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. 2020 Oct 26;15(10):e0240829. doi: 10.1371/journal.pone.0240829

Targeted detection and quantitation of histone modifications from 1,000 cells

Nebiyu A Abshiru 1, Jacek W Sikora 1, Jeannie M Camarillo 1, Juliette A Morris 1, Philip D Compton 1, Tak Lee 2, Yaseswini Neelamraju 3, Samuel Haddox 3, Caroline Sheridan 2, Martin Carroll 4, Larry D Cripe 5, Martin S Tallman 6, Elisabeth M Paietta 7, Ari M Melnick 2, Paul M Thomas 1, Francine E Garrett-Bakelman 2,3,8,*, Neil L Kelleher 1,*
Editor: Charles Michael Greenlief9
PMCID: PMC7588077  PMID: 33104722

Abstract

Histone post-translational modifications (PTMs) create a powerful regulatory mechanism for maintaining chromosomal integrity in cells. Histone acetylation and methylation, the most widely studied histone PTMs, act in concert with chromatin-associated proteins to control access to genetic information during transcription. Alterations in cellular histone PTMs have been linked to disease states and have crucial biomarker and therapeutic potential. Traditional bottom-up mass spectrometry of histones requires large numbers of cells, typically one million or more. However, for some cell subtype-specific studies, it is difficult or impossible to obtain such large numbers of cells and quantification of rare histone PTMs is often unachievable. An established targeted LC-MS/MS method was used to quantify the abundance of histone PTMs from cell lines and primary human specimens. Sample preparation was modified by omitting nuclear isolation and reducing the rounds of histone derivatization to improve detection of histone peptides down to 1,000 cells. In the current study, we developed and validated a quantitative LC-MS/MS approach tailored for a targeted histone assay of 75 histone peptides with as few as 10,000 cells. Furthermore, we were able to detect and quantify 61 histone peptides from just 1,000 primary human stem cells. Detection of 37 histone peptides was possible from 1,000 acute myeloid leukemia patient cells. We anticipate that this revised method can be used in many applications where achieving large cell numbers is challenging, including rare human cell populations.

Introduction

Histone post-translational modifications (PTMs) are essential for epigenetic regulation and maintenance of major DNA metabolic processes such as replication, transcription, and chromatin remodeling [1,2]. The most common histone PTMs include acetylation, methylation, ubiquitination and phosphorylation [3]. These PTMs control gene expression by directly modifying the chromatin structure and/or by providing a docking site for the recruitment of other chromatin modifying complexes [4]. For instance, acetylation of histone H4 K16 promotes gene expression by inhibiting chromatin condensation and formation of higher order chromatin fibers [5]. In contrast, trimethylation of histone H3 K9 is widely known to promote gene silencing via chromatin compaction [6,7]. Disruption of basal levels of histone modifications can lead to genome instability and abnormal gene expression. This has been shown in yeast and human studies where defective H3 K56 acetylation led to spontaneous DNA damage and sensitivity to genotoxic stress [8,9]. Moreover, while normal cells have dedicated control mechanisms for maintaining the steady-state levels of histone PTMs, a number of malignant cells have been shown to possess globally altered histone PTM patterns [10–12]. For example, abnormal levels of H3 K4 and H3 K79 methylations were found in a number of acute leukemias [13–15]. These studies suggest the critical roles histone PTMs play in the development and progression of cancer, but also indicates their potential as biomarkers and therapeutic targets for cancer diagnosis, monitoring and/or treatment.

The identification and quantification of histone PTMs is crucial to understand their molecular function in health and disease. Traditionally, analysis of histone PTMs is performed by immunochemical techniques, such as western blots or ELISAs, which requires the development of PTM- and peptide-specific antibodies. The disadvantages of these techniques are three-fold. First, the approach relies heavily on the prior knowledge of the type and position of the modification of interest. For example, antibodies can rarely be used to discover new sites of modification, but are rather used to detect and quantify a previously known PTM. Additionally, the specificity of antibodies against distinct sites and modifications remains a challenge due to significant cross-reactivity with other PTMs [16]. Finally, antibodies directed towards specific histone PTMs may fail to properly bind due to the presence of nearby PTMs disrupting or inhibiting their interaction [17]. These pitfalls reveal the need for unbiased approaches for quantifying histone PTMs.

Over the last decade, mass spectrometry (MS) has emerged as a powerful tool for characterization and quantitation of site-specific and global levels of histone PTMs. MS offers several advantages including reproducibility, specificity, and ability to rapidly measure numerous PTMs in a single experiment [18]. Previous work from our group and others has utilized both discovery and targeted approaches for the detection and quantitation of histones PTMs by bottom-up, middle-down, and top-down proteomics. These methods have been used to assess endogenous PTM turnover [19–21], to determine PTM dynamics throughout the cell cycle [22], and to examine changes in PTMs in disease states [23,24].

Our ability to reliably detect and quantitate histone PTMs by MS can be affected by various methodological choices. Sample preparation is one of the critical factors that can affect efficient detection of histone peptides via MS. Histone proteins exhibit unique chemical properties, which makes their isolation from biological samples a relatively simple task. Typically, for high throughput MS analysis histone proteins are isolated from a million or more cells, to yield sufficient material for multiple LC-MS/MS injections. However, this methodology is not applicable for the study of clinical samples with limited cells. Consequently, it is very important to assess the compatibility of existing histone assay methodologies and technologies for these types of applications. In the current study, we investigated the scalability of the input material by modifying the standard histone assay protocol to enable histone isolation from across a range of cell amounts. A translational application for use of this method is in clinical studies, where there may be limitations in the number of cells available for analysis. We demonstrated the scalability using histone proteins isolated from HeLa-S3 cells ranging in number from 103 to 106 by eliminating nuclear isolation and reducing the number of propionylation steps (S1 Fig). Our results exhibit capability of the improved protocol to detect and quantify 61 histone peptides from 1,000 primary human bone marrow cells and 37 peptides in malignant cells from Acute Myeloid Leukemia (AML) patients. We anticipate that the new approach presented in this work will open a new frontier for MS-based applications in biomedical and translational research.

Materials and methods

Cell samples

HeLa-S3 cells were purchased from the National Cell Culture Center. Human bone marrow CD34+ cells from healthy donors (NBMs) were purchased from Stemcell Technologies Inc. (Vancouver, Canada; n = 3). AML samples were obtained from the University of Pennsylvania (N = 3: AML1245, AML2093 and AML2373), and the ECOG-ACRIN group (N = 3 from NCT00046930: 5646646, 6815914 and 9600462). Patients provided informed consent according to the Declaration of Helsinki for collection and use of sample materials in IRB-approved research protocols at Weill Cornell Medicine, the University of Virginia and the University of Pennsylvania. Samples were subjected to Ficoll separation on the day of collection, and mononuclear cells were viably frozen. Cell were thawed at 37°C in high-protein medium, treated with 1:10 volume of DNase (1mg/mL, Sigma-Aldrich, St. Louis, MO, USA), washed with PBS at 4°C, and depleted of CD3+ and CD19+ cells using magnetic beads per manufacturer’s recommendations (Miltenyi Biotec, Bergisch Gladbach, Germany). The myeloid enriched cells were washed in PBS at 4°C and cell pellets were flash frozen on dry ice and stored at -80°C until use.

Histone extraction

Histone extraction was performed as described previously with some modifications [23]. Cell pellets were lysed directly with 0.2 M H2SO4 or with nuclear isolation buffer, NIB (15 mM Tris, 60 mM KCl, 15 mM NaCl, 5 mM MgCl2, 1 mM CaCl2, 250 mM sucrose, 0.4 mM 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride, 10 mM sodium butyrate, 0.3% Nonidet P-40 and 1 mM dithiothreitol, pH 7.5). The nuclear pellet isolated with the latter approach was subsequently washed twice with NIB without detergent and resuspended in 0.2 M H2SO4, which extracts histones and other acid-soluble proteins. Trichloroacetic acid was added to a final concentration of 20% v/v to the supernatants that contained histones. The isolated histones were washed first with 0.1% HCl in acetone, washed twice with acetone, and then air-dried in a chemical fume hood.

Histone propionylation and in-solution tryptic digestion

The propionylation reaction and tryptic digestion were adapted from previous works [20,25]. Histones were subjected to one or two rounds of propionylation before and after tryptic digestion. The dried histone pellet was resuspended in 5 μL of 0.1 M NH4HCO3 and mixed with 20 μL of freshly prepared 3:1 (v/v) isopropanol: propionic anhydride mixture. The solution was adjusted to pH 8 by adding multiple rounds of 5 μL aliquots of concentrated NH4OH solution (28% NH3 in water). The pH of the sample was measured at each addition of NH4OH by spotting 0.2 μL on a pH indicator strip. The sample was then incubated at 50 oC for 1 h for one round of propionylation or for 20 min for two rounds of propionylation. The sample was completely dried in a SpeedVac concentrator following each round of propionylation. After the derivatization, histones were digested with 0.5 μg of trypsin at 37°C overnight. Then, after an additional one or two rounds of propionylation, the digest was resuspended in 0.1% TFA prior to MS analysis.

Proteomic analysis and data handling

Histone peptides and the standard peptide mix were analyzed on triple quadrupole MS (ThermoFisher Scientific TSQ Quantiva) directly coupled with UltiMate 3000 nano-LC system. Peptides were first loaded onto an in-house packed trapping column (3 cm × 150 μm) and then separated on New Objective (Woburn, MA) PicoChip analytical column (10 cm × 75 μm). Both columns were packed with Bischoff ProntoSIL C18-AQ, 3 μm, 200 Å resin (New Objective). The chromatography gradient was achieved by increasing percentage of buffer B from 0 to 35% at a flow rate of 0.300 μl/min over 45 minutes. Solvent A: 0.1% formic acid in water, and B: 0.1% formic acid in 95% acetonitrile. The instrument settings were as follows: collision gas pressure of 1.5 mTorr; Q1 peak width of 0.7 (FWHM); cycle time of 2 s; skimmer offset of 10 V; electrospray voltage of 2.5 kV. Targeted analysis of unmodified and various modified histone peptides was performed using collision-induced dissociation. All transitions (S7 Table) are previously published [19,20]

Raw MS files were imported and analyzed in Skyline software with Savitzky-Golay smoothing [26]. All Skyline peak assignments were manually confirmed. Peptides were considered to be detected if the signal to noise ratio was above 3 and quantifiable and there was at least one modification state detected in addition to the unmodified peptide. Peptide peak areas from Skyline were imported into an in-house built software to plot bar graphs representing relative abundances of each histone modifications. The relative abundances were determined based on the mean of biological replicates with error bars showing standard deviation. For each biological replicate, one technical replicate was acquired, with the exception of data acquired for 1×106 cells which had three technical replicates. Peptide modifications are abbreviated as un (unmodified), me1 (monomethyl), me2 (dimethyl), me3 (trimethyl), and ac (acetyl).

Real-Time quantitative polymerase chain reaction

SETDB1 mRNA levels was assessed by Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) using HPRT1 and ACTB as endogenous controls in AML specimens. Briefly, RNA was extracted using the AllPrep DNA/RNA Mini Kit (Qiagen, Hilden, Germany). Reverse Transcription was carried out at 42˚C for 1 hour using 100 ng of total RNA, M-MuLV Reverse Transcriptase (NEB, Ipswich, MA), and a 3:1 mixture of random hexamers (ThermoFisher), to Anchored Oligo-dT, (IDT, Coralville, IA). Subsequently, cDNA was diluted 10-fold and 3 μl of diluted cDNA was used in each 10 μl RT-qPCR reaction. RT-qPCR reactions were setup using 2x Hot-Start Taq Master Mix (NEB), EvaGreen Intercalating Dye (Biotium, Fremont, CA), and the following PrimeTime® Primers from IDT: SETDB1 (Hs.PT.58.25313824), HPRT1 (Hs.PT.58v.45621572), and ACTB (Hs.PT.38a.22214847). RT-qPCR was performed using the CFX384 Touch™ Real-Time PCR Detection System and CFX Maestro software (Bio-Rad, Hercules, California). Relative Quantitation of setdb1 mRNA was performed using the model defined in Pfaffl [27].

Statistics

All values are reported as the mean ± one standard deviation. ANOVA was used with a Bonferroni correction to test for statistical significance at a p-value <0.05. Analysis of covariance (ANCOVA) was used to determine statistical significance in the coefficients of variation (CV).

Results

Effect of nuclear isolation step for low cell numbers

Typical histone extraction methods rely on nuclear extraction buffer containing mild, non-ionic detergents for cell lysis followed by successive washes and centrifugation for isolation of intact nuclei [25]. After every washing step, nuclei are pelleted by low-speed centrifugation (i.e., 600 x g) and the supernatant is removed. Although this protocol has been successfully employed in a wide range of epiproteomic studies in our research group and others [21,23,28], its feasibility for quantifying the abundance of histone PTMs in low input samples has not been investigated. In the current study, we compared the MS-based quantification of histone samples obtained after acid extraction of isolated nuclei and after direct acid extraction of whole cells. Histone peptides generated from 1×104 and 5×104 HeLa-S3 cells were subjected to targeted LC-MS/MS. For samples with 1×104 cells, a significant increase in the extracted peak area was observed for 12 of the 89 quantifiable HeLa-S3 histone peptides in samples prepared without nuclear isolation (Fig 1A, S1 Table). No significant increases were observed at 5×104 cells (S2A Fig). The average peak area for all the peptides at 1×104 and 5×104 cells increased by 2.6- and 1.8-fold, respectively, with the omission of the nuclear isolation step. Furthermore, assessment of the coefficient of variation (CV) for each peptide at both 1×104 (Fig 1B) and 5×104 cells (S2B Fig) revealed that, while there is a significant difference in the variation of the CV values with and without the nuclear isolation, the samples without nuclear isolation show greater consistency across the dynamic range of peak areas (S3A and S3B Fig). These results suggest that elimination of the nuclear isolation step affords an increase in peptide peak area for low cell number samples without contributing to increased variance across samples.

Fig 1. Histone peptide detection with or without nuclear isolation.

Fig 1

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Comparison of (A) extracted peak area of histone peptides and (B) percentage CV values of 29 representative histone peptides from 1×104 cells with or without nuclear isolation step. Error bars represent the standard deviation of biological triplicates. Asterisks (*) represent statistical significance at a p-value <0.05 using ANOVA with a Bonferroni correction.

Reduced propionylation steps of histones improves MS signal

Propionylation of unmodified and monomethylated lysine residues is necessary to reduce digestion of lysine-rich histones by trypsin and creates consistent peptides for quantitation. Chemically, the addition of the propionyl group increase the hydrophobicity of the hydrophilic histone peptides, causing an increase in retention time to allow for adequate separation. The standard histone preparation protocol is time-consuming, typically requiring multiple days of sample preparation. Additionally, the protocol is prone to significant sample loss during pH measurement, undermining its compatibility for sample-limited applications. To limit sample loss, we compared the effects of one versus two rounds of histone propionylation from 1×106 HeLa-S3 cells. The result showed a significantly higher signal intensity for 56 of the 89 histone peptides which were quantifiable with one round of propionylation compared to two rounds (Fig 2A, S1 and S2 Tables). On average, there was a 4.2-fold increase in the extracted peak area of peptides detected with one round of propionylation. Further, quantitation of histone PTMs for histone H3.1 K27 and K36 show no differences in the relative abundance of each modification state between one and two rounds of propionylation (Fig 2B). Some peptides, such as H3.3 K27ac K36un, were observed in samples with one round of propionylation but not with two rounds (S4 Fig). These results show that one round of propionylation contributes to an overall signal increase while still yielding similar results for most PTMs.

Fig 2. Peptide peak area comparison of one versus two rounds of histone propionylation.

Fig 2

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(A) Extracted peak area of one vs two rounds of propionylation for representative histone marks. Histones were acid-extracted from 106 HeLa cells and subjected to one or two rounds of propionylation (N = 4). (B) Bar graphs showing the relative abundances of histone marks. Both propionylation strategies result in comparable relative abundances. Asterisks (*) represent statistical significance at a p-value <0.05 using ANOVA with a Bonferroni correction.

Assessment of the scalability of input material for histone assay

By combining the methodological improvements noted above, we next sought to assess the effects of relative measurements on fewer cells. Serial dilutions of HeLa-S3 cells down to 1×103 cells were directly acid extracted to isolate histones and subjected to one round of propionylation before and after tryptic digestion. Resulting peptides were resuspended in equal volumes and equal injection volumes were loaded onto the analytical column for separation followed by targeted LC-MS/MS analysis. Comparison of the peak intensity shows an overall ~1.4 fold-change in signal between 1×103 and 1×106 cells for both H3.1 K27un K36me2 (Fig 3A and 3B) and H3.1 K27me3 K36un (Fig 3C and 3D). Of the 89 histone peptides quantifiable at 1×106 HeLa-S3 cells, 61 peptides were quantifiable at 1×103 cells (Table 1 and S3 Table).

Fig 3. Lowering the input cell amount for assessment of histone marks.

Fig 3

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HeLa-S3 cells were diluted to obtain a range between 106 and 103 cells. Following preparation, all samples were resuspended in equal volumes and injected in equal amounts for targeted LC-MS/MS. Peak area comparison of representative histone marks generated from 103−106 HeLa-S3 cells for (A) H3.1 K27un K36me3 and (C) H3.1 K27me3 K36un. Representative chromatograms are shown on the right of each panel for (B) H3.1 K27un K36me3 and (D) H3.1 K27me3 K36un. Samples are shown as the number of cells and the replicate number.

Table 1. Peptides quantified at 1000 cells.

Peptide HeLa NBMs AML Peptide HeLa NBMs AML
H4 K5un K8un K12un K16un X X X H3 K9un K14un X X X
H4 K5un K8un K12un K16ac X X X H3 K9un K14ac X X X
H4 K5un K8un K12ac K16ac X X H3 K9me3 K14un X X
H4 K5un K8ac K12un K16ac X X X H3 K9me3 K14ac X X
H4 K5un K8ac K12ac K16ac X X H3 K9me2 K14un X X X
H4 K5ac K8un K12un K16un X X X H3 K9me2 K14ac X X X
H4 K5ac K8ac K12un K16un X X H3 K9me1 K14un X X X
H4 K5ac K8ac K12ac K16un X X H3 K9me1 K14ac X X X
H4 K5ac K8ac K12ac K16ac X X H3 K9ac K14ac X
H3.1/2 K27un K36un X X X H3.3 K27un K36un X X
H3.1/2 K27un K36me3 X X X H3.3 K27un K36me3 X X X
H3.1/2 K27un K36me2 X X X H3.3 K27un K36me2 X X X
H3.1/2 K27un K36me1 X X X H3.3 K27un K36me1 X X
H3.1/2 K27me3 K36un X X X H3.3 K27un K36ac X X
H3.1/2 K27me3 K36me2 X X H3.3 K27me3 K36un X X X
H3.1/2 K27me3 K36me1 X X X H3.3 K27me3 K36me1 X X
H3.1/2 K27me2 K36un X X X H3.3 K27me2 K36un X X X
H3.1/2 K27me2 K36me3 X X H3.3 K27me2 K36me2 X X
H3.1/2 K27me2 K36me2 X X H3.3 K27me2 K36me1 X X
H3.1/2 K27me2 K36me1 X X X H3.3 K27me1 K36un X X
H3.1/2 K27me1 K36un X X X H3.3 K27me1 K36me3 X X X
H3.1/2 K27me1 K36me3 X X X H3.3 K27me1 K36me2 X X X
H3.1/2 K27me1 K36me2 X X X H3.3 K27me1 K36me1 X X
H3.1/2 K27me1 K36me1 X X X H3.3 K27me1 K36ac X X
H3 K79un X X X H3 K18un K23un X X X
H3 K79me1 X X X H3 K18un K23ac X X X
H3 K79me2 X X X H3 K18ac K23un X X X
H4 K20un X X H3 K18ac K23ac X X X
H4 K20me1 X X X H3 K4un X X
H4 K20me2 X X X H3 K4me1 X X
H4 K20me3 X X
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HeLa, NBMs, and AML specimens (103 cells each) were prepared according to the modified method and analyzed by LC-MS/MS. Quantifiable peptides for each cell types are marked with an X.

Determination of histone modifications from primary human cells

To assess if the modified method is translatable to primary human specimens, we first applied the approach to human CD34+ progenitor cells obtained from bone marrow of healthy donors (NBMs). As these represent rare cells in the bone marrow, a method geared towards low cell number inputs would benefit the study of histone PTMs present in this cell type and other rare populations. Using the modified method with an input of 1×103 cells, all peptides detected in HeLa cells were also detected in NBMs, along with one additional peptide, H3 K9ac K14ac (Table 1, S4 Table and S5 Fig). Representative chromatograms show defined peaks for H3 K9me1 K14ac, H4 K5un K8un K12un K16ac, H3 K18un Q19un K23ac, H3 K79un, H3.1/2 K27me1 K36me2, and H3.3 K27me1 and K36un (Fig 4).

Fig 4. Quantitation of histone modifications from 1000 primary human NBMs.

Fig 4

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Representative chromatograms of modified histone peptides from 103 human normal bone marrow CD34+ cells (N = 3).

Finally, we determined the abundance of histone PTMs in malignant cells from AML patients. We used the revised protocol to determine the relative abundance of histone PTMs in six AML patients at 1×106 cells. Levels of H3 K9me2 and H3 K9me3 were high in a subset of three AML patients while low in the second subset of three AML patients (Fig 5A and S5 Table). We considered the possibility that the difference in H3K9 methylation levels could be associated with differences in expression of SETDB1, a histone lysine methyltransferase of the H3 K9 residue [29]. We performed quantitative PCR to assess for mRNA transcript levels of SETDB1 in the AML specimens. We observed a difference in the relative mRNA transcript levels of SETDB1 between the groups (S6 Fig). SETDB1 mRNA was higher on average in patients with increased H3 K9me2/3, suggesting a regulatory role for SETDB1 and/or H3 K9 methylation levels in the AML specimens investigated. Next, we assessed for the detection of histone PTMs in 1×103. Cells from three AML patients were prepared according to the modified method and 37 peptides were quantifiable in the proteomic analysis from 1×103 malignant cells (Table 1 and S6 Table). Representative chromatograms of modified histone peptides are plotted in Fig 5B.

Fig 5. Histone PTMs in AML patient specimens.

Fig 5

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(A) Heatmap of relative histone modification levels detected in 106 cells. (B) Histones were extracted directly by acid extraction from 103 AML patient cells and subjected to one round of propionylation before and after tryptic digestion. Shown are representative chromatograms of modified histone peptides.

Discussion

In this study, we assessed the feasibility of reducing the sample processing steps for preparation of histone peptides for targeted LC-MS/MS to enable analysis of very low cell number samples. Prior work by Garcia et al. [25] is considered the gold standard for sample preparation of histones for bottom-up analysis. While this protocol provides reliable results from as little at 1 μg of protein, those amounts may be difficult or impossible to obtain for some clinical and translational applications. Further advancement of the method into the “one-pot” approach eliminated the need for off-line purification of histones [30], opening the door to the possibility of reduced sample amounts due to reduced sample loss during individual histone isolation.

There is great interest in understanding histone PTM profiles in rare cell populations, including malignant and non-malignant sources, for both basic and clinical research. A critical need for the analysis of clinical samples is the ability to obtain high quality data from low sample inputs. Indeed, analysis of histones from low cell numbers has been the focus of multiple publications in recent years. In 2018, Gou et al. [31] was able to analyze histones from 50,000 cells from both cell lines and primary cells using low resolution mass spectrometry. This represents a significant reduction in the number of cells needed for quantitative analysis of histone modifications compared to prior publications.

Additional methodological baselining has been performed on clinical specimens, both from primary cells and patient tissues. Recent work from Noberini et al. [32] established 5×105 cells as a reliable amount for quantitation of histone modifications from primary cells, translating to less than 10 μg of histone octomers. Similar cell numbers are needed for histone analysis from FFPE tissue collected by laser capture microdissection through the pathology tissue analysis of histones by mass spectrometry approach, or PAT-H-MS [33]. These low histone amounts have also been applied to normal and tumor specimens, establishing that 2–5 μg of histone proteins are needed to obtain quantifiable results.

The approach we outline here is a further improvement to the above referenced methods to enable quantitation of histone PTMs from as low as 1000 primary cells. Exclusion of the nuclear isolation step resulted in a 2.6-fold improvement in the detection of several histone PTMs, with significant advantages seen at very low cell numbers (Fig 1A). Reducing the number of propionylations resulted in additional improvements in signal intensity (Fig 2A). It is important to note, however, that the revised protocol performs better for low cell number samples and fewer advantages are seen at higher cell numbers. At 50,000 cells, the amount used by Guo et al. [31], no benefit was observed when using our modified protocol (S1A Fig). Use of the traditional preparation methods, with nuclear isolation and increased propionylations, may be more applicable for larger starting amounts.

This research aids to expand the scope of “multi-omics,” especially with the focus on cancer. Single cell genomic applications are regularly used, such as single cell RNA-Seq [34] and single nucleus RNA-Seq [35]. The field of metabolomics is also geared towards very low cell numbers. Metabolomics is capable of analyzing 100 breast cancer cells [36] to as low as single cells for specific metabolites, such as glucose phosphate [37]. Lipidomics has been applied to fewer than 100 cells with LC-ESI-MS/MS [38]. High quality data from low cell numbers have been difficult to acquire by LC-based proteomics, but advancements in instrument sensitivity along with modifications in sample preparation as outlined here can provide useful results to better align with the capabilities of other “multi-omic” approaches.

One area where this approach can be readily utilized is the profiling of hematologic malignancies. Multiple aberrations in histone PTMs have been observed in leukemias and lymphomas, such as EZH2 mutations altering H3 K27 methylation [39], DOT1L dysregulation of H3 K79 methylation with MLL translocations [40], and KMT2D mutations affecting H3 K4 methylation [41]. Detection of histone PTMs could not only be applicable to disease prognosis as shown in solid tumors [11,42], but could also provide insight about potential biological mechanisms of disease facilitated by epigenetic mediators. Within AML, epigenetic modifiers are known to play a role in the pathogenesis of disease in a subset of AML patients, with more than a dozen enzymes dysregulated in AML contributing to alterations in histone PTMs [43].

Application of our revised method to AML patient specimens showed a difference in H3 K9me3 across two subsets of AML samples (Fig 5). This difference in H3 K9me3 was consistent with the mRNA levels of SETDB1 (S6 Fig), the enzyme responsible for trimethylation of H3 K9, suggesting that the loss of SETDB1 results in the reduction of H3 K9me3. Alterations in H3 K9me3 have previously been seen in AML, showing a reduction in this modification specifically in promoter regions [44]. Recently, SETDB1 was shown to play a significant role in survival in AML, with patients exhibiting higher SETDB1 mRNA levels experiencing increased survival times (median of 26.3 months in SETDB1 high vs 9.5 months in SETDB1 low) [45]. The limited data presented suggests an approach to identifying patients from limited materials with aberrant H3 K9me3 and associated SETDB1 expression which may contribute to disease pathogenesis and survival. It is important to note, however, that the data in this field are still developing and there is no clear consensus at to the role of H3 K9me3 or SETDB1 in AML. While the underlying biology is still under investigation, our data show that a revised sample histone preparation can be applied to sparse clinical samples to better understand how histone PTMs are altered across individuals.

Conclusions

Sample limitations represent a significant challenge for the translation of proteomics to the clinic and methods need to be modified to utilize this material. We have described a modified method for quantifying histone modifications from samples with limited material. This approach may allow use of residual samples from clinical diagnostics for research, and/or rare cell populations, to assess for potential disease biomarkers and hypotheses related to mechanisms of disease.

Supporting information

S1 Fig. Schematic overview comparing the standard preparation protocols with the modified procedure.

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S2 Fig. Elimination of nuclear isolation in 5×104 cells.

Comparison of (A) extracted peak area of histone peptides and (B) percentage CV values of histone peptides from 5×104 cells with and without the nuclear isolation step. Error bars represent the standard deviation of two instrument replicates within a single experiment.

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S3 Fig. Variation in CV with and without nuclear isolation.

Log10 of peak area for each cell number was plotted with log10 of the coefficient of variation (CV). (A) 1×104 cells show the same slope with (red) and without (green) nuclear isolation and a statistically significant difference in the lines (p = 6.055e-6), but not the slopes (p = 0.4254) by analysis of covariance (ANCOVA). (B) 5×104 cells show different slopes with (red) and without (green) nuclear isolation and a statistically significant difference in the lines (p<2.2e-16) and slopes (p = 0.001876) by ANCOVA.

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S4 Fig. Reduction in propionylations rounds reveals peptides from 1×104 cells.

Skyline extracted peaks for H3.3 K27ac K36un shows the presence of the peptide in one round of propionylation and absent in two rounds.

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S5 Fig. Modified protocol reveals H3 K9K14 peptide at 1×103 cells.

Comparison of H3 K9ac K14ac peptide in HeLa (left) and NBM (right) shows the presence of the peptide in NBM but not HeLa.

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S6 Fig. Correlation of histone modifications with RNA transcript levels.

Relative SETDB1 mRNA levels as determined by qPCR in three samples with low H3K9me2/3 (red) and three samples with high H3K9me2/3 (blue).

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S1 Table. Percent relative abundance of histone PTMs with and without nuclear isolation prior to histone extraction.

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S2 Table. Percent relative abundance of histone PTMs with one or two rounds of propionylation.

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S3 Table. Percent relative abundance of histone PTMs at a range of HeLa cell numbers.

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S4 Table. Percent relative abundance of histone PTMs in CD34+ normal bone marrow.

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S5 Table. Percent relative abundance of histone PTMs in primary AML patient specimens at 1,000 cells.

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S6 Table. Percent relative abundance of histone PTMs in primary AML patient specimens.

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S7 Table. Complete list of transitions used in data acquisition.

(XLSX)

Click here for additional data file. (19.2KB, xlsx)

Acknowledgments

The authors thank Richard LeDuc for helpful discussions on this work.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was carried out with a financial support from The Paul G. Allen Family Foundation (Award # 11715), NCI CCSG P30CA060553 awarded to the Robert H. Lurie Comprehensive Cancer Center, and the National Resource for Translational and Developmental Proteomics supported by P41GM108569 to NLK. We would also like to acknowledge funding from NCI K08CA169055, UVA Cancer Center through the NCI Cancer Center Support Grant P30CA44579, the University of Virginia and the American Society of Hematology (ASHAMFDP-20121) under the ASH-AMFDP partnership with The Robert Wood Johnson Foundation to FEG-B. This study was conducted by the ECOG-ACRIN Cancer Research Group (Peter J. O'Dwyer, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award numbers: CA180827, CA180820, CA233290, CA189859, CA233321, CA233270. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Charles Michael Greenlief

11 Jun 2020

PONE-D-20-14092

Targeted detection and quantitation of histone modifications from 1,000 cells

PLOS ONE

Dear Dr. Kelleher,

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Reviewer #3: I Don't Know

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Reviewer #1: The paper entitled "Targeted detection and quantitation of histone modifications from 1,000 cells" from Kelleher’s group is an interesting and well-planned research on the improvement of sample preparation for histone PTM study. The manuscript is good as for contents, methodology and data analysis, the writing style and the clarity of the exposition are accurate. Conclusions are clear and Ref list is complete and correct. I have no specific concern but it is mandatory to explain/correct the manuscript in some points:

· Fragment type (CID or HCD) should be provided in the method part.

· Authors claimed that serial dilutions were used to make sure HeLa-S3 cells down to 1×103 cells. Why don’t use flow cytometry here?

· Heatmap in the Figure 5A is missing. b and y ions should be labeled in the Figure 5B.

· b and y ions in the Figure 4- are these from unique peptides? Any evidences to support the localization of Me/Ac on the K? Representative MS2 should be provided here.

Reviewer #2: The author in this paper primarily demonstrated the detection of histone peptides from limited number of cells using a targeted LC-MS/MS approach. This paper is interesting and certainly has potential applications towards proteomics at few or even single cell level. Combined with previous publications such as Luo et. Al., Anal. Chem. 2017, 89, 21, 11664–11671, it becomes feasible to pursue multi-omics research with under 1000 cells, which will potentially resolve unique properties of rare population of cells. In this regard, I think this paper is significant, and meets the journal standard for publication, although it lacks originality (i.e., modified protocols are reported).

Additionally, it would be helpful for the author to have a discussion on how this work relates to current multi-omics research, and further demonstrate its capability to study particular type of cells of interest.

Reviewer #3: In this manuscript Abshiru et al. present work that improves the sensitivity on a number of cells analyze basis for proteomic quantitation of histone PTMs. The key step is skipping nuclei isolation for cell numbers less than 1x10^4 and disposing of additional rounds of derivitization. This makes significant advances in sensitive histone proteomic analysis for limited samples in a variety of applications. The overall quality of the work is very good if spotty in places and I am confident in its publication in the near future. There are a few issues that unfortunately preclude its expedited publication without an additional round of review.

Major issues:

1) Figure 5 is missing and has not been peer reviewed. This is the crucial data conveying any actual biological insight. These results are also poorly described in text and no statistical analysis is presented for the interpretation and focus on specific results.

2) The manuscript fails to put this work in proper context from an analytical perspective. The improvement is compared relative to a 13 year old paper with no mention of improvements or comparison to recent work.

3) The discussion of the biological results is near-completely absent and is lacking context as well.

4) There are some major issue around the statistical interpretation of figure 1, given the apparent use of instrument technical replicates on single samples to infer significance of differences between the workflows.

Statistics:

The authors are generally clear and transparent about the use of statistics; however, there is some questionable apples-to-oranges interpretation of the statistics.

In text comments:

88

“However, this methodology is not applicable for the study of clinical samples with limited cells.” – This claim is overstated. A million cells or even a few million cells are a feasible number for many clinical applications. Yes, this is true for some, or even many, clinical applications as well as some basic science questions. Certainly, sensitivity gains are broadly useful.

202

The data does not support these statements. Unless I missed something, the variances used for the statistics are technical and thus do not infer a statistically meaningful difference between the workflows. These results say that your instrument variance is smaller than the difference between these two samples. Repeating the workflow to measure the workflow variance would be necessary to make these statements. I think you could make more general claims of similarity. They certainly look similar and the data has not been obviously compromised by the new workflow.

219

“The standard histone propionylation protocol is time-consuming, typically requiring multiple days of sample preparation.” – Days, really? This only takes minutes of actual work and perhaps a few hours overall. Perhaps you are referring to from cells to the mass spec?

258

The use of the word “asses” is inappropriate.

274

“Histone PTMs’ assessment in 1×106 cells was performed in six patients.” – Rewrite this sentence

275

“We identified consistent levels of H3 K9me2 and H3 K9me3 between two patient groups (Fig 5A and S5 Table).” – Figure 5 does not appear to be the correct figure to cite here. Also this sentence is followed by “We considered the possibility that the difference in H3 K9me levels could be…” The meaning of these two sentences is unclear. “consistent between two patient groups” and “the different in…” do not follow each other. Certainly there is some point that is not clear. This is a significant crux of the paper regarding any biological insight and it is completely unclear.

286

Again, there is a misplaced figure. I see no heat maps in any of the main figures. This makes it hard to review the results.

291

Table 1 is titled as “identified” but the caption calls them “quantifiable”. There is a difference.

299

The paper cited is certainly important. It is an early effort that made important methodological innovations for histones. However, the use of the Gold standard moniker here seems misguided. Perhaps it is in the sense that it set a marker down of 1ug and is a good point of comparison in the distant past. Making a comparison to this work with respect to sensitivity is misleading. Dramatic improvements in sensitivity have been made in the intervening 13 years. Notably the introduction of the one-pot approach just a couple years later, which skips the HPLC purification step and analyzes the entire acid soluble fraction collectively, as is common today, dramatically improved the sensitivity. (J Proteome Res. 2009 Nov;8(11):5367-74) Instruments have also improved in the intervening years. It is true that good metrics of sensitive and efficient analysis are frequently notably absent there are a few more recent papers that are good points of comparison. There is already work down to 50,000 cells (Journal of Proteome Research, 20 Nov 2017, 17(1):234-242) and they did perform nuclei isolation. However, they do not state the amount loaded on column directly; however, there is recent top down work on histones the clearly states injecting 55 ng on column (J. Am. Soc. Mass Spectrom. 2019, 30, 12, 2548–2560). Clearly, the number to compare to in a modern context is much lower than 1µg. Also clear from looking for good points of comparison is that more work is needed that endeavors to bring these numbers further down with clearly defined metrics. Your work clearly does this but could use well researched context. It is your position as author to do this sort of research and educate the reader. As you fairly point out there is also a difference between on column sensitivity and the sample requirements.

325

This is an incredibly sparse discussion of the AML results. There is plenty of context to give here. It does not need to be really big but this is almost nothing.

Figure 1

The use of instrument technical variance does not support there being any statistical significance to the difference between with and without nuclei isolation, which is the point of this figure to my understanding.

Figure 3

The figure would be clearer with additional labels on A and C.The figure caption is slightly confusing primarily due to the organization and labeling. although I think I figured it out. I might go with just an A panel (for A & B) and a B panel (for C & D) if you are not describing the panels separately.

Figure 4

The caption oddly starts out on the very general subject before describing what the figure is.

Figure 5

Wrong figure included in file. This is a critical figure and I do not have access to critically review it.

Supplemental figure 1

It seems to me that this should be Figure 1 and not a supplemental figure. At the least it would be useful and informative to compare your results to previous work in the area of Leukemia and Histones PTM quantitation, particularly in vivo: (e.g. Blood (2014) 124 (21): 2202 & Blood (2019) 134(24): 2183-2194) or even in vitro J. Am. Soc. Mass Spectrom. 2004;15(1):77–86. Has this (*whatever this is* since the figure is missing and the results poorly described) been observed previously or is it novel. Does SETDB1 have an established role in leukemogenesis? A quick google search is a resounding yes, yet no mention here. I infer from Fig S6 that you probably observed higher H3K9me3. Contrary to the SETDB1 story I also see in the literature this biology is mostly connected with higher levels of acetylation, including K9ac which block SETDB1 activity and is antagonistic of K9me3. How to rationalize these.

There are a number of citations that worthy of inclusion (incomplete list):

From the Garcia Lab:

One-Pot Shotgun Quantitative Mass Spectrometry Characterization of Histones. J Proteome Res. 2009 Nov;8(11):5367-74

Dramatically improved sensitivity and established the practice of skipping further purification after dervitization, which is an integral part of your approach. Your work is an extension of gaining sensitivity by reducing steps.

From the Turner Lab:

Reading Signals on the Nucleosome With a New Nomenclature for Modified Histones. Nat Struct Mol Biol. 2005 Feb;12(2):110-2. doi: 10.1038/nsmb0205-110.

This established the Brno nomenclature for histone modifications used throughout this work. It would be helpful to reference this at line 164.

The Tiziana Bonaldi lab has published extensively on clinical applications of histone PTM proteomics on limited samples, including human tumors etc.

**********

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Decision Letter 1

Charles Michael Greenlief

11 Aug 2020

PONE-D-20-14092R1

Targeted detection and quantitation of histone modifications from 1,000 cells

PLOS ONE

Dear Dr. Kelleher,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The reviewers agree that some of their previous concerns were addressed. However the reviewers, and I, felt that not all the concerns were adequately addressed. In particular, the concerns about the previous literature and how it is represented in your manuscript needs to be rectified. The biological context discussion of AML also needs to be improved.

Please submit your revised manuscript by Sep 25 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

C. Michael Greenlief, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors claimed that "these ions were selected to unambiguously confirm the site of modification". If MS2 spectra are not available, it would be good to provide solid evidence to support these ion transitions.

Reviewer #2: Discussion of multi-omics approaches are added in this version, and I believe it is suitable for publication.

Reviewer #3: In this revised manuscript Abshiru et al. present work that improves the sensitivity on a number of cells analyze basis for proteomic quantitation of histone PTMs. The key step is skipping nuclei isolation for cell numbers less than 1x10^4 and disposing of additional rounds of derivitization. This makes significant advances in sensitive histone proteomic analysis for limited samples in a variety of applications. The overall quality of the work is very good and the sensitivity improvements are substantial. The improvements presented here are significant and important; however, the claims remain somewhat overstated and poorly contextualized. The responsiveness of the authors to some reviewer comments was limited and half-hearted, in other places the response is thorough and appropriate. Many major errors and mistakes in language have been fixed. A major flaw remains in the apparent misreading or possible misrepresentation of the prior literature and the overstatement of the improvements made. I find the response of the authors to the reviewer comments on this subject perplexing bordering on disconcerting. I see no need to misrepresent the value of the current work by creating a straw man when the improvements offered in the current work are real and significant when compared to reality.

Major revision

Crux of the major issue:

You completely misread the Guo paper: The claim of the Guo paper is that the prevailing methods (dating back to ~2009) ARE capable of obtaining results from 50,000 cells NOT that they have an improved method that is capable of such. This evidence is clear and unambiguous.

Comments on prior literature generally:

Certainly, one of the issues is that the prior literature has not been as careful or consistent in presenting quantitative metrics of sensitivity and sample requirements. Sometimes specific sensitivity claims are not even stated while other use differing metrics. This makes proper presentation of the context an effort; however, the authors should make the effort and interpret the literature for the audience. The difference between the “number of cells” and “mass of protein on column” sensitivities is important to this particular effort. The frequent but not universal absence of solid sensitivity claims in prior work should not justify claiming that there are no improvements but rather noting this fact prominently as incomplete information in the literature and that it may be hard to judge. A little reading allows fairly clear inferences about prior work. For example, the Guo paper that is now cited for the clear and comparable “50,000 cells” claim includes this sentence: “Histones were extracted as described previously with minor modification” and cites a Jove paper which is essentially a video version of the 2009 J Proteome Res. One Pot paper. Thus, they are the same procedure with inconsequential modification. It is quite clear from reading the Guo paper carefully that they are not presenting an improved method that is now capable of this. The very title begins with “Assessment of …”. Thus, it is claiming that this is the capacity of the established methods but no one has ever really assessed this capacity properly. “…our study addresses a simple, albeit critical, question about the amount of material required for MS analysis of histone PTMs.” Lots of papers in this area start with large numbers of cells not because it is a requirement but because it is easy, convenient and the work is not sample limited (cell culture or tumors). It is also obvious that skipping the HPLC step as was done in the one pot paper was essential to this sensitivity capacity demonstrated by Guo. This is in fact the primary thesis of the improvements in this work as you state: “reduction in sample processing allows for quantitation of very low input samples.”. Skip nuclei isolation. Skip the second round of propionylation. Even more histones are extracted for low cell counts. There is no doubt that the contribution you are making here is important but do not overstate it. You have made a 5-fold to maybe approaching 50-fold improvement over the established methods that have been in use for over ten years, if only recently assessed for LLOQ by input cell number and not widely used in cell number limited work. Nonetheless, the improvements made here are pretty substantial and enabling of important future work.

AML and biological context:

I agree entirely that care should be applied to not overstating the meaning of the data presented here in understanding the fundamental mechanisms of AML. There is simply not enough statistical power for such claims. However, there are trends that are present and worthy of discussion and comparison to other studies. The concordance with prior work is validating some of which have solid in vivo models, Kaplan-Meier curves and other follow up experiments from the proteomics data. It is also important to discuss the limitations of the data and warn readers not to over interpret it. The concordance of your (limited) results with (limited) prior observation are also validating of the capacity of your improved approach to accurately measure.

References cited:

Separately from misrepresentation of the literature, the authors also seem to have a strong self citation bias and a tendency toward selective exclusion of inconvenient but appropriate literature for comparison.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2020 Oct 26;15(10):e0240829. doi: 10.1371/journal.pone.0240829.r004

Author response to Decision Letter 1

23 Sep 2020

Reviewer #1: Authors claimed that "these ions were selected to unambiguously confirm the site of modification". If MS2 spectra are not available, it would be good to provide solid evidence to support these ion transitions.

Peptide transitions that were used in this manuscript were previously developed and published. Zheng et al. (Zheng Y, Sweet SM, Popovic R, Martinez-Garcia E, Tipton JD, Thomas PM, et al. Total kinetic analysis reveals how combinatorial methylation patterns are established on lysines 27 and 36 of histone H3. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(34):13549-54) initially developed the methods for methylated peptides. One year later, he further exanded this to acetylated peptides (Zheng Y, Thomas PM, Kelleher NL. Measurement of acetylation turnover at distinct lysines in human histones identifies long-lived acetylation sites. Nature communications. 2013;4:2203).

We have included these references within the methods on pg 7, line 157, as well as a full list of all transitions as a supplemental table (S7 Table).

Reviewer #2: Discussion of multi-omics approaches are added in this version, and I believe it is suitable for publication.

Reviewer #3: In this revised manuscript Abshiru et al. present work that improves the sensitivity on a number of cells analyze basis for proteomic quantitation of histone PTMs. The key step is skipping nuclei isolation for cell numbers less than 1x10^4 and disposing of additional rounds of derivitization. This makes significant advances in sensitive histone proteomic analysis for limited samples in a variety of applications. The overall quality of the work is very good and the sensitivity improvements are substantial. The improvements presented here are significant and important; however, the claims remain somewhat overstated and poorly contextualized. The responsiveness of the authors to some reviewer comments was limited and half-hearted, in other places the response is thorough and appropriate. Many major errors and mistakes in language have been fixed. A major flaw remains in the apparent misreading or possible misrepresentation of the prior literature and the overstatement of the improvements made. I find the response of the authors to the reviewer comments on this subject perplexing bordering on disconcerting. I see no need to misrepresent the value of the current work by creating a straw man when the improvements offered in the current work are real and significant when compared to reality.

We thank the reviewer for their comments on the strong quality of the work submitted. We certainly didn’t intend to offend, misrepresent or overstate the significance of the work submitted and had believed that we had fully addressed these issues in the prior revision. To address these lingering concerns, were have re-written the discussion section to include additional comparisons to the current literature and hope this will now meet the needs of the reviewers and editors of PLoS One.

Major revision

Crux of the major issue:

You completely misread the Guo paper: The claim of the Guo paper is that the prevailing methods (dating back to ~2009) ARE capable of obtaining results from 50,000 cells NOT that they have an improved method that is capable of such. This evidence is clear and unambiguous.

As discussed above, we do not dispute this fact and have re-written the discussion to include a more in-depth comparison with the current histone sample preparation literature (pg. 15, line 336).

Comments on prior literature generally:

Certainly, one of the issues is that the prior literature has not been as careful or consistent in presenting quantitative metrics of sensitivity and sample requirements. Sometimes specific sensitivity claims are not even stated while other use differing metrics. This makes proper presentation of the context an effort; however, the authors should make the effort and interpret the literature for the audience. The difference between the “number of cells” and “mass of protein on column” sensitivities is important to this particular effort. The frequent but not universal absence of solid sensitivity claims in prior work should not justify claiming that there are no improvements but rather noting this fact prominently as incomplete information in the literature and that it may be hard to judge. A little reading allows fairly clear inferences about prior work. For example, the Guo paper that is now cited for the clear and comparable “50,000 cells” claim includes this sentence: “Histones were extracted as described previously with minor modification” and cites a Jove paper which is essentially a video version of the 2009 J Proteome Res. One Pot paper. Thus, they are the same procedure with inconsequential modification. It is quite clear from reading the Guo paper carefully that they are not presenting an improved method that is now capable of this. The very title begins with “Assessment of …”. Thus, it is claiming that this is the capacity of the established methods but no one has ever really assessed this capacity properly. “…our study addresses a simple, albeit critical, question about the amount of material required for MS analysis of histone PTMs.” Lots of papers in this area start with large numbers of cells not because it is a requirement but because it is easy, convenient and the work is not sample limited (cell culture or tumors). It is also obvious that skipping the HPLC step as was done in the one pot paper was essential to this sensitivity capacity demonstrated by Guo. This is in fact the primary thesis of the improvements in this work as you state: “reduction in sample processing allows for quantitation of very low input samples.”. Skip nuclei isolation. Skip the second round of propionylation. Even more histones are extracted for low cell counts. There is no doubt that the contribution you are making here is important but do not overstate it. You have made a 5-fold to maybe approaching 50-fold improvement over the established methods that have been in use for over ten years, if only recently assessed for LLOQ by input cell number and not widely used in cell number limited work. Nonetheless, the improvements made here are pretty substantial and enabling of important future work.

In the discussion, we have attempted to place our work within the context of what was previously done. With regard to the comparison with the Guo paper, we have stated that the results obtained at 50,000 cells when the nuclear isolation is omitted shows no benefit in sensitivity. For 50,000 cells and above, there is no benefit to our revised method and we suggest that the traditional approach may be preferred at these higher cell starting amounts (pg. 16, line 364).

AML and biological context:

I agree entirely that care should be applied to not overstating the meaning of the data presented here in understanding the fundamental mechanisms of AML. There is simply not enough statistical power for such claims. However, there are trends that are present and worthy of discussion and comparison to other studies. The concordance with prior work is validating some of which have solid in vivo models, Kaplan-Meier curves and other follow up experiments from the proteomics data. It is also important to discuss the limitations of the data and warn readers not to over interpret it. The concordance of your (limited) results with (limited) prior observation are also validating of the capacity of your improved approach to accurately measure.

Given the small “N”, we have been extremely careful not to overstate the findings in the context of AML. In this revision, we have expanded on the role of histone modifying enzymes in blood cancer beginning on pg 16, line 375. We have further shown evidence of the role of H3 K9me3 and SETDB1 levels in AML beginning on pg 17, line 402.

References cited:

Separately from misrepresentation of the literature, the authors also seem to have a strong self citation bias and a tendency toward selective exclusion of inconvenient but appropriate literature for comparison.

We respectfully disagree that we displayed “strong self-citation bias”. Our research group has been active in histone analysis for over 15 years, publishing over 50 papers in this field, much of it building on past methods developed by our group and others applying it within biological contexts. In the previous revision, just 6 of the 40 total references (15%) were to our prior work. With the additional references added in this revision, this ratio drops to 6/45 total or ~13%.

Attachment

Submitted filename: 20200826_PLOSone_Response_2_v2_PMT.docx

Click here for additional data file. (17.4KB, docx)

Decision Letter 2

Charles Michael Greenlief

25 Sep 2020

PONE-D-20-14092R2

Targeted detection and quantitation of histone modifications from 1,000 cells

PLOS ONE

Dear Dr. Kelleher,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

There is a minor point that the authors need to address about Table S7. The manuscript should be accepted after the minor concern mentioned at the end of this letter.

Please submit your revised manuscript by Nov 09 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

C. Michael Greenlief, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

The authors have addressed all the reviewer concerns. The new discussion is well presented.

There is one minor point: On page 25, line 530: There should be a table S7 listed along with its title.

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[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Oct 26;15(10):e0240829. doi: 10.1371/journal.pone.0240829.r006

Author response to Decision Letter 2

30 Sep 2020

We appreciate the positive response to the revised manuscript. We have included the title for table S7 on pg 25, line 526.

Attachment

Submitted filename: 20200826_PLOSone_Response_3_v1_JMC.docx

Click here for additional data file. (12.5KB, docx)

Decision Letter 3

Charles Michael Greenlief

5 Oct 2020

Targeted detection and quantitation of histone modifications from 1,000 cells

PONE-D-20-14092R3

Dear Dr. Kelleher,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

C. Michael Greenlief, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

This is an interesting study and worthy of publication. The authors have addressed all of the reviewers' concerns well in the revised manuscript.

Reviewers' comments:

Acceptance letter

Charles Michael Greenlief

14 Oct 2020

PONE-D-20-14092R3

Targeted detection and quantitation of histone modifications from 1,000 cells

Dear Dr. Kelleher:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Charles Michael Greenlief

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Schematic overview comparing the standard preparation protocols with the modified procedure.

    (TIF)

    Click here for additional data file. (869.7KB, tif)
    S2 Fig. Elimination of nuclear isolation in 5×104 cells.

    Comparison of (A) extracted peak area of histone peptides and (B) percentage CV values of histone peptides from 5×104 cells with and without the nuclear isolation step. Error bars represent the standard deviation of two instrument replicates within a single experiment.

    (TIF)

    Click here for additional data file. (443.9KB, tif)
    S3 Fig. Variation in CV with and without nuclear isolation.

    Log10 of peak area for each cell number was plotted with log10 of the coefficient of variation (CV). (A) 1×104 cells show the same slope with (red) and without (green) nuclear isolation and a statistically significant difference in the lines (p = 6.055e-6), but not the slopes (p = 0.4254) by analysis of covariance (ANCOVA). (B) 5×104 cells show different slopes with (red) and without (green) nuclear isolation and a statistically significant difference in the lines (p<2.2e-16) and slopes (p = 0.001876) by ANCOVA.

    (TIF)

    Click here for additional data file. (754.9KB, tif)
    S4 Fig. Reduction in propionylations rounds reveals peptides from 1×104 cells.

    Skyline extracted peaks for H3.3 K27ac K36un shows the presence of the peptide in one round of propionylation and absent in two rounds.

    (TIF)

    Click here for additional data file. (481.7KB, tif)
    S5 Fig. Modified protocol reveals H3 K9K14 peptide at 1×103 cells.

    Comparison of H3 K9ac K14ac peptide in HeLa (left) and NBM (right) shows the presence of the peptide in NBM but not HeLa.

    (TIF)

    Click here for additional data file. (565.6KB, tif)
    S6 Fig. Correlation of histone modifications with RNA transcript levels.

    Relative SETDB1 mRNA levels as determined by qPCR in three samples with low H3K9me2/3 (red) and three samples with high H3K9me2/3 (blue).

    (TIF)

    Click here for additional data file. (95.2KB, tif)
    S1 Table. Percent relative abundance of histone PTMs with and without nuclear isolation prior to histone extraction.

    (XLSX)

    Click here for additional data file. (40.2KB, xlsx)
    S2 Table. Percent relative abundance of histone PTMs with one or two rounds of propionylation.

    (XLSX)

    Click here for additional data file. (27.6KB, xlsx)
    S3 Table. Percent relative abundance of histone PTMs at a range of HeLa cell numbers.

    (XLSX)

    Click here for additional data file. (39.6KB, xlsx)
    S4 Table. Percent relative abundance of histone PTMs in CD34+ normal bone marrow.

    (XLSX)

    Click here for additional data file. (29.2KB, xlsx)
    S5 Table. Percent relative abundance of histone PTMs in primary AML patient specimens at 1,000 cells.

    (XLSX)

    Click here for additional data file. (16.3KB, xlsx)
    S6 Table. Percent relative abundance of histone PTMs in primary AML patient specimens.

    (XLSX)

    Click here for additional data file. (12.5KB, xlsx)
    S7 Table. Complete list of transitions used in data acquisition.

    (XLSX)

    Click here for additional data file. (19.2KB, xlsx)
    Attachment

    Submitted filename: 20200622_PLOSone_Abshiru_Reviewer_Response_JMC_v2.docx

    Click here for additional data file. (26.1KB, docx)
    Attachment

    Submitted filename: 20200826_PLOSone_Response_2_v2_PMT.docx

    Click here for additional data file. (17.4KB, docx)
    Attachment

    Submitted filename: 20200826_PLOSone_Response_3_v1_JMC.docx

    Click here for additional data file. (12.5KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLoS ONE are provided here courtesy of PLOS

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