Hooi and Truscott, 2011), and protein isomerase activities are thought to have a role counteracting cataract development (Lyon, Sabbah and Julian, 2018; Lyon et al., 2019).”

5) It would be valuable to show some of the data for 14N/15N ratios obtained from different peptides for the same protein to allow readers to evaluate the variation in the data. Perhaps the standard deviation for each value could be given in addition to the average.

We revised the Supplementary file 1 to include the ratios of every peptides for each protein to provide the reader a sense of peptide-to-peptide variability. We should also point out that the calculation of the 14N/15N ratio for a protein is more complicated than simply taking the average of all peptides measured. We used “composite ratio” based on reconstituted MS1 chromatograms that are calculated as under-curve-area of the selected peptides (the quantification software automatically selected peptides with high signal intensity for calculating ratios, as described in Materials and methods). Therefore, the composite ratio reflects a “weighted” average of peptides, taking into account that peptides with higher signal intensity provide more reliable measurements.

Reviewer #2:

(This review was written in collaboration with Eugene Serebryany, a postdoc in the lab who is an expert in crystallins).

This is an interesting and important paper which uses an ingenious isotope labeling approach to determine the lifetimes of proteins in mouse lens in vivo. The findings are not exactly "unexpected" – yes, cytoskeletal proteins and the few enzymes left over in the lens fiber cells don't turn over, because no proteins there turn over – but they seem to be more comprehensive and quantitative than other existing datasets, and nicely presented, too. The Supplementary file 1 that breaks things down by protein is an important resource for future investigators.

We thank the reviewer for the recognition of our work and we have expanded Supplementary file 1 to include more quantitation information. Two more supplementary tables were also added with new data generated from cortex and nucleus tissues.

There are a couple of important limitations to this study, which the authors should point out explicitly in discussing their results:

First, the lenses were not separated into cortex vs. nucleus. That's a problem, because in neonate and very young mice the outer regions of the lens have not yet completed their differentiation process (not yet enucleated) – see the figure and references in Bassnett, 2002. So, when the authors observe some turnover in crystallins – notably γ-S crystallin, which is preferentially expressed in the cortical region – that could be due to this subpopulation of cells that are still metabolically active, on the background of much more quiescent nuclear cells. Even in adult animals the lens cortex retains some protein turnover, so it would have been really nice to see them separate the lens capsule from cortex from nucleus and mass spec those separately rather than all together.

This is an important point, and we included new experimental data separately on the cortex and the nucleus (in new Figure 3 and see our response above to review 1 for further details). In the new analysis, we considered 14N/15N ratio and protein abundance, and made additional discussion of γ crystallins in our revised manuscript.

In our revised text:

In Discussion:

“For instance, while α- and β-crystallins (Crya and Cryb) had more balanced presence between cortex and nucleus fractions, γ-crystallin (Cryg) levels in the cortex were very low (Figure 3C). When protein abundance of all proteins was compared, the cortex and the nucleus had comparable 14N levels, in contrast to very low new protein contents in the nucleus (Figure 3D, and Supplementary file 1).”

Second, there are some limitations in how the results from mice translate to humans, and those should be discussed more. Just off the top of my head: the γ-A, E, F, and N crystallins they mention in the paper are present in mice, but humans don't express them!

We thank you for the comment. We were not aware of the distinctions between mouse and human crystallin genes. We now have these nonhuman crystallin isoforms marked in Figure 3 and included this discussion point in the revised manuscript.

In our revised text:

In Discussion:

“Although the mouse model is our convenient choice for the labeling protocol, which is associated with a high cost of 15N-chow, there are a number of limitations in addressing the protein basis for cataract. For instance, certain mouse crystallin isoforms do not express in human (Figure 3C).”

Finally, the authors should address the following technical yet important problem. It is known that many old proteins, and certainly the lens crystallins, undergo deamidation (when Gln and Asn are gradually, nonenzymatically converted to Glu and Asp). This modification has been found even in quite young lenses, at least in humans. As it happens, deamidation increases molecular weight of the deamidated residue by 1 Da – the same as if an atom of 15N were incorporated into the side chain in place of 14N. Does the authors' dataset have the resolution to distinguish between deamidated and 15N-amide side chains? And have they looked? There is a tiny difference in molecular weight between the two, but many mass spec peak assignment algorithms by default might ignore it. In case they haven't considered deamidation so far, the authors could go back through their data on low-turnover proteins and see whether the apparent 14N/15N ratios change if all peptides containing Gln or Asn are excluded from the analysis.

This is a brilliant comment!

We chose to address it at two different levels in our revised manuscript.

1) We discussed limitation of our approach of not including the search of many post-translational modification types, albeit some are ageing related.

2) We also discussed a technical problem in our calculation of old vs. new ratios without including deamidated peptides that are clear more prevalent in the older 14N-proteins.

In our revised text:

In Discussion:

“Related to point that older proteins tend to accumulate post-translational modifications, our mass spec-based approach was not set up to detect all relevant modifications such as non-enzymatic deamidation of Gln and Asn sidechains that occurs more often in old age (Forsythe et al., 2019). This omission of modified peptides would have affected the calculation of 14N/15N ratios, particularly when the types of modifications were more prevalent in the older 14N-proteins.”

In order to precisely assess the impact of protein deamidation on our calculation of 14N/15N ratios, we performed a separate search for deamidated peptides in the 14N channel and have the spectra count values compared to those for unmodified peptides. We summarized the result in Author response image 1, which shows 10.2% peptides being deamidated. This suggest a ~10% underestimation of old 14N-protein quantity in our calculation of the ratios.

We also attempted to run searches for 15N-peptides for deamidation as a form of modification. However, as the reviewer correctly pointed out, it was challenging. This was because deamidation adds 0.98 atomic mass that is too close to the +0.997 dalton difference between the 14N and 15N atoms. For this reason we were unable to distinguish deamidation on a 15N peptide from its unmodified 15N counterpart, given that our MS-MS was performed on a “high-low” setting without the MS2 accuracy for distinguishing 0.997-0.98=0.009 atomic mass.

Author response image 1
Among all ~600 lens 14N-proteins (x-axis), when calculated on the basis of peptide spectra (y-axis), about 10.2% peptides were deamidated (1560 vs. 13703 for deamidated and unmodified peptides).
https://doi.org/10.7554/eLife.50170.sa2

Article and author information

Author details

  1. Pan Liu

    Feinberg Cardiovascular and Renal Research Institute, Feinberg School of Medicine, Northwestern University, Chicago, United States
    Contribution
    Conceptualization, Data curation, Methodology, Project administration
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3066-652X
  2. Seby Louis Edassery

    Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  3. Laith Ali

    Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States
    Contribution
    Data curation, Software, Project administration
    Competing interests
    No competing interests declared
  4. Benjamin R Thomson

    Feinberg Cardiovascular and Renal Research Institute, Feinberg School of Medicine, Northwestern University, Chicago, United States
    Contribution
    Methodology, Project administration
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6565-5866
  5. Jeffrey N Savas

    Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States
    Contribution
    Resources, Supervision, Funding acquisition
    For correspondence
    jeffrey.savas@northwestern.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8173-5580
  6. Jing Jin

    Feinberg Cardiovascular and Renal Research Institute, Feinberg School of Medicine, Northwestern University, Chicago, United States
    Contribution
    Conceptualization, Resources, Data curation, Supervision, Funding acquisition, Methodology, Project administration
    For correspondence
    jing.jin@northwestern.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7023-5305

Funding

National Institutes of Health (R01AG061787)

  • Jeffrey N Savas

National Institutes of Health (R21AI131087)

  • Jing Jin

National Institutes of Health (R01EY025799)

  • Jing Jin

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We are grateful to Dr. Amani Fawzi for her suggestions to the study, and Dr. Hongwen Zhou for assisting data analysis. This study was supported by National Institutes of Health (R01AG061787, to JNS, and R01EY025799 and R21AI131087, to JJ).

Ethics

Animal experimentation: All animal procedures were approved by Institutional Animal Care and Use Committee of the Northwestern University (approved protocol number IS00000429 and IS00000862).

Senior Editor

  1. Michael A Marletta, University of California, Berkeley, United States

Reviewing Editor

  1. Jeremy Nathans, Johns Hopkins University School of Medicine, United States

Reviewers

  1. Ryan Julian, UC Riverside, United States
  2. Eugene I Shakhnovich, Harvard University, United States

Publication history

  1. Received: July 12, 2019
  2. Accepted: December 4, 2019
  3. Accepted Manuscript published: December 10, 2019 (version 1)
  4. Version of Record published: December 16, 2019 (version 2)

Copyright

© 2019, Liu et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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