Adaptive immunity profiling and methods for generation of monoclonal antibodies

1. A method, comprising:

generating a first cDNA sequence library comprising a first set of target antibody cDNA sequences, said first set of target antibody cDNA sequences obtained from a first sample comprising lymphocytes of a host subject that has not been immunized with an antigen and each of said first set of target antibody cDNA sequences comprising an immunoglobulin (Ig) heavy chain variable domain sequence,

wherein generating said first cDNA sequence library comprises amplifying said first set of target cDNA sequences and sequencing said amplified first set of target cDNA sequences;

generating a second cDNA sequence library comprising a second set of target antibody cDNA sequences, said second set of target antibody cDNA sequences obtained from a second sample comprising lymphocytes of said host subject after being immunized with said antigen and each of said second set of target antibody cDNA sequences comprising an immunoglobulin (Ig) heavy chain variable domain sequence,

wherein generating said second cDNA sequence library comprises amplifying said second set of target cDNA sequences and sequencing said amplified second set of target cDNA sequences;

analyzing the frequencies of occurrence of each of said first and second set of target antibody cDNA sequences;

identifying candidate antibody cDNA sequences that have a statistically significantly higher frequency of occurrence in said second set of target antibody cDNA sequences compared to a frequency of occurrence of said first set of target antibody cDNA sequences;

selecting said candidate antibody cDNA sequences for generating monoclonal antibodies; and

expressing said candidate antibody cDNA sequences to produce a plurality of candidate monoclonal antibodies.

2. The method of claim 1 , wherein the lymphocytes comprise isolated B cells.

3. The method of claim 1 , wherein expressing said candidate antibody cDNA sequences to produce a plurality of candidate monoclonal antibodies comprises subcloning said candidate antibody sequences with a light chain variable domain sequence and an Ig framework.

4. The method of claim 3 , wherein the Ig framework is a human Ig framework.

5. The method of claim 3 , further comprising assaying the candidate monoclonal antibodies for affinity to the antigen.

6. The method of claim 3 , further comprising subjecting the plurality of candidate monoclonal antibodies to positive selection to identify one or more high affinity monoclonal antibodies.

7. The method of claim 6 , wherein subjecting the plurality of candidate monoclonal antibodies to positive selection comprises contacting the plurality of candidate monoclonal antibodies to the antigen bound to a substrate and isolating bound antibodies from unbound antibodies.

8. The method of claim 6 , wherein the candidate monoclonal antibodies bind to an antigen with an affinity of at least 1×10 10 liter/mole, measured as an association constant (K aff ).

9. The method of claim 6 , further comprising sequencing the high affinity monoclonal antibodies.

10. The method of claim 1 , wherein the frequencies of occurrence of said first and second set of target antibody cDNA sequences are analyzed using a bioinformatics software algorithm.

11. The method of claim 1 , wherein the first and second set of target antibody cDNA sequences of said first and second cDNA sequence libraries are sequenced by massively parallel signature sequencing (MPSS).

12. The method of claim 1 , wherein the host subject is an experimental animal.

13. The method of claim 1 , wherein the host subject is a transgenic animal expressing human antibodies.

14. The method of claim 1 , wherein the host subject is a human.

15. The method of claim 1 , wherein generating said first or second cDNA sequence library comprises:

i) isolating lymphocytes from the host subject;

ii) isolating mRNA from the lymphocytes; and

iii) reverse transcribing the mRNA to cDNA.