IP Library › Granted Patent US 12,486,501
Granted Patent B2
US 12,486,501 · App. 17/386,702 · Granted Dec 2, 2025

Multiplexed testing of lymphocytes for antigen specificity

Inventors: David Gifford (Newton, MA); Brandon Carter (Cambridge, MA)
Assignee: Think Therapeutics, Inc.
C12N15/1037C12N15/1089C40B30/04
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,486,501
App. No.
17/386,702
Granted
Dec 2, 2025
Kind
B2
Abstract

Described herein is a method for determining a lymphocyte cell receptor chain sequence specific to a unique antigen, comprising: sorting a plurality of antigens into a plurality of reaction mixtures, wherein the sorting comprises adding a unique antigen of the plurality of antigens to a unique subset of the plurality of reaction mixtures such that two different unique antigens are not added to the unique subset; contacting each reaction with a biological sample comprising a plurality of lymphocytes; separating a target lymphocyte from a subset of the plurality of lymphocytes, wherein the target lymphocyte recognizes the unique antigen; after separating the target lymphocyte, sequencing nucleic acids of the target lymphocyte to obtain the lymphocyte receptor chain sequence, wherein the sequencing is performed by single-cell sequencing; and detecting the unique antigen, wherein the detecting comprises: computing a frequency of lymphocyte cells that express the lymphocyte receptor chain sequence.

Claims (22)

1 . A method for determining a T cell receptor chain sequence, or a portion thereof, specific for two or more antigens, the method comprising:

sorting a plurality of first antigens into a plurality of reaction mixtures, wherein the sorting comprises adding two or more unique antigens of the plurality of first antigens to two or more unique subsets of the plurality of reaction mixtures, and wherein the two or more unique antigens are not added to any two identical subsets of the plurality of reaction mixtures;

contacting each reaction mixture with a biological sample comprising a plurality of T cells;

providing a condition for a first activated T cell in at least one reaction mixture of the plurality of reaction mixtures to expand in number such that a plurality of T cell clones is formed;

adding a query antigen to at least one unique subset of the two or more unique subsets of the plurality of reaction mixtures;

separating a second activated T cell and a non-activated T cell from a subset of the plurality of reaction mixtures, wherein the second activated T cell recognizes the query antigen;

sequencing nucleic acids of the second activated T cell to obtain the T cell receptor chain sequence; and

detecting the two or more unique antigens of the plurality of first antigens, wherein the two or more unique antigens are specific for the T cell receptor chain sequence.

2 . The method of claim 1 , wherein separating the second activated T cell and the non-activated T cell is performed based on a marker, wherein the marker is selected from the group consisting of CD3, CD4, CD8, CD137, OX40, CD25, PD-L1, CD69, CD154, and a combination thereof.

3 . The method of claim 1 , wherein the T cell receptor chain sequence comprises a receptor chain sequence pair, wherein the receptor chain sequence pair consists of an alpha chain sequence and a beta chain sequence.

4 . The method of claim 1 , wherein the second activated T cell recognizes the query antigen by binding an MHC complex comprising the query antigen.

5 . The method of claim 1 , wherein the sorting further comprises applying, using a processor, an error-correcting code configured to determine the two or more unique subsets of the plurality of reaction mixtures that the two or more unique antigens are added to.

6 . The method of claim 5 , wherein the error-correcting code is a superimposed code.

7 . The method of claim 1 , wherein the detecting comprises applying, using a processor, a decoding algorithm, wherein the decoding algorithm is configured to detect the two or more unique antigens specific for the T cell receptor chain sequence when the T cell receptor chain sequence is not substantially present in at least one reaction mixture of the two or more unique subsets of the plurality of reaction mixtures.

8 . The method of claim 7 , wherein the decoding algorithm is a nearest neighbor algorithm.

9 . The method of claim 1 , wherein the query antigen is different from any antigen of the plurality of first antigens.

10 . The method of claim 1 , wherein separating the second activated T cell and the non-activated T cell from the subset of the plurality of reaction mixtures is performed using multimer sorting.

11 . The method of claim 1 , wherein separating the second activated T cell and the non-activated T cell from the subset of the plurality of reaction mixtures is performed using fluorescence-based sorting.

12 . The method of claim 1 , wherein separating the second activated T cell and the non-activated T cell from the subset of the plurality of reaction mixtures is performed using bead-based sorting.

13 . The method of claim 1 , wherein a number of reaction mixtures corresponding to the two or more unique subsets of the plurality of reaction mixtures is a function of a number of expected unique antigens that are specific to the T cell receptor chain sequence.

14 . The method of claim 1 , wherein the plurality of reaction mixtures comprises at least one control reaction mixture, wherein the control reaction mixture does not contain any antigens of the plurality of first antigens.

15 . The method of claim 1 , wherein the detecting further comprises computing a frequency of T cells that express the T cell receptor chain sequence.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 18, 2021
From: GIFFORD, DAVID; CARTER, BRANDON
To: THINK THERAPEUTICS, INC.
Reel/Frame 057210/0501 →
Continuity (2)
Continuation 17142745 · Jan 6, 2021
Related Publication 20220213466A1 · Jul 7, 2022
References Cited (58)
US 5371750A · Inoue et al. · 1994 [cited by examiner]
US 8691510B2 · Faham et al. · 2014 [cited by applicant]
US 9708654B2 · Hunicke-Smith et al. · 2017 [cited by applicant]
US 10066265B2 · Klinger et al. · 2018 [cited by applicant]
US 10077478B2 · Faham et al. · 2018 [cited by applicant]
US 10168328B2 · Berka · 2019 [cited by applicant]
US 10539564B2 · Berka et al. · 2020 [cited by applicant]
US 11111489B1 · Gifford et al. · 2021 [cited by applicant]
US 11261490B2 · Klinger et al. · 2022 [cited by applicant]
US 20120196762A1 · Paradis · 2012 [cited by applicant]
US 20150025812A1 · Paradis · 2015 [cited by examiner]
US 20160024493A1 · Robins · 2016 [cited by applicant]
US 20170114406A1 · Hansen et al. · 2017 [cited by applicant]
US 20180087109A1 · Klinger et al. · 2018 [cited by examiner]
US 20180282808A1 · Milla et al. · 2018 [cited by applicant]
US 20190025299A1 · Vigneault et al. · 2019 [cited by examiner]
US 20190055607A1 · Jayaprakash · 2019 [cited by applicant]
US 20200123597A1 · Danie · 2020 [cited by applicant]
US 20200354784A1 · Goldfless et al. · 2020 [cited by applicant]
US 20210269792A1 · Falconer et al. · 2021 [cited by applicant]
US 20210293812A1 · Vigneault et al. · 2021 [cited by applicant]
Ashby, “W. Ross Ashby's Journal: Zato-coding”, Sep. 22, 1960, pp. 6208-6222. 8 pages. (http://www.rossashby.info/journal/page/6208.html.). [cited by applicant]
Binladen et al., “The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing,” PLoS One, Feb. 14, 2007, ;2(2):e197. 9 pages. [cited by applicant]
Bowyer et al., “Activation-induced markers detect vaccine-specific CD4+ T cell responses not measured by assays conventionally used in clinical trials,” Vaccines, 6(3), 50, Jul. 31, 2018. 19 pages. [cited by applicant]
De Simone et al., “Single Cell T Cell Receptor Sequencing: Techniques and Future Challenges,” Frontiers in Immunology, Jul. 18, 2018, 9:1638. 7 pages. [cited by applicant]
Emerson et al., “Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire,” Nature Genetics, May 2017, 49(5), pp. 659-665 and Online Methods. 10 pages. [cited by applicant]
Kim et al., “Multi-error correcting codes for a binary asymmetric channel,” IRE Transactions on Circuit Theory, May 1959, 6(5), 71-78. [cited by applicant]
Kivioja et al., “Counting absolute Nos. of molecules using unique molecular identifiers,” Nature Methods, Nov. 20, 2011, 9(1):72-74 and Online Methods. 5 pages. [cited by applicant]
Klinger et al., “Combining next-generation sequencing and immune assays: A novel method for identification of antigen-specific T cells,” PLoS One, Sep. 19, 2013, 8(9):e74231. 9 pages. [cited by applicant]
Klinger et al., “Multiplex identification of antigen-specific T cell receptors using a combination of immune assays and immune receptor sequencing,” PLoS One, Oct. 28, 2015, 10(10), e0141561. 21 pages. [cited by applicant]
Lissina et al., “Priming of Qualitatively Superior Human Effector CD8+ T Cells Using TLR8 Ligand Combined with FLT3 Ligand,” The Journal of Immunology (2016), 196(1), pp. 256-263, published online Nov. 25, 2015. 9 pages. [cited by applicant]
Lugosch, “Learning Algorithms for Error Correction,” Masters Thesis, McGill University, Apr. 2018. 82 pages. (https://lorenlugosch.github.io/Masters_Thesis.pdf). [cited by applicant]
Mooers, “Zatocoding applied to mechanical organization of knowledge,” American documentation, Jan. 1951, 2(1), 20-32. doi: 10.1002/asi.509002010. [cited by applicant]
Nolan et al., “A large-scale database of T-cell receptor beta (TCRβ) sequences and binding associations from natural and synthetic exposure to SARS-CoV-2,” Research Square [Preprint]. Aug. 4, 2020. 28 pages. (https://do… [cited by applicant]
Reiss, et al., “Comparative analysis of activation induced marker (AIM) assays for sensitive identification of antigen-specific CD4 T cells,” PLoS One, Oct. 24, 2017, 12(10), e0186998. 22 pages. [cited by applicant]
Rosenberg et al., “Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding,” Science, Apr. 13, 2018, 360(6385):176-182. 8 pages. [cited by applicant]
Scheid et al., “A method for identification of HIV gp140 binding memory B cells in human blood,” Journal of Immunological Methods (2009) 343(2), pp. 65-67. Available online Dec. 25, 2008. [cited by applicant]
Singh et al., “High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes,” Nature Communications Jul. 16, 2019, 10(1):3120. 13 pages. [cited by applicant]
Snyder et al., “Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels,” medRxiv [Preprint]. Sep. 17, 2020. 33 pages. [cited by applicant]
Stahlberg et al., “Simple multiplexed PCR-based barcoding of DNA for ultrasensitive mutation detection by next-generation sequencing,” Nature Protocols, Apr. 2017, 12(4), pp. 664-682. [cited by applicant]
Stubbington et al., “T cell fate and clonality inference from single-cell transcriptomes,” Nature Methods, Apr. 2016, 13(4), pp. 329-332 and Online Methods. 7 pages. [cited by applicant]
Tapia-Calle et al., “A PBMC-Based System to Assess Human T Cell Responses to Influenza Vaccine Candidates In Vitro,” Vaccines, Nov. 13, 2019, 7(4):181. 26 pages. [cited by applicant]
Zimmermann et al., “Antigen Extraction and B Cell Activation Enable Identification of Rare Membrane Antigen Specific Human B Cells,” Frontiers in Immunology, Apr. 16, 2019, 10:829. 18 pages. [cited by applicant]
Zong et al., “Genome-wide detection of single-nucleotide and copy-number variations of a single human cell,” Science, Dec. 21, 2012, 338(6114), pp. 1622-1626. [cited by applicant]
International Search Report and Written Opinion mailed Jun. 8, 2022 in the International Application PCT/US2022/011275. 23 pages. [cited by applicant]
Bell et al., “Dynamics-Based Peptide—MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for Castelo,” Journal of Chemical Theory and Computation, Nov. 18, 2021, vol. 17, pp. 7962-7971. [cited by applicant]
Xiao et al., “In silico design of MHC class I high binding affinity peptides through motifs activation map,” BMC Bioinformatics, published Dec. 31, 2018, vol. 19(Suppl 19):516. 12 pages. [cited by applicant]
Du et al., “Deterministic Designs and Superimposed Codes,” Chapter 7, Combinatorial Group Testing and Its Applications, Series on Applied Mathematics: vol. 12, 2nd Edition, https://doi.org/10.1142/4252, Dec. 1999, pp. 1… [cited by applicant]
Du et al., “DNA Applications,” Chapter 9, Combinatorial Group Testing and Its Applications, Series on Applied Mathematics: vol. 12, 2nd Edition, https://doi.org/10.1142/4252, Dec. 1999, pp. 177-193. [cited by applicant]
D'yachkov et al., “Cover-free families and superimposed codes: Constructions, bounds, and applications to cryptography and group testing,” Proceedings of IEEE International Symposium on Information Theory, Jun. 24-29, 2… [cited by applicant]
D'yachkov et al., “Superimposed Codes and Threshold Group Testing,” In: Aydinian, H., Cicalese, F., Deppe, C. (eds) Information Theory, Combinatorics, and Search Theory. Lecture Notes in Computer Science, vol. 7777. Spr… [cited by applicant]
D'yachkov et al., “Superimposed Distance Codes,” Problems of Control and Information Theory (1989), vol. 18(4), pp. 237-250. [cited by applicant]
Ericson et al., “Superimposed Codes in Rn,” IEEE Transactions on Information Theory (1988), vol. 34(4), pp. 877-880. Aug. 1988. DOI: 10.1109/18.9789. [cited by applicant]
Furedi et al., “An improved upper bound of the rate of Eucledian superimposed codes,” IEEE Transactions on Information Theory, Nov. 6, 1997, vol. 45(2), pp. 1-9. [cited by applicant]
Huang et al., “A Note on Decoding of Superimposed Codes,” Journal of Combinatorial Optimization (2004), Dec. 2003, vol. 7, pp. 381-384. [cited by applicant]
Kautz et al., “Nonrandom binary superimposed codes,” IEEE Transactions on Information Theory, Oct. 1964, vol. 10(4), pp. 363-377. DOI: 10.1109/TIT.1964.1053689. [cited by applicant]
Macula, “A simple construction of d-disjunct matrices with certain constant weights,” Discrete Mathematics, Dec. 25, 1996, vol. 162, Issues 1-3, pp. 311-312. https://doi.org/10.1016/0012-365X(95)00296-9. [cited by applicant]
Ruszinkó, “On the upper bound of the size of the r-cover-free families,” Journal of Combinatorial Theory Series A, May 1994, vol. 66, issue 2, pp. 1-9. [cited by applicant]