-->PPATHOGENS-D-25-03219

Non-human primate LIBRA-Seq accelerates neutralizing antibody discovery in RM vaccinated against HIV-1

PLOS Pathogens

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6) Thank you for stating "Data tables for expression counts for single-cell RNA-seq for memory B cells are are deposited in NCBI’s Gene Expression Omnibus and are accessible through the Gene Expression Omnibus (GEO) under accession number (TBD)." Please provide us with the accession number of the dataset.

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Reviewers' Comments:

Reviewer's Responses to Questions

Part I - Summary

Please use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship.

Reviewer #1: The manuscript by Edwards et al. describes the adaptation of LIBRA-seq to characterize antibody responses in rhesus macaques. The authors developed DNA-barcoded BG505 SOSIP probes for sorting antigen-specific B cells, 10X capture, and single-cell RNA sequencing. They validated this approach using engineered cell lines and then applied it to identify antigen-specific memory B cells from six vaccinated animals. This approach recovered four previously identified neutralizing antibodies from animal RUp16, while identifying six additional neutralizing clones across the cohort. High-throughput analysis revealed patterns of clonal expansion and shared genetic features across animals. The LIBRA-seq scores appear useful for prioritizing antibody candidates for functional testing. However, the manuscript lacks a direct comparison between LIBRA-seq and conventional antibody cloning methods, as well as a discussion of LIBRA-seq’s limitations. Most notably, while the authors assert that LIBRA-seq "accelerates" antibody discovery, they provide no quantitative comparisons of cost, time, or workflow efficiency relative to conventional approaches. Additionally, the identification of a potent neutralizing antibody (RUp16_158_TriplePositive) that would have been excluded based on their filtering strategy, which requires biotin-bait negativity, raises concerns about the analytical pipeline that are inadequately addressed. With revisions addressing these comparisons and technical limitations, this work would represent a valuable methodological contribution to preclinical non-human primate studies.

Reviewer #2: In this study, Edwards et al apply the LIBRA-seq platform to memory B cells from rhesus macaques that received an experimental HIV vaccine, enabling immunogen-specific between IgH/L sequences to be linked with their antigen specificity. They report findings from a total of 6 vaccinated animals, one of which was previously described to have mounted a particularly potent response. The authors validate the performance of their approach by analyzing the recovery of previously-characterized clones, and also by expressing newly-identified antibodies, which together indicate good sensitivity and specificity. Overall, the study is soundly-designed, well-communicated and its conclusions are supported by the data shown.

In light of the prior studies by these authors on the same types of antibodies from the same animals, and reaching a number of the same scientific conclusions, I note that the main import of the work is as a methodological advance. However, these relevant citations are included and I think this methodological focus is frankly communicated and discussed.

Reviewer #3: Edwards, et.al., describe the adaptation and a proof-of-concept dataset demonstrating LIBRA-seq identification of binding and neutralizing antibodies targeting BG505 SOSIP in the rhesus macaque model of HIV/SIV vaccination. The team demonstrates that the adapted method is robust, reproduces prior results, and increases screening throughput for the identification and characterization of antigen-specific monoclonal antibodies. These results represent a discernable improvement over more classical, plate-based methods, and will allow more robust evaluation of humoral responses in the context of pre-clinical studies with non-human primates. This reviewer would like to commend the authors on the extremely thorough description of methodological details, which will surely encourage others to build from these findings. Overall, the paper describes a new approach that will surely increase our understanding of antibody responses during pre-clinical vaccination studies and, with relatively minor updates, should be acceptable for publication in PLoS Pathogens.

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Part II – Major Issues: Key Experiments Required for Acceptance

Please use this section to detail the key new experiments or modifications of existing experiments that should be absolutely required to validate study conclusions.

Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject".

Reviewer #1: 1. The authors assert that LIBRA-seq "accelerates" neutralizing antibody discovery in rhesus macaques. However, they provide no quantitative data to support this claim. The manuscript should include explicit comparisons of (i) hit rates for neutralizing antibody identification between LIBRA-seq and conventional approaches and (ii) estimates of the time required from sample collection to antibody characterization for each approach. Given that the authors previously characterized RUp16 using conventional methods, these comparative data should be readily available. Without such quantitative support, claims of improved efficiency cannot be substantiated.

2. The observation that 50% (2/4) of antibodies with high biotin-bait LIBRA-seq scores bound BG505 SOSIP by ELISA, with Rup16_158_TriplePositive exhibiting potent neutralizing activity, indicates that the biotin-negative filtering strategy may misclassify antigen-specific clones. The authors should quantify how many cells were excluded based on biotin-positivity across the entire cohort and determine whether these excluded cells cluster with double-positive for BG505 and negative for biotin (as observed for RUp16_158_TriplePositive and its dual-positive clonal relatives). They should also discuss the implications of these findings and recommend filtering options for future studies implementing LIBRA-seq.

Reviewer #2: (No Response)

Reviewer #3: Major Concerns:

- Antibody clonal assignments were made by identifying shared V and J genes, and shared CDR3 length, alongside CDR3 identity >70% at the nucleotide level. This seems quite a low identity threshold for a clonal grouping. Further explanation as to how and why these parameters were set for identifying members of the same clonal group would strengthen the overall narrative.

- Figure 4 and associated text demonstrate comparative analyses between the bnAbs identified by LIBRA-seq versus prior studies using more conventional methods in animal RUp16. Approximately 50% (24/48) of the identified heavy chains and 90% (44/48) of light chains agreed with prior analyses. Although the agreement on light chains is clear, the authors do not comment on the lack of overlap of heavy chains. Further discussion on whether this may represent sampling bias or due to a different time point examined would be helpful to agree with the authors conclusions that this constitutes clear orthogonal validation of the LIBRA-seq approach.

- The final Results section defines repertoire features associated with those monoclonal Abs identified by the LIBRA-seq method, including the public usage of IGHV4-79. This is a great example of how this type of method could identify new germline alleles to be targeted by rationally designed immunogens using reverse vaccinology. It was unclear whether the additional animals examined (beyond Rup16) had been characterized using more conventional methods. If the data are available, it would considerably strengthen the overall conclusions to perform similar analyses with “conventional” data. In the animals (or, if not available, if just in Rup16) did the authors see the use of IGHV4-79? Did they see high levels of SHM? In general, these types of broader analyses between standard and LIBRA-seq methods would assist in alleviating any concerns regarding LIBRA-seq-specific bias in repertoire capture and characterization.

- This adapted LIBRA-seq method identified both binding and neutralizing antibodies. The most important concern for the vaccine field is to focus on the identification of bnAbs, as binding antibodies are developed at high titers in most infected individuals. It would be beneficial for the authors to discuss possible future improvements to the assays or analyses parameters that may enhance the discernment between binding and neutralizing antibody identification.

- Data sharing remains unclear, as GEO accessions are “TBD” and git-hub documentation “will be made available”. These availabilities need to be guaranteed and made available to reviewers prior to acceptance.

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Part III – Minor Issues: Editorial and Data Presentation Modifications

Please use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity.

Reviewer #1: 1. The authors should include more discussion of the technical challenges of implementing LIBRA-seq and the approach's limitations, including practical considerations for those considering LIBRA-seq, the technical expertise required, and the computational resources. This information will help readers assess the feasibility of implementing LIBRA-seq.

2. HVV should be defined the first time it is used in the manuscript.

Reviewer #2: – Given that only a single antigen is being used, the contribution of the DNA-barcode on the antigen probes is somewhat unclear: almost all of the discrimination appears to have been done by the fluorescent sorting (eg see Fig 3). How much would the sensitivity / specificity of recovering immunogen-specific IgH/Ls actually have dropped if there was no DNA barcode quantification available? In addition to excluding what appear to be a small number of fluorescent false positives, perhaps the main value of the barcode is allowing a quantitative estimation of binding signal strength / reliability? In that vein, it would have been helpful to see a more thorough and quantitative analysis of sensitivity / specific across the LSS range, and/or some further discussion on this point.

– The titration in Figure 2 would have benefitted from replicates, or an explanation of why none were performed.

– Fig 6: "D" missing from legend.

Reviewer #3: Minor concerns:

In general, the paper was well written and clear. There were a number of typos and minor comments listed here to assist in the readability of the manuscript once it is published:

- Line 269: there are words missing at the end of this sentence, “…0.022-0.039 in IgK, and (0.025-0.044).

- Line 283: I believe that this wording should be adjusted to, “high resolution, higher throughput manner…” to more accurately represent the data presented.

- Lines 289-291, “In addition to recovering the previously identified neutralizing clones, we were able to identify shared gene usage and clonotypes across multiple variants.” While not untrue, this statement felt like a bit of an overreach, as the authors did not identify an exact overlap between methods. This reviewer suggests rewording to “…was able to identify partial shared gene usage…” to better temper the results.

- Lines 428 and 440. Please use the correct symbol for degrees.

- Line 447, this sentence starts with, “(AMQAX1000) Appropriate volume…” Clearly something was lost in editing, please correct.

- Line 452-453, Poor grammar and articles are missing; please review and correct.

- Throughout manuscript – the Ramos cell line is referred to as “ramos” and “Ramos”. Please decide regarding capitalization and be consistent throughout the manuscript.

- Lines 533-534, it is unclear how and what was “combined at 1 to 1 overnight…”. Were streptavidin-AF and oligonucleotide mixed at 1:1 based on vol:vol, or mass:mass? Clarify methods here to increase reproducibility.

- Multiple times the term “x” was used as shorthand for replicates. Please expand. For example, line 551, “Splenocytes were washed 3x with FACS buffer…” should be “Splenocytes were washed three times with FACS buffer...”.

- Single-cell RNA-seq using 10X Genomics equipment and reagents was critical for this study. However, these supplies are referred to repeatedly as either “10x” or “10X”. Please use the proper “10X Genomics” and be consistent throughout draft.

- Lines 626-636, this section appears to be completely duplicated from the prior section (lines 590-601) and can be removed.

- The “Libra-seq Scoring” methods section (lines 637-649) also seems almost word-for-word duplicated from an earlier methods section (lines 602-612). Please rework to limit redundancy.

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Dear Dr. Bosinger,

We are pleased to inform you that your manuscript 'Non-human primate LIBRA-Seq accelerates neutralizing antibody discovery in RM vaccinated against HIV-1' has been provisionally accepted for publication in PLOS Pathogens.

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PLOS Pathogens

Susan Ross

Section Editor

PLOS Pathogens

Sumita Bhaduri-McIntosh

Editor-in-Chief

PLOS Pathogens

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Michael Malim

Editor-in-Chief

PLOS Pathogens

orcid.org/0000-0002-7699-2064

***********************************************************

Reviewer Comments (if any, and for reference):

Reviewer's Responses to Questions

Part I - Summary

Please use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship.

Reviewer #1: The authors have addressed the major concerns raised in the initial review. The addition of Table 2 provides a direct comparison between LIBRA-Seq and their conventional plate-based cloning method, supporting the claim that LIBRA-Seq reduces the time and labor required for antibody discovery. The overview of the technical requirements and limitations of the NHP-adapted LIBRA-Seq workflow is helpful for readers new to the technique. The reanalysis of triple-negative cells clarifies their relationships with antigen-specific lineages, and the Discussion recommends treating positive-bait signals as a quality-control measure rather than for strict exclusion. With minor editorial corrections detailed below, the adaptation of LIBRA-Seq to nonhuman primate models provides an additional tool for evaluating antigen-specific B cells in preclinical studies.

Reviewer #2: The authors have satisfactorily addressed my concerns.

Reviewer #3: The authors carefully considered the feedback provided by all three reviewers, made appropriate changes to strengthen the manuscript, and more thoroughly describe the implementation and limitations of the LIBRA-seq methods. This reviewer believes the revised manuscript to now be suitable for publication.

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Part II – Major Issues: Key Experiments Required for Acceptance

Please use this section to detail the key new experiments or modifications of existing experiments that should be absolutely required to validate study conclusions.

Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject".

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: N/A

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Part III – Minor Issues: Editorial and Data Presentation Modifications

Please use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity.

Reviewer #1: 1. The number of dual-positive antibodies tested by ELISA is inconsistent across the text, Figure 5, and Table 2. Line 238 states that “All 30 antibodies with LIBRA-Seq scores denoting a high specificity for BG505 SOSIP exhibited binding via ELISA,” and Table 2 lists 30 antibodies as expressed. However, Figure 5B shows only 29 antibodies (with only four antibodies from animal Rlr15), and two antibodies from animal Rys15 that do not bind appreciably to BG505 SOSIP. The “Binding Abs (by ELISA)” row of Table 2 reports “27/29 93% overall,” which is consistent with Figure 5B but not the statement on line 238. The authors should reconcile these discrepancies and update the text to accurately reflect the number of samples run and their binding to BG505.

2. The reference to Suppl. Fig. S4A on line 226 appears incorrect. Based on the context (sorting of biotin-negative memory B cells from the five additional vaccinated animals), this citation should likely be Suppl. Fig. S5A. The authors should verify the correct reference to the supplementary figure.

Reviewer #2: (No Response)

Reviewer #3: N/A

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Reviewer #1: No

Reviewer #2: Yes: John A Altin

Reviewer #3: No