Peer review of: Nanoproteomics enables proteoform-resolved analysis of low-abundance proteins in human seru (2020)

REVIEWER COMMENTS 
Reviewer #1 (Remarks to the Author): 


Top-down mass spectrometry (MS) proteomics plays a critical role in identifying post-translational 
modification of proteins. However, the detection and analysis of low-abundance proteins in 
plasma/serum by MS has proven challenging. The authors developed a nanoproteomics platform by 
conjugating superparamagnetic nanoparticles with targeting peptides to enrich cardiac troponin I 
(cTnI), a biomarker for cardiovascular disease, in serum samples. The nanoproteomics platform 
showed excellent cTnI enrichment relative to other abundant proteins in plasma. The authors 
performed a thorough demonstration of the utility of this platform, showing diverse cTnI 
proteoforms and establishing the proteoform-pathophysiology relationship. This is compelling work 
that could be further improved by addressing the following critiques before publication in Nature 
Communications. 

1. From Fig 1c-1e, it appears that there may be Fe3O4-peptide aggregation. Therefore, the reviewer 
suggests adding more experiments on the dispersibility and size uniformity of Fe3O4-peptide, as this 
may influence surface area and cTn1 enrichment. 

2. While SDS-PAGE provides a gross measure of assay reproducibility, it has important limitations. It 
would be more compelling to see bottom-up MS data of three replicates (NP-Targeting Peptide) 
from the serum with data presentation in a Venn diagram to show reproducibility. 

3. Fig. 11 demonstrates the authors’ claim that the salt (NaCl) concentration of the wash buffer was 
a critical tunable parameter to promote effective cTn1 enrichment. It would be helpful to test that 
hypothesis and explain this phenomenon with additional relevant experiments. In addition, the 
authors should also determine the zeta potential of the NP-Pep, since the electric charge intensity 
could influence cTn1 enrichment when using different NaCl concentrations as the washing buffer. 

4. When the authors sought to evaluate the cTn1 enrichment performance of NP-Pep and measure 
cTn1 enrichment, they first used ELISA to briefly determine the cTn1 ratio. Does this mean that the 
authors should also use ELISA to determine the ratio and then use the corresponding concentration 
of NP-Pep for cTn1 enrichment? What determines the concentration of NP-Pep used? 

5. Although the targeting peptide can specifically adsorb cTnl proteoforms with depletion of human 
serum albumin, there are still other nonspecific proteins on the SDS-PAGE gel images that are 
normal. The authors should discuss this in more depth. In addition, could the authors analyze the 
most abundant proteins (e.g., the top 10) and their accumulation percentages? Does the size of 
nonspecific proteins and the size difference between NPs and nonspecific proteins affect enrichment 
performance? 

6. The targeting peptide, which has an excellent binding affinity (0.27 nM), lends the iron oxide 
nanoparticles outstanding capacity to enrich cTnl proteoforms. In human blood samples, the authors 
use the spike-in cTnl samples to test their platform. With known spike-in cTnl samples, can the 
authors calculate the enrichment efficiency from the cTnI spike-in serum samples? 

7. In figure S13, the unfunctionalized NPs(i) have very poor enrichment performance. Is that because 
of the hydrophobicity of NP-BAPTES before peptide conjugation? The NPs conjugated with control 
peptide(iii) showed much weaker enrichment of cTnl but similar enrichment of nonspecific proteins 
compared with NPs conjugated with targeting peptide. Could the authors compare the accumulation 
percentage of the 10 most abundant proteins (loading mixture)? This may help readers understand 
how to eliminate the adsorption of nonspecific proteins. 

8. It is very impressive that targeting peptide-conjugated NPs have an excellent capacity to deplete 
human serum albumin, but the authors did not mention whether the control peptide-conjugated 
NPs also have this ability. Where does the albumin-depletion property come from? The NP itself or 
the peptide sequence? Can the authors compare the albumin depletion capability of targeting 
peptide-conjugated NPs and control peptide-conjugated NPs? 

9. SDS-PAGE gel shows obvious protein enrichment, including the target cTnl. Since targeting 
peptides can specifically and tightly bind with cTnl, could the authors perform a second elution to 
determine whether some cTnl and other proteins are left on the surface of NPs after the first 
elution? 

10. Stability is critical when considering the commercialization of this nanoproteomics technology. 
Will this NP-targeting peptide maintain its targeting performance after 3 months? 6 months? 

 


Reviewer #2 (Remarks to the Author):  

Tiambeng et al. present an interesting antibody-free approach for characterization of low abundance 
cardiac troponin I proteoforms directly from human serum based on a powerful combination of top-
down mass spec and nanotechnology (peptide-functionalized superparamagnetic nanoparticles). 
The novelty is primarily in enrichment protocol, with other methods employed, including top-down 
mass spectrometry, being generic. The study is well planned and executed, and technical quality is 
high. This is however a highly targeted approach that will be of limited interest to broad audience at 
least in its current version. I would strongly suggest expanding the discussion of general applicability 
and potential for the future. 

Specific comments: 

Pages 4-6, Figure 1: The idea of using allenamides for selective conjugation to Cys is interesting and 
novel (even though this chemistry has been around for some time). It appears that the site 
selectivity would be lost if the peptide to be conjugated has Cys as part of the binding sequence. 
Azides and cyclooctynes would be alternatives that could easily be incorporated via SPPS and be fully 
biorthogonal. Authors should discuss these limitations and alternative approaches. 

Pages 4-6, Figure 1: Another concern is the use of thermogravimetric analysis to determine a surface 
density of 1.5 peptide/nm2. That is an unusual way of measuring peptide loading and it is not clear 
from the manuscript how the authors arrived at that value. Since the peptide has two Trp residue 
and one Tyr, couldn’t they just measure the depletion of peptide during the NP-BAPTES reaction 
using 280 nm absorbance and derive a more useful value such as µmol peptide per mg nanoparticle? 
That way at least it would be known how much total peptide ligand is being added to the sarcomeric 
protein extracts. 

Pages 4-6, Figure 1: Because NP-Ctrl and NP-Pep contain reactive sites that have not been quenched 
with an exogenous thiol (e.g. glutathione or Cysteine) after the conjugation reaction, it is possible 
that BAPTES could react with Cys-containing proteins or other compounds downstream. Please 
comment. 

Figure 1: The DCM/water biphasic analysis is interesting. Did the authors perform a mock reaction 
first with NP-BAPTES or added it after being vacuum dried (in which case it is not a fair comparison 
with NP-Pep). 

Pages 8-9, Figure S12: The SDS-PAGE with SYPRO showed depletion of nonbinding proteins through 
loading, flow through, and eluate. However, the enrichment could have been better demonstrated 
with ELISA instead of MS peak abundance. 

Page 8: “NP-BAPTES functionalized with a negative-control peptide containing alanine substitutions 
to reduce cTnI-binding affinity” - however there are more amino acid substitutions to the control 
peptide than just alanine. It is unclear what was the rational for the other changes. 

Page 9, Figure 2, Figure S12, Table S3 (and elsewhere): It appears proteoforms were identified using 
only accurate intact mass measurements on a Q-TOF. While this approach allows for increased 
sensitivity, it obviously has limitations and would have to supplemented by MS/MS to e.g. inform on 
the site of phosphorylation (other PTMs). Did authors attempt to perform MS/MS measurements? 
Did they detect any novel proteoforms in comparison to prior art? Some discussion around these 
topics would have been helpful. 

Page 12, Figure 3: Comparing the nanoparticles to agarose and NP-Pep to Agarose-mAb is not a fair 
comparison. A better comparison would have been dynabeads linked to the mAb or peptide. That 
would strengthen the argument that nanoparticles are superior other particles (page 3), and that the 
peptide is better than the mAb. 

Tables S3 and S4: ppcTnI[1-206] should be ppcTnI[1-207] based on the listed observed mass. This 
would be consistent with Figure S12 

Page15, line 319: should it be 0.006 ng/mL (instead of 0.06 ng/mL)? 

Figure S21 shows the amount of cTnI as a function of concentration (ng/mL) except in (d) where it’s 
portrayed as amount (ng). The legend mentions loading as a function of concentration as well, but 
without knowing the volume loaded it’s not possible to derive the estimated total cTnI loaded onto 
the LC column. A table shows the calculated and observed masses of ppcTnI as 24063.7 Da, however 
these masses are inconsistent with (b) of the same figure and the tables in the supplemental. 

Figures S22-23: The 32+ charge state of ppcTnI portrayed in figure S22 is inconsistent with the 32+ 
charge state portrayed in figure S23, although it appears figure 22 has the correct m/z. The entire 
m/z axis of figure 23 is confusing as it skips between 0.5 m/z and 5 m/z steps. 

 


Reviewer #3 (Remarks to the Author): 

Thanks for the opportunity to review this methodological manuscript. The paper is well-written, 
well-organized, well-illustrated, properly referenced and novel. 

In this work, a multidisciplinary team of chemists, and cell & molecular biologists, presents a 
nanoparticle-based preparatory method for selectively, sensitively and consistently detecting an 
exemplary protein of clinical interest, cardiac Troponin I (cTnI). 

The premise of the work relates to the longtime-, well-known- problem of plasma or serum 
proteome assessment that is due to the large dynamic range of proteins in terms of concentration 
and the dominance of the measurable proteome by such high molecular weight entities as 
circulating albumin. Regardless of our awareness of this issue, approaches thus far have not solved 
the problem. 

The improvement of pre-MS preparation, beyond the use of immuno-based techniques for selection 
of certain proteins has long been needed. Thus, the nano-proteomic strategy to detect and 
quantitate proteoforms like those of cTnI is of considerable interest and potential. 


My assessment of the technology is very high level. It appears logical and valid. The experimental 
replicates and the reliance on three different types of human heart muscle samples allows 
comparison of normal with disease state tissues using this methodological workflow. 


The figures illustrate the nature of each experiment well, interpretable by a non-expert. 

A few questions which if answered and with answers intercalated into the paper should add a little 
value; they are as follows: 


1. Is it assumed that the approach used for cTNI would/will work for the other troponins? Will it 
work for other low abundance proteins in plasma or serum like cytokines, growth factors, etc.? 
Please elaborate the basis of this belief? If other low abundance proteoforms could be assessed, 
what would be the hurdles for doing so that are not covered by the work that you present here? 


2. What is the practicability of the nano-proteome strategy versus immuno-strategies in terms of 
time, various costs and broader applicability for the detection of other low abundance proteoforms? 

 
3. While this nano-proteomic technique appears sensitive, reproducible, etc., will it be so when 
plasma or serum from patients with different levels of blood lipids, blood sugar, etc., are 
encountered? 


4. What is the value of showing the different nano-proteoforms between the three hearts that were 
studied? Do you have any insight as what those apparent differences might mean? Please elaborate. 

5. When you do the spike-in experiments, which cTnI do you use? Why? Would a different source 
impact your results? Overall, how do you assure specificity of what you are measuring (realizing the 
problems of specificity that exist with immuno-pre-MS techniques? 

6. Will this advanced technique ever have clinical relevance? Please explain how and likely when? 
What are the hurdles? 

Thanks for the privilege of reviewing this paper.