DIGITAL COUNTING OF INDIVIDUAL MOLECULES BY STOCHASTIC ATTACHMENT OF DIVERSE LABELS

• US 20160326584A1
• Filed: 07/29/2016
• Published: 11/10/2016
• Est. Priority Date: 12/15/2009
• Status: Active Grant

• Current Assignee: Becton, Dickinson & Co
• Original Assignee: Cellular Research, Inc. (Becton, Dickinson & Co)
• Inventors: Fodor, Stephen P.A., Fu, Glenn K.
• Granted Patent: US 10,047,394 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: C12N 15/1065 Preparation or screening of tagged libraries, e.g. tagged microorganisms by STM-mutagenesis, tagged polynucleotides, gene tags
• CPC Class Codes: C12Q 1/6809 Methods for determination or identification of nucleic acids involving differential detection
• CPC Class Codes: C12Q 1/6837 using probe arrays or probe chips C12Q1/6874 takes precedence
• CPC Class Codes: C12Q 1/6851 Quantitative amplification
• CPC Class Codes: C12Q 1/686 Polymerase chain reaction [PCR]
• CPC Class Codes: C12Q 1/6869 Methods for sequencing
• CPC Class Codes: C12Q 1/6874 involving nucleic acid arrays, e.g. sequencing by hybridisation
• CPC Class Codes: C12Q 1/6876 Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
• CPC Class Codes: C12Q 2525/191 incorporating an adaptor
• CPC Class Codes: C12Q 2537/157 A reaction step characterised by the number of molecules incorporated or released
• CPC Class Codes: C12Q 2565/102 Multiple non-interacting labels
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16B 25/20 Polymerase chain reaction [PCR]; Primer or probe design; Probe optimisation
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids

Abstract

Compositions, methods and kits are disclosed for high-sensitivity single molecule digital counting by the stochastic labeling of a collection of identical molecules by attachment of a diverse set of labels. Each copy of a molecule randomly chooses from a non-depleting reservoir of diverse labels. Detection may be by a variety of methods including hybridization based or sequencing. Molecules that would otherwise be identical in information content can be labeled to create a separately detectable product that is unique or approximately unique in a collection. This stochastic transformation relaxes the problem of counting molecules from one of locating and identifying identical molecules to a series of binary digital questions detecting whether preprogrammed labels are present. The methods may be used, for example, to estimate the number of separate molecules of a given type or types within a sample.

Claims

1-30. -30. (canceled)

31. A method for counting n wherein n is a number of occurrences of a first target molecule that are present in a sample comprising multiple diverse target molecules:

(a) attaching by a random manner to a plurality of occurrences of the first target molecule a label from a set of diverse labels, wherein the set comprises m different labels, thereby generating for each occurrence of the first target molecule, a new molecule that comprises a copy of the first target molecule and a label, wherein more than 90% of the new molecules have a label that is different from the labels on the other new molecules;

(b) detecting each new molecule by detecting each label present on the new molecule; and

(c) counting the number of new molecules, thereby counting the number of occurrences of the first target molecule in the sample.

32. The method of claim 31, wherein m and n are related by E(k), wherein

33. The method of claim 31, wherein m and n are related by Var(k), wherein

34. The method of claim 31, wherein m and n are related by E(t), wherein

35. The method of claim 31, wherein m and n are related by Var(k), wherein

36. The method of claim 31, wherein the ratio of n to m is at most 0.693.

37. The method of claim 31, wherein detecting the labels present on the new molecules comprises sequencing the new molecules.

38. The method of claim 37, wherein sequencing the new molecules comprises mapping the sequencing reads to a reference sequence.

39. The method of claim 37, wherein sequencing the new molecules comprises aligning the sequencing reads.

40. The method of claim 37, wherein sequencing the new molecules comprises detecting a mismatch in the label or the copy of the first target molecule in the sequencing reads.

41. The method of claim 37, wherein sequencing the new molecules comprises sequencing a portion of the label or a portion of the first target molecule.

42. The method of claim 37, wherein counting the number of new molecules comprises counting the number of labels present on the new molecules.

43. The method of claim 42, wherein counting the number of labels present on the new molecules comprises scoring a label in the sequencing reads.

44. The method of claim 31, comprising adding an adaptor to the plurality of occurrences of the first target molecule.

45. The method of claim 31, wherein the attaching of step (a) comprises reverse transcription of an occurrence of the first target molecule.

46. The method of claim 31, wherein the attaching of step (a) comprises reverse transcription of the plurality of occurrences of the first target molecule.

47. The method of claim 31, wherein the plurality of occurrences of the first target molecule is mRNA.

48. The method of claim 31, wherein the set of diverse labels comprise an oligo-dT sequence.

49. The method of claim 31, wherein the plurality of occurrences of the first target molecule is DNA.

50. The method of claim 31, wherein the sample is a single cell.