N-terminal proteoforms may engage in different protein complexes

Proteins originating from the same gene, yet differing at their N-terminus—so-called N-terminal proteoforms—can take part in different protein–protein interactions.


Results:
In the Interaction profiling of Nt-proteoforms and their canonical counterparts section, the authors could address MaxQuant's normalization strategies and how similar VLP contents were within VLPs. They could also clarify if VLPs of different baits can be analyzed together regarding normalization and imputation. For the Proteoform-specific interaction partners section, the authors could explain the reason for imputation and whether it would be necessary for a more suitable analysis strategy. In the Studying selected differences between proteoform interactomes by AP-MS section, the authors could clarify why some proteins did not show up in the table of candidate interactors for AP-MS but were present in the Volcano plot. They could also evaluate the comparison of identified interaction networks to known interaction networks as mentioned in the text. Lastly, the last paragraphs of the Interaction profiling of Nt-proteoforms and their canonical counterparts section are not well-formulated.

Summary:
The authors explore N-terminal proteoforms in a mammalian cell line and investigate their impact on protein complex formation. They construct an N-terminal proteoform catalogue of the HEK293T cellular cytosol by mapping peptides generated by COFRADIC to the UniProt database and a custom-built database including Ribo-seq data and UniProt isoforms. They apply a custom scoring system to select a subset of 22 high-confidence N-terminal proteoforms for interaction mapping. The authors show that N-terminal proteoforms have significant tissue-dependent expression profiles in humans and compare the potential interaction partners for candidate Nterminal proteoforms to their canonical counterparts using Virotrap technology.
General remarks: The authors present a comprehensive study about cytoplasmic, N-terminal proteoforms in the HEK cell cytoplasm. Their approach is convincing and validates the existence of 20 N-terminal proteoforms with divergent PPI interaction partner profiling, which is a valuable addition to the literature. However, the authors use several assumptions along the way from the proteomic measurement to the final list of 20 proteins, which limits the ability to refer back from the 20 proteins to the global nature of the N-proteoformome. I recommend publishing of the article, it's a great contribution to LSA, but including a 'study limitation' section to openly discuss the bias that emerged from the strong multistep selection criteria that reduced a long list of MS hits to just 20 proteins.
We would like to thank the reviewer for her/his kind appreciation of our manuscript and support for publishing it. Including a 'study limitation' section is indeed an interesting addition to our manuscript as it provides a more complete view on all aspects of our study. We addressed this comment by adding a part in the discussion section that emphasizes that our selection strategy also induces a bias. The adjustments made are outlined in more detail below.

Major points:
The authors could include a 'study limitation' section to openly discuss the bias that emerged from the strong multistep selection criteria that reduced a long list of MS hits to just 20 proteins.
Please note that in the discussion section, we had already discussed some aspects of our strategy such as the focus on cytosolic proteins and the use of HEK293T cells. We now extended the discussion by explaining possible biases in our selection strategy and by including also other discussion points different from those suggested by the reviewer. Below is an overview of the changes made.
The following part was added: "We here attempted a more global analysis of the interaction profiles of N-terminal proteoforms and their canonical counterparts. However, as Virotrap, and other MS-based PPI methods, are labor-intensive, only a limited, yet well-selected set of pairs could be analyzed. Funneling all identified N-terminal proteoforms to a manageable set for Virotrap-based interactome analysis was based on several selection criteria that could have introduced biases. First, as mentioned, we focused on cytosolic proteoforms. Second, the identified peptides were stringently filtered to only select N-terminal peptides confidently originating from translation events, thus ignoring N-terminal proteoforms originating from protein processing, which further reduced the N-terminal proteoforms that could be considered for further analysis. The fraction of N-terminal proteoforms among all identified peptides is much smaller than expected from the composition our database (see figure 3A in reference https: //pubmed.ncbi.nlm.nih.gov/35788065/). From 22,003 UniProt isoforms, we identified 89, of which 83 were highly confident identifications. In analogy, from 60,661 proteoforms predicted from Ribo-seq data, we could only identify 80, including 73 with high confidence. Similar disproportions have been reported by (N-terminal) riboproteogenomics studies (https://pubmed.ncbi.nlm.nih.gov/24623590/, https://pubmed.ncbi.nlm.nih.gov/25156699/, https://www.nature.com/articles/nmeth.3688, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3817102/) and, in our opinion, highlight the need for validation of candidate proteoforms derived from Ribo-seq analysis by alternative means. Following initial filtering, a second, orthogonal selection based on biological information was made to retain the potentially most interesting pairs. From this list, a final selection was made based on criteria to prioritize candidates suited for Virotrap, which meant prioritizing proteoforms with a substantial difference at their N-termini, non-structural proteins and proteoforms with losses or gains of protein domains or motifs. This likely also introduced a bias in our results as these criteria might increase our chances of identifying differences between the interactomes of the studied proteoforms. As such, it will likely be error-prone to translate our results towards general conclusions about N-terminal proteoforms." The authors could comment or explain the discrepancy in the number of N-terminal proteoforms identified in their study compared to the literature estimates.
We suspect that the reviewer meant that we reported less N-terminal proteoforms (such as those originating from 5'UTR translation) than Ribo-seq based studies. However, the number of Nterminal proteoforms detected in our study corresponds to numbers detected by similar N-terminal proteomics approaches used to identify N-terminal proteoforms originating from different translation events (e.g. https://pubmed.ncbi.nlm.nih.gov/24623590/). On the other hand, studies also focusing on neo N-termini originating from processing -which, we like to repeat was not the aim of our current study -reported on more N-terminal proteoforms (e.g. https://pubs.acs.org/doi/full/10.1021/acs.jproteome.5b00579, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872078/), yet less N-terminal proteoforms originating from differently spliced transcripts and alternative translation initiation.
As mentioned in our answer to the previous comment, we hypothesize that our stringent filtering strategy to some extent accounted for the discrepancy compared to studies that also considered processing events. Indeed, when re-examining our data from trypsin-digested samples searched in our custom database, we found that when considering all unique N-terminal peptides (thus, only considering Ace-or AcD4-starting peptides), 5,062 peptides were identified, of which 3,600 mapped to a position beyond the second position in the protein sequence. Of these, 468 were retained after filtering for translation products, implying that we filtered out 3,132 N-terminal peptides potentially originating from proteolytic processing, which is in line with data reported in the abovementioned studies.
When evaluating the distribution of identified accessions before any filtering step, distributions of N-terminal proteoforms similar to the composition of our custom database (see below or https: //pubmed.ncbi.nlm.nih.gov/35788065/ supplementary figure S3, left side pie charts) are found. However, after the first filtering step (accession sorting), this distribution disappears as almost all peptides get linked to UniProt entries. This first filter is crucial as peptides often match multiple protein sequences, both well-annotated one as well as novel ones. As Mascot was used at the peptide level, database entries seem to have been listed pretty much at random following identification of such multi-protein matching peptides, this as Mascot deals with the protein inference problem at the protein level. To correct for this, we reordered all peptide-associated protein entries, prioritizing UniProt entries over UniProt isoform entries, and these over Ensembl entries (coming from the Ribo-Seq data) as the UniProt database is by far the most completely annotated and curated of these databases. This thus shows that the discrepancy is due to our stringent filtering approach, but also that our filtering approach is necessary to report true protein evidence of these alternative ORFs.
Additionally, also see the answer provided to the previous question, where we make a comparison with database composition and with previous riboproteogenomics studies.

s limitations and the considered approach, as baits were only tested in one setup (bait coupled to AD and tested for interaction with prey coupled to DB, and not in other set-ups such as bait coupled C-terminally to AD or bait coupled to DB)
. Therefore, we found that Y2H was reported to did not work for a the majority of baits, also likely, due to auto-activation or failure of nuclear localization of bait and/or prey, and typically reports strong PPIs [40,71]. Nevertheless, we were able to validate the interaction of PDCD4 with the full-length EIF4A1 protein, reported by Virotrap."

Minor points
Minor and technical comments (including suggestions to the Authors, so that they could improve the presentation and accessibility of their manuscript): The authors could use consistent language and abbreviation throughout the paper, especially for N-terminal / Nt and N-terminal proteoform / Nt-proteoform.
We thank the reviewer for pointing this out and we changed all use of Nt-back to N-terminal. Other abbreviations were also checked and adjusted to always use the abbreviation once it was introduced.
Abbreviations could be introduced in the Results section as well as in the Materials and Methods section.
Abbreviations were now also used in the Materials and methods section. From the author guidelines of Life Science Alliance, we noticed that the Material and Methods sections comes almost at the end. All terms were thus introduced prior to this section, if possible. Abbreviations first used in the Materials and Methods section were properly introduced and used consistently throughout the manuscript.
The resolution of figures is low, and the color schemes could be friendlier, especially in Figure 6.
We assume low figure quality is only due to the embedding in the PDF and figures will be uploaded separately in high resolution. The figures were revised by all co-authors and several lab members and no comments were made on this, therefore, we kept the color schemes. In fact, it was noticed that the color scheme allowed for easy interpretation and was used consistent over all figures.
Supplementary tables could be named the same as in the manuscript.
We always refer to Supplementary tables as Supplementary Table SX in the text and also use this format in the naming of the Excel files. We thus do not know how we should adjust the names as they already seem uniform. There might have been introduced a discrepancy in the merging of all files. We doublechecked the naming in the text and the names of the files when uploading the revised version and found no inconsistencies.

Abstract:
The abstract is well written and provides a good overview of the study aim and what was done. However, the authors could elaborate on how Nt-proteoforms originate from splice variants in the introduction section.
In the introduction, the following part was adjusted in response to this request (text in bold was added): "Studies in our lab revealed that 10-20% of protein N-termini in several human and mouse cells point to alternative translation initiation and/or alternative splicing [5]. Such N-terminal proteoforms thus stem from the same gene but differ at their N-terminus. In eukaryotes, the canonical mechanism for translation to start involves a ribosome assembling at the 5' end of a mature mRNA molecule, which then starts scanning for start codons towards the 3' end.  [2,6,7]."

Introduction:
The topic is introduced well, and the reader understands the aim and scope of the study, as well as why the topic is of interest. However, some aspects to understand the workflow are not covered well. COFRADIC and Virotrap are mentioned and linked to literature, but they are key parts of the workflow and could be explained in a few sentences.

The introduction was adjusted to: "Here, we first applied N-terminal COFRADIC [45] on the cytosol of HEK293T cells to construct a comprehensive catalogue of N-terminal cytosolic proteoforms. N-terminal COFRADIC in essence relies on two consecutive, identical chromatographic separations of peptides, interrupted by a chemical reaction with 2,4,6-trinitrobenzenesulfonic acid (TNBS) causing a hydrophobic shift of internal peptides which is exploited to capture N-terminal peptides during the second chromatographic separation [45]. We then applied stringent filtering to select proteoforms pairs for interactome analysis by Virotrap (see Figure 1), a method to study protein-protein interactions that avoids cell lysis by exploiting the characteristics of the HIV-1 p55 GAG protein which leads to the production of virus-like particles (VLPs). We then applied stringent filtering to select proteoforms pairs for interactome analysis by Virotrap (see Figure 1). In short, in Virotrap, a bait protein is fused to the C-terminus of the HIV-1 GAG protein, leading to the recruitment of the GAG-bait fusion protein at the plasma membrane where GAG multimerization occurs, followed by subsequent budding of virus-like particles (VLPs) from the cells. As the bait is coupled to GAG, this allows for co-purification of baitassociated protein partners by trapping them into VLPs. Purification of the VLPs themselves relies on co-expressing FLAG-tagged and untagged VSV-G, presented as trimers on the surface of VLPs, allowing for efficient antibody-based purification of the
VLPs. Of note, Virotrap was shown to be a sensitive PPI method, as VLPs encapsulate and preserve the protein complexes, allowing the detection of weak and transient protein-protein interactions [46]." The first three paragraphs are also repetitive in language and need rewording.
We have made some adaptations through the text to avoid this repetitive wording. In the following parts, the strikethrough text was removed.

"Eukaryotic protein-coding genes give rise to several protein variants, or proteoforms, through various mechanisms including genetic alterations, alternative promotor usage during transcription and alternative splicing during mRNA maturation, use of alternative initiation codons and stop codon read-through during translation,, numerous co-and post-translational modifications [1-3]
Crosstalk between these mechanisms greatly expands a proteome's complexity [4]. Studies of our lab revealed that 10-20% of protein N-termini in several human and mouse cells point to alternative translation initiation and/or alternative splicing [5]. Such N-terminal proteoforms thus stem from the same gene but differ at their N-terminus. In eukaryotes, the canonical mechanism for translation to start involves a ribosome assembling at the 5' end of a mature mRNA molecule, which then starts scanning for start codons towards the 3' end. Alternative start codons can be used for translation by various mechanisms such as upon leaky scanning or the use internal ribosome entry sites [6,7]. In addition, alternative splicing may give rise to transcripts that have different 5' ends (e.g. due to skipping of the first exon) [8,9]. The majority of N-terminal proteoforms are truncated at the N-terminus relative to the canonical form however, up to 6% have extended N-terminal regions presumably caused by ribosomes starting translation starting from codons in the annotated 5'UTR. N-terminal proteoforms can also carry modified N-termini different from those of the canonical protein [2,10,11]. [2,9,[12][13][14]. N-terminal proteoforms They may have different functions as the N-terminus of a protein steers several protein features such as half-life and protein localization [15,16]. Concerning the latter, many targeting signals reside at a protein's N-terminus and, consequently, N-terminally truncated or extended proteoforms may lose or gain targeting signals, causing such proteoforms to reside at different subcellular localizations [12,[17][18][19][20][21][22][23][24][25]. Several Nt-N-terminal proteoforms with such altered subcellular localization are These might be iso-functional, but thus and thus active in different compartments [19,20]. Our lab and the Kuster lab showed that pairs of N-terminal proteoforms originating from the same gene can possess different stabilities in cells [9,26,27]. Of note, mounting evidence indicates that alternative translation initiation is regulated in response to a variety of stress stimuli and/or in a tissue and a cell developmental specific manner [3,28,29]. Van Damme et al. (2014) also showed that alternative translation initiation sites are generally conserved among eukaryotes, hinting to their possible biological impact [5]. In addition, several N-terminal proteoforms have already been linked to human diseases, illustrating their potential for therapeutic intervention, diagnosing and prognosing disease [2,30].

N-terminal proteoforms are often overlooked and information on their biological function is often based on atomistic studies focusing on one gene
Other studies showed that N-terminal proteoforms may have altered functionalities [14,28,29,[31][32][33][34][35][36]]. An example is the regulator of G-protein signaling (RGS2)  Additionally, the statement "Nt-proteoforms have long been overlooked and studies on their biological function are emerging just now" needs revision since the cited references are more than 20 years old.
One reference [11] is indeed more than 20 years old, yet we wanted to state that N-terminal proteoforms are not often considered for functional studies and that the information we now have about their biological roles is mainly based on individual studies of just one proteoform. We agree with the comment of the reviewer and adjusted the sentence to the following (see below), to better suit the information/ statement we intend to give.
The sentence was adjusted to: "N-terminal proteoforms are often overlooked and information on their biological function is often based on atomistic studies focusing on one gene. "

Materials and Methods:
The analysis code should be made available, and the generation of a cytosolic proteome map of HEK293T cells needs better explanation. The sentences in bold were added to the appropriate materials and methods section: "Per sample and replicate, we obtained a unique peptide count, spectral count and NSAF (normalized spectral abundance factor) quantification.

Briefly, SAF values were first calculated per protein based on total spectral counts corrected for protein length (since longer proteins produce more peptides). Next, to accurately account for variation between samples, individual SAF values were divided by the sum of all SAFs per sample, resulting in the NSAF value. Log transformation of NSAF values was performed to achieve normal distribution of data suitable for downstream statistical analysis. Differential expression analysis across all tissues was performed using limma (3.50.3) based on log2NSAF values… "
The authors could also introduce abbreviations in the Materials and Methods section, as some were only introduced in the Results section.

See above. We double-checked the text and adjusted it where needed.
For Virotrap studies, the authors could introduce the abbreviations PR and FL at their first use, clarify what was measured, and explain when imputation was applied and why. The authors could also clarify if peptide quantities were normalized between baits and control and why missing potential interaction partners of all baits were imputed.

Introduction of FL and PR term in part of Materials and Methods: Generation of Virotrap clones in the following sentences (text in bold was added):
"Gag-bait fusion constructs were generated as described [46].

Concerning the comment on normalization, besides the normalization function embedded in the MaxLFQ algorithm, no additional normalization was performed neither on the peptide or on the protein level.
Very similar comments were made on the results section and we also would like to refer to our answers given below.

Results:
In the Interaction profiling of Nt-proteoforms and their canonical counterparts section, the authors could address MaxQuant's normalization strategies and how similar VLP contents were within VLPs. They could also clarify if VLPs of different baits can be analyzed together regarding normalization and imputation.  (Figure 4

.B). Our experiments show, that besides the interaction partners and baits, many "background proteins" are consistently identified in the VLPs. In fact, for example in the first set 458/1997 (23%) of proteins are identified in 80% of Virotrap samples, providing a basis for MaxLFQ normalization."
For the Proteoform-specific interaction partners section, the authors could explain the reason for imputation and whether it would be necessary for a more suitable analysis strategy.
There are several ways of analyzing affinity purification MS data and according to our knowledge, there is no golden standard approach. In our study, the imputed values were systematically small, adjusted to the low-end of protein intensities observed in each sample. Imputation was only performed for proteins identified in ¾ replicates of one condition. This allowed for statistical analysis of proteins unique to a given bait. An alternative strategy, without imputation, would be to obtain a statistical test results when possible and additionally consider unique proteins as interactors, which is also not ideal.
In the Studying selected differences between proteoform interactomes by AP-MS section, the authors could clarify why some proteins did not show up in the table of candidate interactors for AP-MS but were present in the Volcano plot.
There are three proteins: IFIT5, PNPT1 and APOL2 that were reported as significant proteins between the FL and PR but that are not reported as candidate interaction partners. Upon checking the profile plots of these proteins before imputation (see profile plot below, APOL2 in red, PNPT1 in blue and IFIT5 in black), one notices that all these proteins are most intense in MAVS FL samples and especially APOL2 and IFIT5 seem specific for MAVS FL as they are not identified in many other samples. However, all these proteins are identified at quite low intensities and thus do not seem strong interaction partners but their profile suggest that they could be (presence in MAVS FL samples and absent in most other samples or more abundantly present specifically in MAVS FL samples). They indeed also seem to differ between the FL and PR and we are thus not surprised that these proteins are suggested as interaction partners in the volcano plot comparison between FL-PR.
We assume that these proteins might be not reported as interaction partners due to imputation. We therefore check their profile after imputation (see below). We see especially for APOL2 and IFIT5 a large difference in the imputed values causing a highly variable profile. This could cause the protein not to be considered as significant.
This shows that our approach is not fault-proof, but as mentioned above, we still believe that our approach remains valid and we likely reported the most confident interactors. Currently no general or standard approach exist for the analysis of PPI datasets. One approach that could have helped to report APOL2 and IFIT5 as potential interaction partners would be to include black-white cases (presence/absence).
They could also evaluate the comparison of identified interaction networks to known interaction networks as mentioned in the text.

interaction partners, nine are known interaction partners listed in at least one of the three consulted PPI databases. This shows that both Virotrap and AP-MS identified known interaction partners and, besides these, both approaches also reported several novel potential interaction partners, many of which are only identified with one of the two analysis methods. This demonstrates the uniqueness of each PPI method and the difficulties often encountered when validating specific interactions. Additionally, all unique or specific interaction partners reported for MAVS PR are not reported in either BioGRID, STRING or IntAct. This could hint to an alternative function of the proteoform which is unrelated to the function of the FL protein. "
Lastly, the last paragraphs of the Interaction profiling of Nt-proteoforms and their canonical counterparts section are not well-formulated.
We think that the reviewer is pointing to the paragraphs below, which we attempted to make more understandable.
"Some selected interesting findings on proteoform-specific interactors are discussed in the following section.
For MAVS, a the pairwise test between the interactomes of FL and PR resulted in 10 significant proteins (Figure 7.A), being :PTK7, PLK1, HNRNPUL2, CEP55, CD2AP, ARRDC1, DAG1, EIF3K, TRAF2 and NUP205. Of these, only TRAF2 and PLK1 have been reported above as candidate interaction partners for MAVS FL and PR respectively. , and are thus withheld as proteins that possibly interact differently with the MAVS proteoforms. By this stringent filtering, we thus remove several proteins that, although they seem to interact differently with MAVS FL or PR, they are unlikely to be interaction partners. In fact, This is also obvious by visualizing from their intensities profiles in the different samples before imputation (Figure 7.B), which show that TRAF2 and PLK1 interact with MAVS with a significant difference in intensity between in the FL and PR interactomes. For comparison, we also show the profile of two proteins that were reported as significantly different between the FL and PR interactomes, but were removed as they were not listed as candidate interactors. A first example is DAG1, which was not identified in any of the MAVS interactomes, but while the found difference in the interactomes of the MAVS proteoforms is only due to differences in the imputed intensity values. In fact, this example highlights an imputation-based shortcoming of the data analysis software however, imputation is necessary for statistical analysis. A second example is ARRDC1, which is identified in almost all samples with an apparent lower intensity in the MAVS samples, making it thus unlikely that ARRDC1 is an interaction partner of MAVS. To conclude, it seems that MAVS PR has lost the interaction does not interact with TRAF2, which could be due to the fact that in MAVS PR, the domain required for this interaction with TRAF2 becomes outer is exposed at the N-terminal part of MAVS PR (Figure 5.A), which affects the interaction with TRAF2. On the other hand, MAVS PR seems to interact better stronger with PLK1, suggesting that MAVS PR proteoforms can both gain and lose as well as gain interactors.
For the polyadenylate-binding protein-interacting protein 1 (PAIP1), an N-terminal proteoform starting at position 113 which is a known UniProt isoform, was detected. This PAIP1 N-terminal proteoform specifically interacts with GIGYF2, ZNF598 and EIF4E2, which together form the 4EHP-GYF2 complex. GIGYF2 and ZNF598 were identified from the comparison of the FL and the PR interactomes, while ZNF598 and EIF4E2 were listed as candidate interactors of PAIP1 PR (Figure 7.C). The engagement of PAIP1 PR with the 4EHP-GYF2 protein complex could point to a different functionality of the PAIP1N-terminal proteoform versus full-length PAIP1.
Opposite to PAIP1 PR, we report that on the other hand the N-terminal proteoform (missing amino acid 1-211) of the eukaryotic initiation factor 4A-I (EIF4A1) loses several known interactions (see Figure 7.D). In the pairwise comparison between FL and PR, we found that the interaction with eight candidate eukaryotic initiation factors (EIF4A3, EIF4E, EIF4G3, EIF4B, EIF4G2, EIF4A2, EIF4H and EIF4G1), seems to be is specific for the FL, while on the side of the EIF4A1 proteoform, we identified amongst the significant candidate interaction partners several proteins involved in proteasome-mediated protein degradation as possible interactors.

Y2H screens to validate the interaction profile of N-terminal proteoforms
To support our previous findings on the interactome of N-terminal proteoforms, we performed a Yeast two-hybrid (Y2H) screen similar as reported in [8,63]. Y2H These screens were performed in which such that all baits (both canonical protein and N-terminal proteoform) Table 4 and Supplementary We thank the reviewer for her/his support of our manuscript. Thank you for submitting your revised manuscript entitled "N-terminal proteoforms may engage in different protein complexes". We would be happy to publish your paper in Life Science Alliance pending final revisions necessary to meet our formatting guidelines.
Along with points mentioned below, please tend to the following: -please delete the contents section following the title page -please consult our manuscript preparation guidelines https://www.life-science-alliance.org/manuscript-prep and make sure your manuscript sections are in the correct order -please upload a clean manuscript without any track changes or highlighted text -please add a conflict of interest statement to your main manuscript text -please add a callout for Figure S4 to your main manuscript text -in the Materials and Methods section, you write "See Supplementary Materials and Methods for additional information." I don't see this additional file, and in any case this should be incorporated into the main Materials and Methods section. We don't have a size limit on this section. If any unique References are mentioned there, please be sure to incorporate those into the main Reference list as well.
If you are planning a press release on your work, please inform us immediately to allow informing our production team and scheduling a release date.
LSA now encourages authors to provide a 30-60 second video where the study is briefly explained. We will use these videos on social media to promote the published paper and the presenting author (for examples, see https://twitter.com/LSAjournal/timelines/1437405065917124608). Corresponding or first-authors are welcome to submit the video. Please submit only one video per manuscript. The video can be emailed to contact@life-science-alliance.org To upload the final version of your manuscript, please log in to your account: https://lsa.msubmit.net/cgi-bin/main.plex You will be guided to complete the submission of your revised manuscript and to fill in all necessary information. Please get in touch in case you do not know or remember your login name.
To avoid unnecessary delays in the acceptance and publication of your paper, please read the following information carefully.

A. FINAL FILES:
These items are required for acceptance.
--An editable version of the final text (.DOC or .DOCX) is needed for copyediting (no PDFs).
--High-resolution figure, supplementary figure and video files uploaded as individual files: See our detailed guidelines for preparing your production-ready images, https://www.life-science-alliance.org/authors --Summary blurb (enter in submission system): A short text summarizing in a single sentence the study (max. 200 characters including spaces). This text is used in conjunction with the titles of papers, hence should be informative and complementary to the title. It should describe the context and significance of the findings for a general readership; it should be written in the present tense and refer to the work in the third person. Author names should not be mentioned.

B. MANUSCRIPT ORGANIZATION AND FORMATTING:
Full guidelines are available on our Instructions for Authors page, https://www.life-science-alliance.org/authors We encourage our authors to provide original source data, particularly uncropped/-processed electrophoretic blots and spreadsheets for the main figures of the manuscript. If you would like to add source data, we would welcome one PDF/Excel-file per figure for this information. These files will be linked online as supplementary "Source Data" files. **Submission of a paper that does not conform to Life Science Alliance guidelines will delay the acceptance of your manuscript.** **It is Life Science Alliance policy that if requested, original data images must be made available to the editors. Failure to provide original images upon request will result in unavoidable delays in publication. Please ensure that you have access to all original data images prior to final submission.** **The license to publish form must be signed before your manuscript can be sent to production. A link to the electronic license to publish form will be sent to the corresponding author only. Please take a moment to check your funder requirements.** **Reviews, decision letters, and point-by-point responses associated with peer-review at Life Science Alliance will be published online, alongside the manuscript. If you do want to opt out of having the reviewer reports and your point-by-point responses displayed, please let us know immediately.** Thank you for your attention to these final processing requirements. Please revise and format the manuscript and upload materials within 5 days.
Thank you for this interesting contribution, we look forward to publishing your paper in Life Science Alliance. Thank you for submitting your Research Article entitled "N-terminal proteoforms may engage in different protein complexes". It is a pleasure to let you know that your manuscript is now accepted for publication in Life Science Alliance. Congratulations on this interesting work.
The final published version of your manuscript will be deposited by us to PubMed Central upon online publication.
Your manuscript will now progress through copyediting and proofing. It is journal policy that authors provide original data upon request.
Reviews, decision letters, and point-by-point responses associated with peer-review at Life Science Alliance will be published online, alongside the manuscript. If you do want to opt out of having the reviewer reports and your point-by-point responses displayed, please let us know immediately. ***IMPORTANT: If you will be unreachable at any time, please provide us with the email address of an alternate author. Failure to respond to routine queries may lead to unavoidable delays in publication.*** Scheduling details will be available from our production department. You will receive proofs shortly before the publication date. Only essential corrections can be made at the proof stage so if there are any minor final changes you wish to make to the manuscript, please let the journal office know now.

DISTRIBUTION OF MATERIALS:
Authors are required to distribute freely any materials used in experiments published in Life Science Alliance. Authors are encouraged to deposit materials used in their studies to the appropriate repositories for distribution to researchers.
You can contact the journal office with any questions, contact@life-science-alliance.org Again, congratulations on a very nice paper. I hope you found the review process to be constructive and are pleased with how the manuscript was handled editorially. We look forward to future exciting submissions from your lab.