Methods for identifying conformational epitopes

Abstract

The present invention provides a method for identifying a conformational epitope of a protein antigen formed from at least two different peptides comprising sequences from the protein antigen, comprising the steps of: - selecting at least one first peptide comprising a sequence from the protein antigen that is recognized by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least one individual immunized against the protein antigen; and -3·10 from the first peptide in the three-dimensional structure of the protein antigen -9 selecting at least one second peptide located at a distance of 1 m or less and comprising a sequence from the protein antigen recognized by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least one individual immunized against the protein antigen of the previous step; Including, The method relates to a method wherein the at least one first peptide and the at least one second peptide form a conformational epitope of a protein antigen.

Description

[Technical Field]

[0001] The present invention relates to methods for identifying conformational epitopes, as well as methods for preparing antibodies against said conformational epitopes. [Background technology]

[0002] Interest in therapeutic monoclonal antibodies continues to grow year by year. Indeed, their highly specific affinity for antigens allows them to provide highly effective medical treatments. Thus, between 2005 and 2017, the number of monoclonal antibodies approved by the U.S. Food and Drug Administration increased from 2 to 64.

[0003] However, there are still significant obstacles to overcome in the preparation of effective monoclonal antibodies.

[0004] In fact, the selection of B lymphocytes from which monoclonal antibodies are derived is often performed by screening among all antibodies that recognize all or part of the three-dimensional structure of the target protein antigen. This screening process, which involves many steps, remains complex, as explained in Saeed et al. (2017) Front. Microbiol. 8:495. Antibodies targeting linear epitopes are also frequently obtained, which generally have lower affinity than conformational antibodies that simultaneously recognize different parts of the protein antigen's three-dimensional structure. These conformational antibodies correspond to epitopes derived from the protein's three-dimensional, tertiary, or quaternary structure, which in most cases provide the antibody with the best affinity and therefore most reliably achieve their biological function, particularly neutralization of their target. This neutralization by the generated monoclonal antibodies can be achieved by direct blocking of the protein in question by the antibody or by opsonization of the target microorganism by the antibody. In the latter case, the antibody's constant region may contain specific peptide sequences that enable recognition by immune system cell receptors or the complement system.

[0005] Therefore, obtaining monoclonal antibodies specific for conformational epitopes, thus making it possible to recognize the three-dimensional structure of the target antigen, should improve the avidity of these antibodies and therefore their use as experimental tools, diagnostic markers or immunotherapeutics.

[0006] In this regard, Tsumoto et al (2019) Immunotherapy 11:119-127 propose preparing monoclonal antibodies against conformational epitopes of antigens by immunizing mice with a DNA molecule encoding the antigen, isolating B lymphocytes, and then fusing them with myeloma cells expressing this antigen to obtain hybridomas that produce monoclonal antibodies specific to the three-dimensional structure of the antigen.

[0007] However, this process, although it produces monoclonal antibodies against conformational epitopes, is relatively complicated to carry out.

[0008] What remains to be done is to identify conformational epitopes and provide an easily implemented process for obtaining monoclonal antibodies to these conformational epitopes. [Prior art documents] [Non-patent literature]

[0009] [Non-Patent Document 1] 1Saeed et al.(2017)Front.Microbiol.8:495 [Non-patent document 2] 2Tsumoto et al (2019) Immunotherapy 11:119-127 Summary of the Invention [Problem to be solved by the invention]

[0010] The present invention arises from the inventors' unexpected discovery that it was possible to identify conformational epitopes of a protein antigen by combining screening of peptides derived from the protein antigen against sera from individuals immunized against the protein antigen and localization of the peptides relative to each other in the three-dimensional structure of the protein antigen. [Means for solving the problem]

[0011] The present invention provides a method for identifying a conformational epitope of a protein antigen formed from at least two different peptides comprising sequences derived from the protein antigen, comprising the steps of: - selecting at least one first peptide comprising a sequence from the protein antigen that is recognized by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least one individual immunized against the protein antigen; and -3·10 from the first peptide in the three-dimensional structure of the protein antigen -9 selecting at least one second peptide located at a distance of 1 m or less and comprising a sequence from the protein antigen recognized by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least one individual immunized against the protein antigen of the previous step; Including, The method relates to a method wherein the at least one first peptide and the at least one second peptide form a conformational epitope of a protein antigen.

[0012] The present invention also relates to a plurality of different peptides, each of whose sequence is derived from a protein antigen sequence, and each of the different peptides is linked to a fluorophore having a different fluorescence emission wavelength.

[0013] The present invention also relates to a plurality of, in particular all, first and second peptides obtained by carrying out the method for identifying conformational epitopes as defined above for a protein antigen, wherein the first and second peptides are each linked to a fluorophore having a different fluorescence emission wavelength.

[0014] The present invention also relates to a method for selecting lymphocytes that recognize a protein antigen from a population of cells, comprising the step of identifying at least one lymphocyte that binds to at least two different peptides comprising sequences from the protein antigen that form a conformational epitope of the protein antigen, wherein the conformational epitope is identified by carrying out the method for identifying conformational epitopes defined above.

[0015] The present invention also relates to a process for preparing at least one antibody or antibody fragment against a protein antigen, wherein the antibody or antibody fragment is prepared from at least one B lymphocyte obtained by carrying out the lymphocyte selection process defined above. DETAILED DESCRIPTION OF THE INVENTION

[0016] As used herein, the term "comprising" is synonymous with "including," "containing," or "encompassing," i.e., when an object "comprises" one or more features, features other than those mentioned may also be included in the object. Conversely, the phrase "consisting of" means "consisted of," i.e., when an object "consists of" one or more characteristics, the object cannot include features other than those mentioned.

[0017] composition The at least one composition comprising antibodies or antibody-bearing B lymphocytes may be of any type likely to contain B lymphocytes or antibodies.

[0018] The at least one composition may be obtained from a single individual or from several individuals. Preferably, the at least one composition is obtained from a biological sample or specimen, such as a whole blood, serum, ascites, or bone marrow sample or specimen, of one or more individuals.

[0019] Preferably, at least one composition is a population of peripheral blood mononuclear cells (PBMCs).

[0020] At least one composition may contain only B lymphocytes or may be enriched for B lymphocytes. In particular, the selection may be performed using a ligand, particularly an antibody, that targets a membrane marker specific for B lymphocytes, and the antibody may be coupled to a magnetic bead or a luminophore, particularly a fluorophore, to facilitate detection, selection, isolation or purification of lymphocyte-antibody complexes.

[0021] By "B lymphocyte" is intended any cell of the B lineage, such as a naive B lymphocyte, an activated B lymphocyte, a memory B lymphocyte, a plasmablast or a plasma cell, especially one that is long-lived.

[0022] As will be appreciated by those skilled in the art, B lymphocytes recognize protein antigens through the antibodies they carry.

[0023] antibody As intended herein, the term "antibody" refers to whole antibodies as well as to at least one antigen-binding portion, e.g., a V L and / or V H The present invention encompasses antibody fragments, including Fab, F(ab')2 and scFv fragments. Antibodies according to the present invention may be derived from a single species and may be chimeric, humanized or human. Antibodies may be monospecific or bispecific. Furthermore, antibodies according to the present invention may be monomeric or multimeric, particularly dimeric or pentameric. Antibodies according to the present invention may be of isotype A, D, E, G or M, preferably G.

[0024] The antibody against the protein antigen is preferably an antibody that recognizes a conformational epitope of the protein antigen.

[0025] The antibody against the protein antigen is preferably an antibody specific to the three-dimensional structure of the protein antigen.

[0026] The antibody against the protein antigen is preferably a monoclonal antibody.

[0027] Antibodies to protein antigens can be prepared from purified B lymphocytes according to a number of techniques well known to those skilled in the art.

[0028] For example, B lymphocytes can be fused, possibly after clonal expansion, with myeloma cells to obtain monoclonal antibody-producing hybridomas. Also for example, DNA sequences encoding all or part of an antibody, particularly the variable portions thereof, can be cloned, particularly from lymphocyte messenger RNA, and then recombinantly expressed by cultured cells, optionally after insertion into a humanized antibody construct.

[0029] individual Preferably, the individual immunized against the protein antigen is a non-human mammal or a human.

[0030] Immunization against a protein antigen can be natural, due to an infectious agent such as a virus, bacterium, or eukaryote that carries and / or expresses the protein antigen in an individual. Immunization against a protein antigen can also be artificially induced, particularly by active immunization with a vaccine comprising the protein antigen or a portion thereof, or by inducing the production of the protein antigen in an individual, particularly with a live vaccine, particularly an attenuated vaccine, an inactivated vaccine, a subunit vaccine, a viral vector vaccine, or a DNA or RNA vaccine.

[0031] As intended herein, a "strong responder" is an individual whose immune response to a peptide or protein antigen is stronger than that of other individuals from the same population.

[0032] peptide As intended herein, a sequence derived from a protein antigen is a contiguous amino acid residue sequence portion or fragment of the entire amino acid residue sequence of the protein antigen.

[0033] Preferably, the protein antigen sequence is fragmented into at least 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 200, 300, 400, or 500 different peptide sequences.

[0034] Preferably, the protein antigen sequence is fragmented into up to 1000, 500, 400, 300, 200, 100, 90, 80, 70, 60, 50, 45, 40, 35, 30, 25, 20, 15, 10, or 5 different peptide sequences.

[0035] Preferably, the at least two different peptides is at least three, four or five different peptides.

[0036] Preferably, the at least two different peptides is a maximum of six, five or four different peptides.

[0037] Preferably, each of the at least two different peptides comprises 6 to 50 amino acid residues, 6 to 40 amino acid residues, 6 to 30 amino acid residues, 6 to 25 amino acid residues, 6 to 20 amino acid residues, 6 to 15 amino acid residues, 10 to 30 amino acid residues, 10 to 20 amino acid residues, 12 to 20 amino acid residues, 10 to 18 amino acid residues, or 10 to 15 amino acid residues.

[0038] Preferably, the at least two different peptides each comprise at least 6, 7, 8, 9, 10, 11 or 12 amino acid residues.

[0039] Preferably, the at least two different peptides each contain no more than 50, 40, 30, 25, 20 or 15 amino acid residues.

[0040] Preferably, at least two peptides comprise non-overlapping sequences from the protein antigen. As intended herein, non-overlapping sequences are such that they do not overlap within the primary structure of the antigen, i.e., they are non-contiguous peptides.

[0041] Preferably, at least two peptides are at least 3·10° apart from each other in the three-dimensional structure of the protein antigen. -9 m (30 Å), 2.5·10 -9 (25 Angstroms)2·10 -9 m (20 angstroms), 10 -9 The distance is less than 10 Å (m).

[0042] The three-dimensional structure of a protein antigen can be obtained by X-ray crystallography, nuclear magnetic resonance (NMR), microscopy, or even by computer prediction of the three-dimensional structure using, for example, Alphafold 2 software (Jumper et al. (2021) Nature 596:583-589; URL: alphafold.ebi.ac.uk).

[0043] The distance between at least two different peptides can be calculated by many methods well known to those skilled in the art.It can be the average distance between each amino acid residue of one of the peptides and each amino acid residue of the other peptides.Preferably, it is the minimum distance between each amino acid residue of one of the peptides and each amino acid residue of the other peptides.

[0044] As intended herein, the distance between two amino acid residues is the distance between the respective alpha-carbon centers of each residue.

[0045] antigen The protein antigen according to the present invention can be any kind of protein or protein complex, in particular it can be a monomeric or multimeric protein, in particular a homo- or heteromultimer.

[0046] Preferably, the protein antigen is composed of one or more proteins containing up to 10,000, 5,000, 2,500, 1,000 or 500 amino acid residues.

[0047] Preferably, the protein antigen is composed of one or more proteins comprising at least 25, 50, 75, 100 or 200 amino acid residues.

[0048] Preferably, the protein antigen is composed of one or more proteins containing 25 to 10,000 or 25 to 5,000, more preferably 50 to 2,500, and even more preferably 75 to 2,000 amino acid residues.

[0049] Protein antigens may consist solely of amino acid residues or may contain aprotic moieties in addition to amino acid residues. Proteins may be substituted with at least one polysaccharide and / or at least one lipid. Furthermore, proteins may contain one or more prosthetic groups, such as heme groups, cofactors, nucleic acids, or iron-sulfur clusters.

[0050] Protein antigens can be derived from any type of organism. Preferably, the protein antigen is derived from an infectious agent or a human or animal protein.

[0051] In particular, protein antigens can be obtained by purification from organisms that naturally produce them or by recombinant production from cell cultures of any kind (eukaryotic or prokaryotic).

[0052] recognition Preferably, the recognition of the peptide by the antibody or at least one composition comprising antibody-bearing B lymphocytes is determined using a peptide microarray (also known as an ELISA chip), or by phage display of the peptide, or by ELISA for the peptide, techniques well known to those skilled in the art of epitope mapping.

[0053] Preferably, the peptides are labeled with different fluorophores and their recognition by at least one composition comprising antibody-bearing B lymphocytes is measured by fluorescence-assisted cell sorting (FACS), using a FACS that allows for the simultaneous detection of at least 5, 10, 15, 20, or 25 different fluorescence wavelengths.

[0054] Preferred Embodiments In a first embodiment of the method for identifying a conformational epitope as defined above, the at least one first peptide and the at least one second peptide are selected from a plurality of different peptides comprising sequences derived from the protein antigen as a result of recognition by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least two different individuals immunized against the protein antigen.

[0055] Preferably, according to this first embodiment, at least two different individuals are strong responders to at least one first peptide and at least one second peptide of the plurality of different individuals immunized against the protein antigen.

[0056] According to this first embodiment, epitope mapping is performed using an ELISA chip. The protein is cleaved into overlapping peptides that completely cover it, if possible, and the response of antibody compositions to the peptides can be measured simultaneously. Alternatively, a phage display approach can be used, in which the expressed sequences can correspond to the target protein or can be random. In the latter case, only regions of the target protein that are sufficiently similar to the sequence of the peptide displayed by the phage and are identified as "positive" are considered. The three-dimensional structure of the protein antigen (possibly several, if the antigen has several possible conformations) is used to calculate the distance between the peptides. This distance can correspond to the minimum distance separating the amino acids of two peptides, but other forms of distance calculation, such as the distance between the central amino acids of the peptides, can also be used. If the three-dimensional structure of the protein is not available, it can be predicted using reliable prediction tools such as Alphafold 2. Once these data are known, a matrix of distances between all paired peptides becomes available. If it is desired to improve the method by working directly at the three-dimensional level of triplets of discontinuous peptides, a 3 × 3 matrix can also be used, or even, for example, a matrix of distances between triplets of non-contiguous peptides, with distances of 3 × 10 from each other. -9 One can even use 4x4 or more by identifying all peptides that are less than a millimeter apart.

[0057] Then, peptides whose compositions show parallel or correlated responses are searched for, which means, for example, that the same strong responders to these peptides are found in the group.Generally, when only a portion of subjects strongly react to a given peptide (rarely more than half, or rarely even more than one-third), peptides with the same "strong responders of the group" will be searched for.For example, peptides whose subjects in the top percentile (for example, 25%, 30%, or even 50%) of antibody response are the same as those within x individuals are searched for.The fewer individuals in the study, the lower x will be; the more individuals studied, the higher x will be.Typically, when the response of a group of 24 individuals is studied, the top 25% (6 individuals) or top 33% (8 individuals) can be obtained, and due to the possible flexibility of different individuals in the selected top group, 5 or 7 strong responders can be obtained from the top 6 or 8 percentiles, respectively. If 60 compositions are available, the top 25% or top 30% can be obtained, with 15 or 18 common individuals, respectively, with flexibility to select 1, 2, 3, or more common individuals, resulting in 13, 14, or 15 common individuals from 15, or 15, 16, 17, or 18 common individuals from 18. To perform these calculations, flexible testing software can be used, allowing the number of common individuals obtained according to peptide pairs or triplets and the selected conditions to be enumerated. Alternatively, correlation coefficients between responses to peptides can be used, but this may be less accurate unless one adheres to a group of patients with strong responses from high antibody response percentiles.

[0058] As a result of the above operations, a table of peptide pairs or triplets is obtained with respect to the coefficient, i.e., the number of strong responders in the common or high correlation coefficient, for each peptide pair. Based on these results, the best peptide pairs that meet sufficiently stringent criteria for the number of strong responders in the common or high correlation coefficient can be determined based on the number of strong responders in the common or high correlation coefficient composition. When studying antibody responses to several proteins simultaneously, one way to distinguish the best correlation of peptide pairs from the same protein from background noise would be to examine the best values ​​found for peptide pairs located on different proteins. These pairs usually do not correspond to conformational epitopes unless the proteins form multimers. Therefore, the best inter-protein value or this best value minus 1 can be used as the threshold to be considered.

[0059] Because the distance between peptides is known, for each protein tested, the distance is 30, 25, or 20 Å (i.e., 3 10 -9 , 2.5·10 -9 or 2·10 -9Discontinuous peptide pairs with distances less than 100 Å (m) can be distinguished from those with distances greater than 20, 25, or 30 Å. As previously observed, this distance threshold is important because studies have shown that epitopes recognized by antibody B epitopes measure an average of 10-15 Å, with a maximum of 26-30 Å (Cao et al. (2011) Immunome Research 7:3:1). However, this value can of course be modified to accommodate smaller distances, e.g., 10, 15, or 20 Å, or larger distances, e.g., 30 or even 35 Å. We observed that the number of peptide pairs with high correlation values ​​in the peptide pair matrix increases significantly relative to pairs with distances less than 25 Å. The only possible explanation for this enrichment of close peptide pairs, e.g., at a maximum distance threshold of 25 Å, is that these peptide pairs correspond to peptides recognized by the same antibody in a given serum.

[0060] Once these conformational epitopes are identified, cloning antibodies is straightforward. Immunized subjects with a common response to two or three peptides can be identified precisely because these subjects are used to select the peptide pairs or triplets that form the conformational epitopes. Among all possible peptide pairs, the peptide with the higher ELISA value may be preferred. Among all possible patients, the patient with the highest ELISA value may also be selected. Once these conformational antibody-producing (and potentially neutralizing) subjects are identified, several experimental methods are then possible for cloning antibody-producing B lymphocytes from their PBMCs using knowledge of the conformational epitope peptides. Any method can be used to select B lymphocytes that recognize the identified conformational peptides, two of which are shown below:

[0061] For example, PBMCs can be transformed with EBV virus, followed by selection of antibody-producing clones through dilution / selection cycles, each time selecting a group of cells that produce antibodies that recognize two, three, or four peptides of a pair, depending on the number of peptides identified in the conformational epitope. This selection can be performed after a sufficient number of clones have been obtained. Transformation into antibody-producing B strains can also be achieved by fusing the transformed strain to obtain hybridomas, according to methods well known to those skilled in the art.

[0062] b. Optionally, after culturing the individual, one can attempt to directly select B lymphocytes that recognize two, three, four, or five peptides from the individual's PBMCs by FACS, depending on the number of peptides identified in the conformational epitope. The surface antibodies of the B lymphocytes of interest can then be labeled with the selected fluorochrome-labeled peptide and selected by FACS. Alternatively, one can select B lymphocytes with a peptide coating that adheres to the plate through an adhesion / wash cycle to eliminate non-adherent lymphocytes.

[0063] Once the right B lymphocytes are cloned, monoclonal antibodies can be produced directly by conventional culture methods, or identified by sequencing, or recloned by genetic engineering into cassettes, which are used to reinsert DNA corresponding to the sequenced antibody genes into the genome of strains suitable for mass production of monoclonal antibodies.

[0064] In a second embodiment of the method for identifying a conformational epitope as defined above, the at least one first peptide and the at least one second peptide are selected from a plurality of different peptides comprising a sequence derived from a protein antigen as a result of recognition by at least one composition comprising an antibody or antibody-bearing B lymphocytes from the same individual.

[0065] Preferably, according to this second embodiment, the at least one first peptide and the at least one second peptide are strongly recognized among a plurality of different peptides comprising a sequence derived from the protein antigen.

[0066] The first embodiment described above may be less easily applied to the small number of individuals analyzed. Another approach, according to the second embodiment, is to search for peptides to which the individual responds significantly, for example, to take peptides for which the response in the individual is greater than the median of all peptides plus one standard deviation, and project them directly onto the three-dimensional structure of the protein antigen. If the peptides thus determined to be positive in the antibody response are found to be more than 30 Å (i.e., 3·10 -9 If two peptides are found adjacent to each other at a distance of less than 1 m, it can be assumed that a three-dimensional epitope is involved, potentially necessitating the purification of cells from that individual that simultaneously recognize both peptides, as described above. These thresholds are arbitrary and can be modified depending on the number of peptide n-uplets found, with more if there is not enough signal, or fewer if there are too many n-uplets (n≧2). For example, instead of taking the median + 1 standard deviation, one could take the median + 2 standard deviations, or the 75th or 90th percentile of the antibody response to the peptide, etc. The size of the epitope can also be varied, from 30 to 25, or even 20, 15, or 10 angstroms. These approaches can be applied to a small number of individuals by searching for adjacent peptide n-uplets (n≧2) found in all or some of the individuals tested.

[0067] The method described in the previous paragraph for searching for n-uplets (n >= 2) of spatially close responder peptides also applies when there are many individuals in a group. Thus, one can search for peptides that are significantly recognized by a large number of subjects (e.g., responders to peptides above the 75th percentile of responses to this peptide, or above the median + 1 standard deviation), and then search for neighboring peptides in the protein's three-dimensional structure (within 30 Å, or within 25, 20, 15, or even 10 Å of each other). Also, there may be well-recognized peptides, in which case they correspond to pairs of peptides that may form conformational epitopes, or none at all, in which case one can systematically test all neighboring peptides to see if the peptides in the pair are simultaneously recognized by the individual's B lymphocytes.

[0068] Another method for identifying good peptide n-uplets (n≧2) is to select peptides found in a group of protected individuals with, for example, potentially neutralizing antibodies, and eliminate peptide n-uplets found in a group of diseased individuals whose antibodies would likely not have been protective. This discriminatory approach can effectively work on small groups of subjects to attempt to select the best peptide n-uplets (n≧2), i.e., the best conformational epitopes.

[0069] In some cases, ELISA data may be available for only a limited number of peptides and individuals, or even for a single peptide and a single individual. In this case, if a preferred peptide is selected because it elicits responses in one or more individuals, peptides within 30 angstroms (or 25, 20, 15, or even 10 angstroms) of this peptide can simply be identified in the protein antigen structure, whether monomeric or multimeric, and whether peptide pairs including the selected preferred peptide and adjacent peptides in the structure are simultaneously recognized by the individual's B lymphocytes can be systematically examined.

[0070] In a third embodiment, the peptides are labeled with different fluorophores and their recognition by at least one composition comprising antibody-bearing B lymphocytes is measured by FACS.

[0071] In this case, conformational epitopes are detected directly on individual cells by FACS in two steps: the first step involves selecting a series of fluorophore-labeled peptides with different fluorescence emission wavelengths whose sequences are derived from the protein antigen sequence, which are then tested on the individual's cells by FACS. This step allows for the identification of peptides recognized by the individual's cells and the selection of a number of them as a priority. In the second step, a zoom-in on each of these priority peptides can be performed by testing each of these labeled peptides by FACS using a series of peptides that are spatially close to the peptide but labeled with fluorophores with different fluorescence emission wavelengths. Typically, when the starting point is a protein antigen, at least three peptides labeled with different fluorophores, with a maximum size of 60 but a minimum size of 10 residues, preferably at least 15 residues, particularly at least 20 residues, and sometimes at least 30 residues, can be tested first. Of course, if a protein antigen is large, it is interesting to cover it with as many peptides as possible to identify the maximum number of peptides recognized by the individual's cells. It may be possible to test as many staining peptides as possible within the limits of the available FACS detection capabilities for different fluorescence wavelengths. This allows peptides recognized by the individual's cells to be selected according to their purpose (response level, localization in the target protein, etc.). For each selected peptide, the FACS test can be repeated in combination with a series of peptides that are spatially close to it, for example, within 25 or 30 Å. This series typically includes at least two peptides, but this can number in the dozens depending on the protein zones located around the selected peptide and the number of different possible fluorophore labels. Thus, it is possible to select peptides recognized by the individual's B lymphocytes in combination with this preferred peptide, thus forming a conformational epitope with this peptide.

[0072] If one does not wish to select preferred peptides, one may even attempt to systematically test the recognition of all pairs of different peptides that are less than 30 angstroms, or 25, 20, 15, or even 10 angstroms apart in the structure of the protein antigen by the individual's B lymphocytes, in a manner similar to the second embodiment, except that this is done for all peptides of the protein antigen or for peptides selected in specific regions of the protein antigen. In particular, this can be achieved by selecting multiple peptides labeled with at least two fluorophores, as described above.

[0073] The present invention is further illustrated by the following non-limiting examples. [Example]

[0074] Example 1: Identification of antibodies targeting conformational epitopes of the SARS-CoV 2 spike (S) protein. Example 1 below experimentally demonstrates the existence of a conformational epitope comprising at least two peptides, detected after epitope mapping to the E, M, N and S proteins of SARS-CoV-2.

[0075] We performed epitope mapping of the E, M, N, and S proteins of the SARS-CoV-2 virus using sera from SARS-CoV-2-infected patients and controls, using contiguous peptides of 15 amino acids in size that overlap by 11 amino acids and cover these four proteins. There were 16 peptides for E, 53 peptides for M, 102 peptides for N, and 316 peptides for S. Epitope mapping was performed on sera from 41 uninfected controls, 27 asymptomatic subjects, 23 symptomatic subjects, and 32 subjects with severe disease.

[0076] Epitope mapping ELISA data were obtained from JPT Technology's ELISA chips for the three immunoglobulin types IgA, IgG, and IgM. We refined the data by processing the immunoglobulins separately according to conventional procedures based on the ELISA values ​​of negative (serum-free) controls, the possible presence of batch effects, and the hyperreactivity of specific sera.

[0077] From the cleaned ELISA data, we searched for SARS-CoV-2-specific epitopes recognized by IgG. We used statistical t-tests and Bonferroni corrections (for the number of peptides tested). Using this stringent test, we identified approximately 10 public linear SARS-CoV-2 epitopes (see Table 1).

[0078] [Table 1]

[0079] Peptides corresponding to the linear epitopes most strongly recognized by epitope mapping. Next, we sought to determine the conformational epitopes by applying the procedure according to the invention as follows:

[0080] A. Bioinformatics calculations to identify conformational epitope pairs. 1. Calculation of the number of common strong responders between two peptides. For each pair of 483 peptides used for epitope mapping, we identified the number of strong responders identical between each pair of peptides for each group of patients. For the purposes of this example, strong responders are considered to be the top 25% of subjects. Depending on the purpose of peptide pair selection, other values ​​can also be selected, such as 10%, 30%, or 50% with the highest response. Other threshold criteria, such as ELISA response thresholds that can be adjusted according to the peptides involved, or the protein or immunoglobulin type involved, can also be selected to select strong responders. In this example, subjects who were simply within 25% of the strongest ELISA response to a peptide were selected as strong responders to this peptide.

[0081] 2. Calculation of the distance between two peptides. For every pair of peptides from protein S, we also calculated the distance between these peptides. The distances were obtained from the 3D structure of protein S available in the Protein Data Bank (Reference 6VXX), and here the distance measured between two peptides corresponds to the smallest distance between two amino acids in these peptides. There were 50,086 peptide pairs tested for S (for the 316 peptides overlapping with S), among which there were 48,827 pairs of non-contiguous peptides. Of these, 7,287 pairs of non-contiguous peptides had a distance of less than 20 angstroms, and 41,540 pairs of non-contiguous peptides had a distance of more than 20 angstroms.

[0082] 3. Calculation of the maximum number of strong responders common between the two peptides, Nmax group, for peptide pairs from different proteins to serve as a baseline control. For pairs of peptides from different proteins, we then counted the maximum number of strong responder sera common to each pair of peptides (the strongest 25%). This was done separately for data from each group of subjects: 41 uninfected controls, 27 asymptomatic subjects, 23 symptomatic subjects, and 32 subjects with a severe course. For the severe group, the maximum number of subjects common to the top 8 responders (25% of 32) obtained between peptides from different proteins was 6.

[0083] 4. For each group, selection of peptide pairs from protein S for which the number of common strong responders is equal to or greater than the Nmax-group. In the remainder of this example, we will continue to use the S protein, since it is the largest, to demonstrate the effectiveness of the approach adopted to identify three-dimensional epitopes. In each of the subject groups, we identified all pairs of discontinuous peptides for which the number of strong common responders was greater than the value of the largest Nmax-group obtained in point 3 above. Thus, for protein S, we obtained a table of peptide pairs for distances below the selected threshold of 20 Å, but with a number of common individuals equal to or greater than 6 (the maximum value found for interprotein EM, EN, ES, MN, MS, NS), here relating to the severe group in which the IgG response was good (see Table 2).

[0084] [Table 2A] [Table 2B]

[0085] Pairs of conformational epitopes strongly recognized by the same individual. Note that the linear epitopes in Table 1 are not found in Table 2, suggesting different recognition mechanisms.

[0086] Interestingly, the peptides identified in the short-range pairs generally do not correspond to the very strong linear epitopes in the ELISAs identified in Table 1. While responses do not rise to 60,000, as seen for the linear epitope peptide S in Table 1 in critically ill patients, responders can be found with high levels of antibody to 5,000 or even 10,000 of the identified peptides.

[0087] 5. Measurement of the enrichment of nearby peptide pairs (less than 20 Å distance) from the pairs selected in the previous step. We selected peptide pairs with a significant number of strong responders in common and assessed which of these peptide pairs had a distance between the peptides greater than 20 Angstroms and which had a distance less than 20 Angstroms (extensively described in the table in the previous paragraph). By Fisher's exact test, we were able to compare the distribution of the number of peptide pairs obtained with that of all non-contiguous peptide pairs derived from protein S. The results obtained for the different groups under the conditions described in the examples are shown below:

[0088] [Table 3]

[0089] Protein-S peptide pairs selected because they were recognized by the same strong responder, and measurements of enrichment of spatially close peptides by comparison with all protein-S peptide pairs (p-values ​​and RR).

[0090] The enrichment obtained for the group of severely ill patients who develop the most antibodies due to prolonged infection proves to be very significant: out of 85 pairs of peptides recognized by the same patient, there are 29 pairs of peptides with a distance of less than 20 Å (i.e., 34%), while out of 48,827 pairs of non-contiguous peptides in the protein, there are 7,287 pairs of peptides with a distance of less than 20 Å (i.e., 15%). This enrichment in peptide pairs with a distance of less than 20 Å is consistent with a p-value of 10.-5 The enrichment in pairs of spatially close peptides corresponds to a ratio of 2.28 (ratios of fractions 29 / 85 and 7287 / 48827) instead of 1, which would be expected by chance.

[0091] If only epitope mapping data from a single protein is available, one can still calculate the maximum common interest across all peptide pairs, and this value can be considered a threshold for the number of strong common responders, or this value minus 1 (or even a value equal to or less than -2). These best values ​​can then be looked at to see if peptide pairs separated by an acceptable distance for the epitope are enriched (e.g., less than 10, 15, 20, or 25 Angstroms).

[0092] For the value of the N-max group, a less stringent search may be desired depending on the number of individuals in the group and the selected threshold.

[0093] The same approach can be followed, but now using peptide triplets to find epitopes involving three peptides at a time instead of two. In this case, the distance between the peptides can be calculated, for example, 2 x 2, or their presence can be confirmed within the same sphere of diameter smaller than the desired size of the epitope (e.g., 10, 15, 20, or 25 Å).

[0094] B. Selection of PBMCs from Patients Producing Antibodies Targeting Conformational Epitopes When we looked for common strong responders between two peptides from different groups, these subjects were known by name from the data used to construct the matrix of peptide pairs for common strong responders.

[0095] To find the most interesting conformational epitope, several parameters can be taken into consideration. One can attempt to target patients with strong responses to two (or more) peptides identified in the conformational epitope. One can also attempt to prioritize peptides corresponding to sites known not to mutate over time (in this case, the SARS-CoV-2 protein S, which is known to mutate over time). As another example of a parameter for peptide selection, peptides recognized by patients with specific biological or clinical characteristics may be preferred. In this example, three closely related peptides were selected that showed fairly high levels of response: peptides S008, S021, and S049 (see Table 2). There are two reasons for selecting these peptides: the presence of three of them may suggest better binding to antibodies that simultaneously recognize them, and the level of response to these peptides is relatively strong compared to the other peptides in Table 2.

[0096] Thus, peptide pairs with high ELISA response levels are preferred, although of course this is not always the case, as there may also be epitopes that are less strongly recognized but have effective neutralizing effects.

[0097] Since individuals responding to the three peptides are known (see Table 2, column 4), the individuals with the strongest overall responses to these peptides are selected to harvest PBMCs, which are used in the next step for selection of B clones. In this case, this was patients 40 and 41.

[0098] C. Selection of B clones from PBMCs of subjects with antibodies that recognize conformational epitopes There are several protocols for selecting peptide-recognizing B clones. In this example, we chose a protocol based on FACS selection. The peptides were labeled with fluorescent dyes, and memory B lymphocytes that recognized all three peptides were recognized. For this purpose, a B cell-labeling antibody (anti-CD19) was used, and the labeled peptide was added at several concentrations ranging from 10 ng / ml to 10 micrograms / ml. FACS analysis of cells in the presence of memory B cell marker antibodies and peptides showed the presence of B clones labeled with all three peptides at an optimal concentration of 1 microgram / ml. Three peptide-labeled B cells were purified individually in individual microplate wells. The next step was to amplify cellular RNA and clone the variable fragments of the IgG heavy and light chains into specific expression cassettes for monoclonal antibodies. These various FACS purification and cloning steps are well known to those skilled in the art and are described, inter alia, in the publication by Corsiero et al. (2016) Ann Rheum Dis. 75(10):1866-75.

[0099] Expression assays were then used to produce small amounts of monoclonal antibodies in 12 monoclonal antibody-producing lines. Of the 12 antibodies tested, eight recognized the three peptides S008, S021, and S049 used in their selection, as well as the spike protein by ELISA, demonstrating that these antibodies are indeed conformational antibodies.

[0100] Example 2 Example 2 below describes a systematic method to search for conformational epitopes comprising at least two discontinuous peptides using peptides known to be immunogenic in individuals by ELISA, knowledge of the 3D structure of the SARS-CoV-2 spike (S) protein, and flow cytometry (FACS) analysis of cells from subjects immunized against SARS-CoV-2.

[0101] In this example, we collected cells from an individual who developed a long-term form of COVID-19, as we had sufficient samples of PBMCs collected at different times. The approach used here to search for B lymphocytes that recognize conformational epitopes differs from previous studies, as we only knew that the individual was infected and that their antibodies recognized the spike peptide S025, corresponding to residues 97 to 111. The latter peptide was biotinylated using the supplier's Thermo Scientific™ recommendations (EZ-Link™ Sulfo-NHS-LC-Biotinylation Kit) and then coupled to the fluorescent conjugate, Streptavidin-BV510™. Using the known structural data of the spike protein, we investigated which amino acids of the spike protein were spatially close to this peptide and whether peptides containing these amino acids could be recognized by FACS along with the S025 peptide from B lymphocytes from this individual.

[0102] The S025 peptide is in the NTD region of the spike, covering nearly the first 290 residues of the spike. When searching for all spike residues that are not part of the S025 peptide but are located less than 20 angstroms away from this peptide (the possible size of a conformational epitope), the entire NTD region is found (except for a few residues). We had peptides that were 15 residues in size and overlapped by 11 residues, covering the entire NTD region (peptides S001, S002, ... S070). Therefore, we selected the following 24 peptides that sufficiently cover the NTD region to investigate whether any of them also fired in patients' memory B lymphocytes in conjunction with S025, namely S001, S004, S007, S010, S013, S016, S019, S021, S023, S028, S031, S034, S037, S040, S043, S046, S049, S05, S055, S058, S061, S064, S067, and S070.

[0103] These 24 peptides were biotinylated using the recommendations of the supplier Thermo Scientific™ (EZ-Link™ Sulfo-NHS-LC-Biotinilation Kit) and then conjugated to a fluorescent streptavidin-phycoerythrin (PE) conjugate. We then tested them one by one in memory B cell labeling experiments (labeled with anti-CD19-APC and anti-CD27-BV711 antibodies) to determine which peptides co-labeled individual B lymphocytes with the S025 peptide. We therefore identified two other peptides, S021 (spike residues 81 to 95) and S049 (spike residues 193 to 207), that co-labeled B lymphocytes with S025.

[0104] The question arose as to whether residues from each of these three peptides form the same conformational epitope (recognized by the same antibody). Therefore, we biotinylated the S049 peptide and then coupled it with a third fluorescent dye, FITC, and reprobed the patient's cells by FACS to see if B lymphocytes simultaneously recognized all three peptides. We successfully identified memory B lymphocytes from the patient that simultaneously displayed all three colors. This indicates that these three discontinuous peptides contain residues that form the same conformational epitope. It is then easy to use a cell sorter to simultaneously recover B clones that recognize these three peptides and to use tools well known to those skilled in the art to derive monoclonal antibodies targeting this conformational epitope.

[0105] The approach developed in this example is of great interest as it facilitates the identification of conformational epitopes (here comprising three discontinuous peptide amino acids) even from the cells of a single individual.

[0106] Monoclonal antibodies that recognize conformational epitopes can then be derived by using flow cytometry cell sorting (FACS) to purify B cells that recognize the peptide (all or part of the peptide) involved in the conformational epitope. These B cells can be derived from the same individual or from other individuals who have been immunized (naturally or by vaccine) against the target antigen. These cells can be cultured to obtain supernatants containing antibodies that can be evaluated in vitro, and the mRNA for the variable portions of the antibodies can then be cloned, for example, into lineage production cassettes for producing large quantities of monoclonal antibodies. Alternatively, mRNA from FACS-sorted B lymphocytes can be cloned directly into a cassette system for in-line monoclonal antibody production.

[0107] Example 3 Example 3 below describes a method for direct conformational epitope probing by flow cytometry (FACS) based on the use of consecutive peptides labeled with different fluorescent colors.

[0108] This example demonstrates how conformational epitopes can be directly identified by screening a series of different fluorescently labeled peptides from the same target protein.

[0109] We used cells from the individual in Example 2, who presented with a long-term form of COVID-19, for whom we collected sufficient PBMC samples at different times.

[0110] We produced six peptides of SARS-CoV2 Spike, 20 residues in size, spanning the NTD (N-terminal domain) and RBD (receptor binding domain) domains of the spike: peptide 1, which has residues 15–34 in the NTD, designated P1; Peptide 2, which contains residues 93–112 in the NTD, designated P2 Peptide 3, which contains residues 217–236 in the NTD, designated P3 Peptide 4, which contains residues 438–457 in the RBD, designated P4 Peptide 5, containing residues 458–477 in the RBD, designated P5 peptide 6, residues 501–520 in the RBD, designated P6;

[0111] These six peptides were biotinylated using the Thermo Scientific™ supplier's recommendations (EZ-Link™ Sulfo-NHS-LC-Biotinilation kit) and coupled to fluorescent dyes of six different emission colors for FACS analysis.

[0112] In a first experiment, we simultaneously tested the binding of these six peptides to memory B lymphocytes (identified by anti-CD19-APC and anti-CD27-BV711 antibodies and fluorescent dyes with emission colors different from those of the peptides).

[0113] In this first experiment, we obtained 4254 memory B lymphocytes out of 181,000 PBMCs tested.

[0114] This experiment showed that the individual's memory B lymphocytes specifically recognized two peptides.

[0115] The P2 peptide is recognized by 23 memory B lymphocytes, the P4 peptide by 34 memory B lymphocytes, and the other peptides by fewer than 5 memory B lymphocytes.

[0116] The P2 peptide comprises the S025 peptide from Example 2. Peptide P4 corresponds to the RBM (receptor binding motif) region, which is also known to frequently induce antibody production in infected subjects.

[0117] To investigate whether the results of Example 2 could be reproduced by this direct FACS approach, we searched for peptides located within 10 angstroms of the P2 peptide in the spike structure. We relied on 15-mers (overlapping 11 residues) covering the entire spike protein in Example 2. Bioinformatic analysis of the 3D structure of the spike protein showed that there were 42 of these peptides, which were separated from the P2 peptide and located less than 10 angstroms away from the P2 peptide in the spike 3D structure. These were peptides S5, S6, S15, S16, S19, S20, S21, S28, S29, S30, S31, S32, S33, S34, S35, S39, S40, S41, S42, S43, S44, S45, S46, S47, S48, S49, S50, S51, S52, S53, S54, S56, S57, S58, S59, S60, S61, S63, S64, S65, S66, and S67.

[0118] Since many of the 42 peptides overlapped, we selected 16 of them to represent the entire region of the protein covered by these 42 peptides: S5, S15, S19, S28, S31, S34, S39, S42, S45, S48, S51, S54, S57, S60, S63, S66.

[0119] As previously performed for the six peptides in the first series, these 16 peptides were biotinylated using the recommendations of the supplier Thermo Scientific™ (EZ-Link™ Sulfo-NHS-LC-Biotinylation Kit) and conjugated to fluorescent conjugates of different emission colors for FACS analysis. These colors are also different from the colors of the labels of the anti-CD19 and anti-CD27 antibodies used to identify memory B lymphocytes and the previously generated P2 peptide. We labeled the first eight of the 16 peptides (S5–S42) with eight fluorescent dyes and the last eight peptides (S45–S66) with the same fluorescent dyes, and performed combined labeling experiments between the P2 peptide and each of these two peptide groups.

[0120] The FACS results for the experiments with the first eight peptides S5-S42 were as follows: Number of memory B lymphocytes = 3750 out of 152000 cells analyzed. Number of B cells labeled with P2 peptide alone: ​​14 Number of B cells labeled with P2 and S19 peptides: 4

[0121] There were only 10 S19 peptide-labeled B cells.

[0122] For the seven other peptides tested, no cells were labeled.

[0123] FACS results for experiments with the other eight peptides S45-S66 were as follows: Number of memory B lymphocytes = 3794 out of 165,000 cells analyzed. Number of B cells labeled with P2 peptide alone: ​​19 Number of B cells labeled with P2 and S48 peptides: 2

[0124] Only five S48 peptide-labeled B cells were present.

[0125] For the seven other peptides tested, no cells were labeled, except for peptide S66, which labeled two B cells.

[0126] This experiment confirms that peptides S19 and S48 can each form a conformational epitope with peptide P2. Interestingly, S19 is very close to the S21 peptide identified in Example 2, while S48 is very close to the S49 peptide also identified in Example 2. We attempted to confirm by FACS whether the S19 / P2 epitope and the S48 / P2 epitope are recognized by the same antibody. In an experiment similar to the previous one but including only the P2, S19, and S48 labeled peptides (with different fluorescent dyes), we were able to simultaneously identify two cells labeled by all three peptides, indicating that the same conformational epitope is involved.

[0127] This example demonstrates that an approach based on the combined analysis of a series of peptides labeled with different fluorescent colors is highly effective for identifying conformational epitopes.

[0128] The identified peptides can then be used, as in Example 2, to purify by FACS B lymphocytes bearing antibodies that recognize the desired conformational epitope, and to produce monoclonal antibodies using methods well known to those skilled in the art.

Claims

1. 1. A method for identifying a conformational epitope of a protein antigen formed from at least two different peptides comprising sequences from the protein antigen, comprising: - selecting at least one first peptide comprising a sequence from said protein antigen that is recognized by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least one individual immunized against said protein antigen, and - 3.10 from the first peptide in the three-dimensional structure of the protein antigen －9 selecting at least one second peptide located at a distance of not more than 1 m and comprising a sequence from said protein antigen that is recognized by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least one individual immunized against said protein antigen of the previous step; Including, the at least one first peptide and the at least one second peptide form a conformational epitope of the protein antigen; method.

2. 2. The method of claim 1, wherein the at least one first peptide and the at least one second peptide are selected from a plurality of different peptides comprising sequences from the protein antigen as a result of recognition by at least one composition comprising antibodies or antibody-bearing B lymphocytes from at least two different individuals immunized against the protein antigen.

3. 3. The method of claim 2, wherein the at least two different individuals are strong responders to the at least one first peptide and the at least one second peptide among a plurality of different individuals immunized against the protein antigen.

4. 2. The method of claim 1, wherein the at least one first peptide and the at least one second peptide are selected from a plurality of different peptides comprising a sequence derived from the protein antigen as a result of recognition by at least one composition comprising an antibody or antibody-bearing B lymphocyte from the same individual.

5. 5. The method of claim 4, wherein the at least one first peptide and the at least one second peptide are strongly recognized among the plurality of different peptides comprising sequences derived from the protein antigen.

6. 6. The method of claim 1, wherein the peptides each contain between 6 and 30 amino acid residues.

7. 7. The method of claim 1, wherein the peptides comprise non-overlapping sequences from the protein antigen.

8. 8. The method of claim 1, wherein the protein antigen is derived from a human or animal infectious agent or protein.

9. 9. The method of claim 1, wherein the recognition of the peptide by at least one composition comprising antibody-bearing B lymphocytes is determined by phage display or ELISA.

10. 9. The method of claim 1, wherein the peptides are labeled with different fluorophores and their recognition by at least one composition comprising antibody-bearing B lymphocytes is measured by FACS.

11. 11. A method for selecting lymphocytes that recognize a protein antigen from a population of cells, comprising identifying at least one lymphocyte that binds to at least two different peptides comprising sequences from the protein antigen that form a conformational epitope of the protein antigen, wherein the conformational epitope is identified by performing the method of any one of claims 1 to 10.

12. 12. A method for preparing at least one antibody or antibody fragment against a protein antigen, wherein said antibody or antibody fragment is prepared from at least one B lymphocyte obtained by carrying out the lymphocyte selection method defined in claim 11.

13. A plurality of first peptides and second peptides obtained by carrying out the method defined in any one of claims 1 to 10 on a protein antigen, wherein the first peptides and second peptides are each linked to a fluorophore having a different fluorescence emission wavelength.

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