Automated ChIPmentation procedure on limited biological material of the human blood fluke Schistosoma mansoni

In living cells, the genetic information stored in the DNA sequence is always associated with chromosomal and extra-chromosomal epigenetic information. Chromatin is formed by the DNA and associated proteins, in particular histones. Covalent histone modifications are important bearers of epigenetic information and as such have been increasingly studied since about the year 2000. One of the principal techniques to gather information about the association between DNA and modified histones is chromatin immunoprecipitation (ChIP), also combined with massive sequencing (ChIP-Seq). Automated ChIPmentation procedure is a convenient alternative to native chromatin immunoprecipitation (N-ChIP). It is now routinely used for ChIP-Seq in many model species, using in general roughly 10 6 cells per experiment. Such high cell numbers are sometimes difficult to produce. Using the human parasite Schistosoma mansoni, whose production requires sacrificing animals and should therefore be kept to a minimum, we show here that automated ChIPmentation is suitable for limited biological material. We define the operational limit as ≥20,000 Schistosoma cells with 30,000-300,000 cells as optimum. We also present a streamlined protocol for the preparation of ChIP input libraries.


Introduction
Schistosoma mansoni is a human parasite with a complex life cycle that shows strong developmental phenotypic plasticity, with intra-molluscal and intra-vertebrate stages, and two free-swimming larvae stages (miracidium and cercariae).We had shown by native chromatin immunoprecipitation (N-ChIP) that the different life cycle stages also show strong histone modification plasticity (de Carvalho Augusto et al., 2019;Cosseau et al., 2009;Roquis et al., 2018).While N-ChIP has been successfully used, we found that it is associated two challenges: one is the high hands-on time with the N-ChIP, and the other is obtaining enough biological material to perform several ChIP experiments with different antibodies.We therefore explored and benchmarked an automated ChIP procedure (Figure 1).ChIPmentation is a ChIP-sequencing (ChIP-seq) technology which uses a transposase to add the sequencing adaptors to the DNA of interest instead of the classical multi-step processing, including end repair, A-tailing, adaptor ligation and size-selection (Schmidl et al., 2015).Thanks to the action of the transposase, loaded with sequencing adaptors, the library preparation is performed in only one step, which reduces hands-on time and material loss.Moreover, in the ChIPmentation approach, this tagmentation process is performed directly on chromatin during the immunoprecipitation process instead of naked DNA after purification.This workflow allows for a more reproducible tagmentation.
The combined facts that ChIPmentation has been automated on Diagenode's IP-Star Compact Automated System and that this technology has been validated on low amounts of human cells (Roels et al., 2020;Schmidl et al., 2015) make it a perfect candidate for ChIP-seq on limited material of other, non-model species.Here we addressed the questions of whether ChIPmentation, which was originally developed for human cell cultures, (i) can be used with schistosomes, (ii) whether it can be automated on a pipetting robot, and finally (iii) what the lowest schistosome cell number would be to obtain robust results with this procedure.We show here that the method is almost as sensitive as N-ChIP, but is about two times faster and can be carried out on the IP-Star pipetting robot, reducing experimenter hands-on and, more importantly, training time.

Methods
Production of biological material S. mansoni NMRI eggs were extracted from livers of golden hamsters (donated by ParaDev) 42 days post-infection.Nocturnal S. mansoni from Oman (Mouahid et al., 2012) were extracted from livers of two swiss OF1 mice eight months post-infection.Miracidia were allowed to hatch for two hours in spring water, collected by pipetting and sedimented on ice for 30 min.Miracidia were counted under a microscope, aliquoted and stored at -80°C.

Ethical considerations
Experiments on animals permits The laboratory received the permit number A 66040 for experiments on animals, from both the French Ministère de l'Agriculture et de la Pêche (Ministry of Agriculture and Fisheries) and the French Ministère de l'Education Nationale de la Recherche et de  Ethical approval number: we obtained approval from the CEEA -036 Comité d'éthique en expérimentation animale Languedoc Roussillon (CEEA-LR)", which is the registration code of our ethical committee within the Comité national de réflexion éthique sur l'expérimentation animale (CNREEA), under the agreement number C66-136-01.The CNREEA is part of the French Ministry of Higher Education, Research and Innovation.

Cell lysis and chromatin shearing
Chromatin preparation was performed using the Diagenode ChIPmentation Kit for Histones, Cat.No. C01011009 and protocol with minor modifications.A total of 10,000 miracidia (1,000,000 cells based on the observation that one miracidium is composed of 100-120 cells) were resuspended in 1 mL 1x Hank's balanced salt solution (HBSS), split into 2x500 µl and crushed with a plastic pestle in an Eppendorf tube on ice during ~1 min.For cross-linking, 13.5 µl of formaldehyde were added and tubes were incubated for 10 min at room temperature with occasional inversion.To stop cross-linking fixation, 57 µl of glycine were added and samples were incubated for 5 min at room temperature.Samples were centrifuged at 500 g, at 4°C, for 5 min.The pellet was resuspended in 2x1 mL of ice-cold Lysis Buffer iL1, combined and homogenized in a Dounce (pestle A) on ice for 5 min.After another centrifugation (500 g, 5 min, 4°C), the supernatant was discarded and the pellet was resuspended in 1 mL of ice-cold Lysis Buffer IL2 and centrifuged (500 g, 5 min, 4°C).The supernatant was discarded, and the pellet was resuspended in 100 µl of complete Shearing Buffer iS1 for each tube.Samples were sonicated with the Bioruptor Pico (Diagenode, Cat.No. B01080010).To find optimal shearing conditions that deliver fragments between 300 and 1500 bp we performed sonication tests for 2, 4, 6, 8, 10 and 16 cycles (30 s ON and 30 s OFF at 4°C) and separated the fragments by migration through 1% agarose gels or on an Agilent 2100 Bioanalyzer with a High Sensitivity DNA Assay v1.03.After a second round of optimisation of 4, 5 and 6 cycles, five cycles (30 s ON and 30 s OFF) were used for all subsequent fragmentations.After transfer into new tubes, samples were centrifuged (16,000 g, 10 min, 4°C).The supernatants were transferred into a new single tube (200 µl total) and 20 µl iS1 was added, yielding

Amendments from Version 1
We added statistical support to the determination the lower limit of the number of cells that should be used for ChIPmentation.There has been a number of small amendments to the text and especially to the figure and table legends to make them clearer.a total volume of 220 µl.The procedure was done in duplicate (named L and R in the following).Serial dilutions were done in iS1 to produce 100 µl equivalents of 10,000 miracidia (10 6 cells), 1,000 miracidia (10 5 cells), 100 miracidia (10 4 cells), 50 miracidia (5,000 cells), 10 miracidia (10 3 cells), five miracidia (500 cells) and one miracidium (100 cells) or 100 µl iS1 as negative control.

Magnetic immunoprecipitation and tagmentation
Immunoprecipitation (IP) was performed on the Diagenode IP-Star Compact Automated System (Cat.No. B03000002) according to the ChIPmentation Kit for Histones User Guide and by following the manufacturer's on-screen instructions.Antibody (Ab) coating time was set to 3 h, IP reaction to 13 h, washes to 10 min, and tagmentation to 5 min.For each sample the Ab coating mix was done with 4 µl anti-H3K4me3 (Diagenode, Cat.No. C15410003; mixture of lot A1051D and A1052D; raised in rabbit).Tn5 and all other reagents came from ChIPmentation Kit for Histones (Diagenode, Cat.No. C01011009).
Stripping, end repair and reverse cross-linking were done as indicated in the User Guide.

Input library tagmentation
In the ChIPmentation Kit for Histones (Diagenode, Cat.No. C01011009) the suggested strategy is to sequence one immunoprecipitated sample with a control immunoglobulin G (IgG) and to use it for sequencing normalization instead of the traditional input, which cannot be treated in exactly the same way as the immunoprecipitated samples.However, IgG are negative control samples, and the generation of such samples in low-amount approaches involves in our experience the use of a high number of amplification cycles that can induce some biases.A protocol for the tagmentation of the input sample was therefore set-up as follows.
For each immunoprecipitated sample, 1µl of sheared chromatin was kept aside before IP in the IP-Star.One µl of MgCl 2 (Diagenode ChIPmentation kit for Histones, Cat.No. C01011009), 8 µl of molecular biology grade water, 10 µl 2xTagment DNA buffer and 1 µl of 100-fold in moleculargrade water diluted Tn5 DNA tagmentation enzyme (Illumina 20034197, lot 20464427) were added to each 1 µl input.We used here the Tn5 from Illumina because using Tn5 of the Diagenode ChIPmentation Kit would have reduced the number of ChIPmentation reactions that could be done with a kit.We have no reason to believe that both enzymes are substantially different.The tagmentation reaction was performed in a thermocycler for five minutes at 55°C.Then, 25 µl of 2xPCR NEB master mix (New England Biolabs M0541L, lot 10067165) was added to each input.The end-repair and de-cross-link were performed in a thermocycler for five minutes at 72°C followed by 10 minutes at 95°C.An aliquot of 2 µl was taken from each input and added to 8 µl of quantification mix.For each reaction, this quantification mix was composed of 0.3 µl of forward and reverse ATAC-seq primers (25 µM) (Table 1, (Buenrostro et al., 2015), 1 µl SYBR Green 10X (Diagenode kit), 1.3 µl of molecular biology grade water and 5 µl of 2xPCR NEB master mix.While not formally tested, leftover primers of the ChIPmentation kit could probably also be used, but the volume must be adjusted as the primer pairs in the kit were 10 µM instead of 25 µM.Library amplification, purification, quality checking and sequencing steps were performed as for the immunoprecipitated samples (see below).

Library amplification
To determine optimal number of library amplification cycles we proceeded as described in steps 5.1 to 5.5 of the ChIPmentation User Guide with modifications detailed below.We determined the number of amplification cycles for each library by using the number of cycles that corresponded to 1/3 of the qPCR amplification curve slope during the exponential phase.Results are shown in Table 2. Amplification was done in step 5.7.After PCR, 48 µl of library amplification mix were AMPure-purified on the IP-Star using 86 µl of AMPure beads (1.8x).Instead of a resuspension buffer, we used ChIP grade water for a final volume of 20 µl.

Library check and sequencing
Library fragment size and concentration was checked on an Agilent 2100 Bioanalyzer with a High Sensitivity DNA Assay v1.03.Paired-end sequencing (2x75 cycles) was performed at the Bio-Environnement platform (University of Perpignan, France) on a NextSeq 550 instrument (Illumina, USA).
Uniquely aligned reads were filtered from the BAM files using the XS: tag of Bowtie2, Galaxy version 2.3.4.3 and Galaxy 0 (Langmead & Salzberg, 2012).PCR duplicates were removed with samtools rmdup Galaxy version 2.0.1 (Li et al., 2009).BAM files were subsampled to 3.8 M uniquely aligned reads with Picard DownsampleSam Galaxy version 2.18.2.1 (Broad Institute, 2022, February 23).Peakcalling was done with Peakranger (v1.17)Galaxy version 1.0.0 (Feng et al., 2011), with P value cut-off: 0.0001, false discovery rate (FDR) cutoff: 0.05, Read extension length 100 -2,000 bp, Smoothing bandwidth: 99.Delta: 0.8, Detection mode: region.ChromstaR, Galaxy version 0.99.0 (Taudt et al., 2016) was used with a bin size same as Peakranger extension lengths and a step size of half a bin size.Miracidia genomic DNA libraries served as input.In ChromstaR postprocessing, the maximum posterior probabilities to adjust sensitivity of peak detection was set to 0.999.This kept broad peaks intact.We reasoned that gaps between peaks that were larger than a nucleosome are not biologically meaningful and peaks were merged with BEDTOOLS, Galaxy version 2.29.2 (Quinlan & Hall, 2010) when they were ≤150 bp apart (the average length of DNA in a nucleosome).
Enrichment plots over metagenes were produced over 5,073 genes on the positive strand based on the canonical annotation v7 of S. mansoni.To test for statistically significant differences between the profiles a Wicoxon rank-sum test was  used.The profiles were obtained using the chromstaR::: enrichmentAtAnnotation() function using the ChromstaR object and the annotation of the above-mentioned genes.The wilcox.test()function from R was used to calculate a p-value between all two-by-two comparisons.To test for statistically significant differences between the RPKM values, the data, extracted from the ChromstaR object, were averaged by samples and these values were used to perform a Wilcoxon rank-sum test to obtain a p-value between all two-by-two comparisons.

Results
ChIPmentation has a sensitivity that is comparable to N-ChIP We used S. mansoni miracidia which are composed of 100-120 cells as starting material, allowing for a good estimate of cell numbers.After the chromatin fragmentation and library amplification, 10 6 to 10 4 cell equivalents gave comparable Bioanalyzer profiles with peaks around 1kb (lanes L/R 1-3 in Figure 2).For 5,000 cells equivalents and below, fragments of smaller size became clearly visible.No high-molecular fragments were observed in the negative control without chromatin (Figure 2 and Table 2).
Alignments to the genome gave expected results (~50% uniquely aligned reads) for 10 6 to 10 4 cell equivalents, but dropped to ~35% with 10 3 cells equivalent and were <20% for 100 cells equivalent.No contaminating DNA was detected (Table 3).
In order to compare ChIPmentation results to N-ChIP we re-analysed earlier data obtained by N-ChIP (de Carvalho Augusto et al., 2019) using the same data-cleaning, alignment and peak-calling parameters as for ChIPmentation (Table 4).
For ChIPmentation, peakcalling with Peakranger was highly robust for 10 6 cells and delivered the expected values (based on earlier N-ChIP results).Below this cell equivalent, peak-calling became dependent on read extension length (Table 5).Testing different read extension length is a routine procedure in the laboratory that in our hands empirically improves robustness of peak calling.Figure 2 shows that fragment size is between 200 and 2000 bp, but Peakranger does not use ranges but only single mean values which is in our case 200 + ((2000-200)/2) = 1100 bp meaning that both methods converge towards the same value.
We iteratively identified 1,000 bp as best-read extension length.Using the HMM-based ChromstaR improved peak calling for ChIPmentation 10 4 cell equivalent, but not for 10 3 or 100 cells.We obtained comparable results for ChIPmentation of 10 6 , 10 4 cells and N-ChIP ~10 6 , 10 4 and 10 3 cells (Table 6).
ChromstaR metagene profiles showed consistent profiles for ChIPmentation 10 6 , 10 4 and 10 3 cells, and all N-ChIP, but not for ChIPmentation on 100 cell equivalents (Figure 3).To test for statistically significant differences between the profiles we a Wilcoxon rank-sum test.The results are in Table 7 and a detailed report in the underlying data on Zenodo.Using a common threshold for significance of p = 0.05 we can reject the null hypothesis only for sample C7, i.e.ChIPmentation on 100 cell equivalents, suggesting there is a significant difference only between C7 and the other samples.Interestingly, we also noticed that using RPKM, all samples are statistically different from each other, meaning that results of ChIPmentation and N-ChIP experiments are very sensitive to the amount of input material if RPKM values would be used (for details see underlying data).ChromstaR allows for estimating the correlation of chromatin profiles based on read counts (Figure 4), and indicates high correlations between ChIPmentation 10 6 , and N-ChIP ~10 6 , 10 4 .
All other overall chromatin profiles were below 0.75 correlation coefficient.This is surprising given the high similarity of metagene profiles.Visual inspection of peaks and profiles showed that peaks were actually correctly identified by ChromstaR (but much less by Peakranger) in ChIPmentation until 10 4 cells, but there was higher background than in N-ChIP which probably decreased the correlation for lower cell equivalents (Figure 5).
To determine cell number dependent sensitivity and specificity of the ChIPmentation approach decided to consider the N-ChIP results as true positives.We had in the past very high reproducibility of the N-ChIP procedure.We used BEDTools intersect with 20% overlap and otherwise default parameters to identify common peaks between the 6,186 N-ChIP peaks obtained with 10 6 cells and the ChIPmentation peaks.Common peaks were considered "true positives" and not common peaks as "false positives".We then used BEDTools Complement to identify regions without peaks and again BEDTools intersect with the abovementioned parameters to identify "true negatives".Sensitivity was calculated as true positives / positives, specificity as true negatives / (true negatives + false positives) and positive predictive value (PPV) as true positives / (true positives + false positives).Results are in Table 8.Intersection of sensitivity and specificity as a function of the optimization parameter (here cell number) is generally considered as optimum.Figure 6 shows that intersection occurs at 105 cells within a large plateau between 30,000 and 300,000 cells.ChIPmentation input library can rapidly be produced in parallel to the automated procedure After having formally established that automated ChIPmentation had a comparable sensitivity to our routine N-ChIP procedure, we aimed to identify the optimal way to produce input libraries for control of unspecific enrichment.The production of input chromatin is "built-in" the N-ChIP protocol (Cosseau et al., 2009;de Carvalho Augusto et al., 2020;Roquis et al., 2018) and needed to be adapted to the automated ChIPmentation procedure.During a ChIPmentation experiment three types of input can be considered (Figure 7): (i) 1 µl of chromatin before immunoprecipitation, (ii) chromatin that binds non-specifically to any support, and (iii) chromatin truly available for IP.In (i), an aliquot of 1 µl is taken from the sample before immunoprecipitation.The two other types (input library ii and iii) need a supplementary sample in which mock IP is done without antibody.After IP, this supplementary sample contains magnetic beads with the non-specifically bound chromatin and the supernatant, which is the available chromatin for IP.
Only (i), i.e. before IP chromatin and (iii) i.e. free chromatin available for IP give ideal library sizes (Figure 7).We decided to optimize the input protocol for option (i), non-immunoprecipitated chromatin because it does not occupy a slot in the IP-Star.In addition, during the preliminary test, 1 µl chromatin input showed a lower Ct compared to option (iii) input, which means that it requires fewer amplification cycles (data on Zenodo).
For the preparation of the 1 µl chromatin input libraries, we identified two critical parameters.The first one was the dilution of the tagmentation enzyme.Using undiluted Tn5 caused complete over-tagmentation.Between 10-and 100-fold dilutions in water delivered optimal results but the best dilution should be experimentally titrated and depends on the nature of the samples (Figure 8A).
Secondly, we found that, in our hands, there was no need to add tagmentation neutralizer (0.2% sodium dodecyl sulfate [SDS]) after tagmentation (Figure 8-B and Figure 9).This actually inhibits the PCR amplification step (Picelli et al., 2014).While not being systematically studied we noticed that parameters like tagmentation temperature (37°C-55°C) (Figure 9), tagmentation time (2-10 min) and addition of MgCl 2 did not have a critical effect on input library generation.

Discussion
As many methods, ChIPmentation had been developed using readily available but highly artificial cell cultures (Schmidl et al., 2015).The transition from such model systems to non-model species and ecologically realistic conditions is sometimes very difficult or even impossible.Here we showed that the automated ChIPmentation can be done with a parasitic flatworm and delivers results comparable to N-ChIP, the current method of choice for this species.However, the method is roughly two times faster and requires roughly six times less hands-on time (2 days ChIPmentation vs 4 days N-ChIP from sampling to library).Since the procedure is done on a pipetting robot with on-screen instructions for the researcher, in our experience, training time was reduced to about a week.Based on prices in France, ChIPmentation costs about 90€ per sample in material and reagents while N-ChIP cost roughly 20€ per sample, excluding antibody costs.
Our results show that robust detection of peaks with ChIPmentation occurs around 100,000 cells equivalent per antibody reaction, with 10,000 being the absolute limit if background is acceptable.Operational limit for N-ChIP is 10,000 cells equivalent, confirming our previous results.To avoid variations that might be introduced by small errors in the estimation of cell numbers, we arbitrarily doubled this lower cell limit and established ≥20,000 cells as the lower limit for the routine ChIPmentation-seq procedures in S. mansoni.This is a little higher than what has been described in Human cells where good results have been published with as little as 5,000 cells.
To improve signal to noise ratio and reduce background in ChIPmentation, it could be useful to increase the washing time (currently 10 min) and speed (currently medium) but we    recommend increasing cell number rather than to invest in washing optimization.In conclusion, ideally ChIPmentation should be done with 30,000 to 300,000 S.mansoni cells.
Using 1 µl of non-immunoprecipitated chromatin for the reference input library production is the best compromise to save space in the IP-Star, experiment time and biological materials when one is restricted by quantity.
This ChIPmentation protocol is not limited to miracidia cells.We also performed this protocol on S. mansoni adult worms and sporocysts.It should be noted that the number of sonication cycles needs to be experimentally determined and adapted for each sample type before proceeding to ChIPmentation experiments.
A new version of the ChIPmentation solution, called µChIPmentation for Histones (Diagenode, Cat.No. C01011011), has also been released recently in order to improve the quality for low-amount samples.This relies on a reduced number of steps, especially during chromatin preparation, and reduced number of tube transfers, in order to avoid DNA loss.It also contains a new protocol to process the non-immunoprecipitated chromatin input samples up to the sequencing step.This new version of µChIPmentation may be a good alternative for experiments on very low cell numbers in the future.

Qijun Chen
1 Shenyang Agricultural University, Liao Ning Sheng, China 2 Shenyang Agricultural University, Liao Ning Sheng, China The methodology described in the manuscript represents a great improvement to the ChIP-Seq related studies in the interest of very limited biological materials.Many parasite species are not be able to proliferate outside their hosts, the approach presented here will improve studies in the parasitology field, though not limited.I think the protocol developed by the group is very interesting, thus is suggested for expansion in investigation on other organisms.The manuscript is recommended for indexing with minor revisions.
It would be more convincing if the experiments of the ChIPmentation were performed in parallel with the "native ChIP-Seq", as described in Fig 1 .Here the authors only referred previous data which were not generated with the same batches of materials. 1.
The authors need to discuss the robustness or efficiency of the transposases, and the sources of the enzymes.

2.
Is the rationale for developing the new method (or application) clearly explained?Yes Is the description of the method technically sound?Yes The data presented by the group are very interesting, especially when applied to the human parasite Schistosoma mansoni, which, in addition to not being a model organism, does not have a genome considered finalized.Thus, the methodology described in this paper opens up an interesting perspective for the study of the different evolutionary forms of the parasite, which will certainly provide interesting epigenetic mechanisms, especially with regard to the host-parasite interaction.I have only two considerations, minor review: I understand that two steps are critical to success in the CHIP methodology.The sonication conditions and DNA loss between each chromatin purification step.Thus, I think that these points could be better explored in the discussion and; The manuscript by Lasica et al. provides a description of the automated ChIPmentation procedure applied to a trematode parasite.The authors argue that the automated procedure is as sensitive as CHIP-Seq and define an operational limit of >20,000 cells.I think the publication of the method is of significance but the manuscript needs to be improved.I suggest a more thorough analysis of the data collected with improved statistics to give the results more strength.I found the manuscript difficult to read for a number of reasons.
Given that the authors compare two techniques, they should more explicitly discuss sensitivity and specificity of the methods.I understand there is not "reference" material but I suggest posing the hypothesis that CHIP-seq is right and use these result as a reference to quantifying explicitly the error rates with different quantities of input material.Based on results from BEDTools interest, there are 734 peaks identified by CHIPmentation that have not been found by CHIPseq: are these false positives?There are 238 peaks found by CHIPseq not found by CHIPmentation: are these false negative?What are the differences in estimated false positives and false negatives when a different quantity of input material is used?This is particularly important to calculate and compare with 10,000 cells given the conclusions of the article. 1.

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The figures should be revised to provide more easy-to-read labels.

4.
I think the impact of the mansucript would be greatly increased if the authors provide statistical analyses: is there a significant difference between the number of peaks called with ChIPmentation and N-CHIP ?What is the percentage of peaks from one experiment also present in another?
○ I am not convinced by the >20,000 cells threshold suggested by the authors.Results presented in Fig 4 and 5 rather show that there is high background noise at 10,000 cells and that more accurate results are obtained at 100,000 cells.The method has never been tested with 20,000 cells and there are no statistical or modelisation results to support this threshold.Can something be dones to better support this operational limit?
○ Figure 1: Image quality is too poor for publication.It was blurry.

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Input Library prep, second paragraph: a sentence can not start with a number, "1" must be spelled out to "One".
la Technologie (Ministry of Education, Research and Technology, Décret n° 2001-464 du 29 mai 2001 modifiant le décret n° 87-848 du 19 octobre 1987).This includes housing, breeding and care of the mice and hamsters, and animal experimentation.HM holds the official certificate for animal experimentation N° C661101 delivered by the Direction Départementale de la Protection des Populations (Articles R 214-87 à R 214-122 du Code Rural et article R 215-10 ; Arrêté du 19 avril 1988).

Figure 1 .
Figure 1.Comparison of Native-ChIP and ChIPmentation workflows.Biological sampling time depends on the biological model used.Native-ChIP protocol lasts three to four days.A sucrose cushion is used for cell lysis and MNase digestion for the fragmentation step.The immunoprecipitation is done by centrifugation.The whole process is done manually.ChIPmentation protocol lasts two days.Cross-linking is used for cell lysis and sonication for the fragmentation step.The immunoprecipitation, tagmentation and library cleaning are done with the IP-Star.

Figure 6 .
Figure 6.Sensitivity (blue) and specificity (orange) on the y-axis) as a function of the cell number (x-axis).Intersection of specificityand sensitivity occurs at 10 5 cells within a large plateau between 30,000 and 300,000 cells indicating optimal cell numbers in this range.

Figure 7 .
Figure 7. Types of inputs generated during ChIPmentation and their associated bioanalyzer profiles.X axis represents the size in base pair, and Y axis represents the fluorescence intensity.Ideal library size is between 150 bp and 500 bp (blue rectangle).(i) 1µl aliquot of one sample chromatin taken before its immunoprecipitation.(ii) and (iii) are from a supplementary sample where immunoprecipitation in the IP-Star is done without antibody.After immunoprecipitation, this supplementary sample contains magnetic beads with the (ii) non-specifically binding chromatin and the supernatant which is the (iii) available chromatin for immunoprecipitation. (ii) No specific binding chromatin which did not deliver a usable library.

Figure 9 .
Figure 9. Picture of size separation of PCR products after qPCR for input library quantification by electrophoresis.Electrophoresis was performed through an agarose gel stained with ethidium bromide.Tagmentation was performed at 37°C and 55°C with 10-fold diluted Tn5.Sample legend: (S) with SDS, (E) without SDS, (TS) without Tn5 enzyme but with 0.2% SDS, (TE) without Tn5 enzyme and without SDS, (T-) qPCR negative control without chromatin.Ideal library size is between 150 bp and 500 bp.Only E samples had the right library size.Contrast was augmented, raw image provided.

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20200921-1_Report.pdf (qPCR report for comparing inputs with enzyme of Diagenode kit and our protocol with other enzyme Tn5) -CG_Ro_1_High Sensitivity DNA Assay_DE13805677_2019-06-20_09-10-48.pdf(DNA assay file underlying Figure 2) -CG_Ro_2_High Sensitivity DNA Assay_DE13805677_2019-06-20_10-12-12.pdf(DNA assay file underlying Figure 2) -gel qpcr test input sds_01.Tif -wilcoxon_curves.html: detailed analysis results of Wilcoxon test for differences in metagene profiles -wilcoxon_curves.Rmd : R code for detailed analysis results of Wilcoxon test for differences in metagene profiles Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).doi.org/10.21956/wellcomeopenres.19678.r61954© 2023 Chen Q.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Are sufficient details provided to allow replication of the method development and its use by others?Yes If any results are presented, are all the source data underlying the results available to ensure full reproducibility?Yes Are the conclusions about the method and its performance adequately supported by the findings presented in the article?Yes Competing Interests: No competing interests were disclosed.Reviewer Expertise: Molecular parasitology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Reviewer Report 20 July 2023 https://doi.org/10.21956/wellcomeopenres.19678.r61955© 2023 Guerra-Sá R.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Renata Guerra-Sá 1 Universidade Federal de Ouro Preto, Ouro Preto, State of Minas Gerais, Brazil 2 Universidade Federal de Ouro Preto, Ouro Preto, State of Minas Gerais, Brazil

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I missed a more detailed comment in terms of cost and number of biological replicas and the size of libraries when comparing ChIPmentation and N-ChIP techniques.○Is the rationale for developing the new method (or application) clearly explained?YesIs the description of the method technically sound?Yes Are sufficient details provided to allow replication of the method development and its use by others?Yes If any results are presented, are all the source data underlying the results available to ensure full reproducibility?Yes Are the conclusions about the method and its performance adequately supported by the findings presented in the article?Yes Competing Interests: No competing interests were disclosed.Reviewer Expertise: Molecular Biology and Epigenetics I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Reviewer Report 24 May 2022 https://doi.org/10.21956/wellcomeopenres.19678.r50460© 2022 Dheilly N.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nolwenn M. Dheilly 1 UMR Virology ANSES/INRAE, ENVA, Animal health laboratory, 14 rue Pierre et Marie Curie, Maisons Alfort, France 2 UMR Virology ANSES/INRAE, ENVA, Animal health laboratory, 14 rue Pierre et Marie Curie, Maisons Alfort, France

Figure 3 :○Figure 4 :○Figure 5 ○Figure 8 :○
Figure3: "consistent profiles" of metagene profiles except for 100 cells.Please revise the labels on the figure to make it easier to read.It seems that NC profile is also different from the others.Can you add the 95% confidence interval?Can you provide statistical analyses to test whether the profiles actually differ?○

Table 5 .
Optimization of peakcalling with Peakranger.Number of peaks identified for each condition.ChIPmentation on top.In bold: 1000 bp was selected as the best extension length and applied to N-ChIP data below.N-ChIP A is for 0.8x10 6 cells.

Table 4 . General statistics on N-ChIP libraries.
When possible, libraries were downsampled to 3.8 M uniquely aligned reads.

Table 3 .
General statistics on ChIPmentation libraries.All libraries were downsampled to 3.8 M uniquely aligned reads.

Table 7 . p-values of Wilcoxon test for differences between metagene profiles using log(observed/ expected) values as in Figure 3. Significant differences
(p<0.05) in bold.

Table 8 . Merged peaks, BEDTools intersect results at 20% overlap and specificity, sensitivity and PPV for N-ChIP and ChIPmentation.
For example, I had to go back and forth between the figure and legend to figure out what is C, C3 etc. Authors should also make sure that appropriate labels for axes are provided.(more detailed suggestions on each figure below).It can be difficult for some readers when the same result -size distribution of libraries -is presented in different formats: electrophoresis gel of Bioanalyzer in Fig 2, actual capillary RNA elextrophoresis plot from the Bioanalyzer in Fig 6 and 7, and then gel electrophoresis for fig 8.

Table 3 :
Results, paragraph 1: I have no idea how the text relates to table 2. I disagree with the statement that 10 6 and 10 4 gave comparable results.In Figure2, L1 appears different to R1 and L3 appears different to L3. alignment to the genome gave expected results (50%): maybe provide percentage in the table?Is there a problem with the number of read pairs for R1? Can you explicitely explain what is provided in each column in the table legend?Why has this number of peaks not been calculated for N-CHIP with other read extension length?
○ Library amplification: Results are shown in table 6 or table 2? ○ ○ Table 2: spell out "yes".○ ○ Table 5: below 1000, peak calling became dependent on bin size: How did you determine ○ this threshold?