DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim status
2. Claims 1-20 are currently pending and under exam herein.
Claims 1-20 are rejected.
Priority
3. Claimed benefit of domestic priority U.S. Provisional Patent Application Serial No. 63/430,727, filed on 07 December 2022, and U.S. Provisional Patent Application Serial No. 63/469,901, filed on 31 May 2023 is acknowledged. In this action, all claims are examined as though they had an effective filing date of 07 December 2022. In future actions, the effective filing date of one or more claims may change, due to amendments to the claims, or further analysis of the disclosure(s) of the priority application(s).
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 23 April 2024 is being considered by the examiner.
Drawings
5. The drawings submitted on 07 December 2023 are objected to for the reasons indicated below:
Figures 1-11, 13-20, 22-30, 32-33 and 36-41 are in color. Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification:
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
The nucleic acid and amino acid sequences that appear in Figure 1b (and that are listed in the included XML file) are not identified by sequence identifiers in accordance with 37 CFR 1.821(d).
Appropriate correction is required.
Nucleotide and/or Amino Acid Sequence Disclosures
REQUIREMENTS FOR PATENT APPLICATIONS CONTAINING NUCLEOTIDE AND/OR AMINO ACID SEQUENCE DISCLOSURES
Items 1) and 2) provide general guidance related to requirements for sequence disclosures.
37 CFR 1.821(c) requires that patent applications which contain disclosures of nucleotide and/or amino acid sequences that fall within the definitions of 37 CFR 1.821(a) must contain a "Sequence Listing," as a separate part of the disclosure, which presents the nucleotide and/or amino acid sequences and associated information using the symbols and format in accordance with the requirements of 37 CFR 1.821 - 1.825. This "Sequence Listing" part of the disclosure may be submitted:
In accordance with 37 CFR 1.821(c)(1) via the USPTO patent electronic filing system (see Section I.1 of the Legal Framework for Patent Electronic System (https://www.uspto.gov/PatentLegalFramework), hereinafter "Legal Framework") as an ASCII text file, together with an incorporation-by-reference of the material in the ASCII text file in a separate paragraph of the specification as required by 37 CFR 1.823(b)(1) identifying:
the name of the ASCII text file;
ii) the date of creation; and
iii) the size of the ASCII text file in bytes;
In accordance with 37 CFR 1.821(c)(1) on read-only optical disc(s) as permitted by 37 CFR 1.52(e)(1)(ii), labeled according to 37 CFR 1.52(e)(5), with an incorporation-by-reference of the material in the ASCII text file according to 37 CFR 1.52(e)(8) and 37 CFR 1.823(b)(1) in a separate paragraph of the specification identifying:
the name of the ASCII text file;
the date of creation; and
the size of the ASCII text file in bytes;
In accordance with 37 CFR 1.821(c)(2) via the USPTO patent electronic filing system as a PDF file (not recommended); or
In accordance with 37 CFR 1.821(c)(3) on physical sheets of paper (not recommended).
When a “Sequence Listing” has been submitted as a PDF file as in 1(c) above (37 CFR 1.821(c)(2)) or on physical sheets of paper as in 1(d) above (37 CFR 1.821(c)(3)), 37 CFR 1.821(e)(1) requires a computer readable form (CRF) of the “Sequence Listing” in accordance with the requirements of 37 CFR 1.824.
If the "Sequence Listing" required by 37 CFR 1.821(c) is filed via the USPTO patent electronic filing system as a PDF, then 37 CFR 1.821(e)(1)(ii) or 1.821(e)(2)(ii) requires submission of a statement that the "Sequence Listing" content of the PDF copy and the CRF copy (the ASCII text file copy) are identical.
If the "Sequence Listing" required by 37 CFR 1.821(c) is filed on paper or read-only optical disc, then 37 CFR 1.821(e)(1)(ii) or 1.821(e)(2)(ii) requires submission of a statement that the "Sequence Listing" content of the paper or read-only optical disc copy and the CRF are identical.
6. Specific deficiencies and the required response to this Office Action are as follows:
Specific deficiency – Nucleotide and/or amino acid sequences appearing in the drawings are not identified by sequence identifiers in accordance with 37 CFR 1.821(d). Sequence identifiers for nucleotide and/or amino acid sequences must appear either in the drawings or in the Brief Description of the Drawings.
Required response – Applicant must provide:
Replacement and annotated drawings in accordance with 37 CFR 1.121(d) inserting the required sequence identifiers;
AND/OR
A substitute specification in compliance with 37 CFR 1.52, 1.121(b)(3) and 1.125 inserting the required sequence identifiers into the Brief Description of the Drawings, consisting of:
A copy of the previously-submitted specification, with deletions shown with strikethrough or brackets and insertions shown with underlining (marked-up version);
A copy of the amended specification without markings (clean version); and
A statement that the substitute specification contains no new matter.
Claim Objections
7. Claim 6 is objected to because of the following informalities:
The claim recites “The method according to claim 4, wherein obtaining transcripts from the refined barcoded information”, which is grammatically incorrect. A possible correction is to change the claim to “The method according to claim 4 further comprising obtaining transcripts from the refined barcoded information”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
8. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A, Prong 1
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claims 1 and 11 recite: scanning the barcoded full-length cDNAs sequencing information to acquire barcoded information
Claims 1 and 11 recite: calculating multi-omics information of the single cells based on the at least one BAM file.
Claims 1 and 11 recite: curating errors in the barcode information to produce curated barcoded information
Claims 4 and 14 recite: the method according to claim 3 further comprising refining the barcoded information acquired in step (2) before step (3) to produce refined barcoded information independently through an algorithm iCARLO
Claims 5 and 15 recite: curating at least one error in the Unique Molecular Identifiers (UMIs) in step (3) for transcriptome analysis
Claims 6 and 16 recite: curating at least one error in the transcripts in step (3) for the transcriptome analysis.
Claims 7 and 17 recite: the method according to claim 4, wherein the single cells multi-omics information includes at least one of gene expression matrix, isoforms profile and mutations profile
Claims 8 and 18 recite: the method according to claim 7, wherein the single cells gene expression matrix is generated via: calculating a UMI counts of genes in the single cells using the at least one BAM files; wherein each of the at least one BAM files is individually mapped
Claims 8 and 18 recite: selecting consensus reads that mapped to mature mRNA references to detect transcriptional isoforms of the single cells
Claims 8 and 18 recite: calculating single cell mutation profiles from the consensus reads of the single cells
The limitations regarding ‘scanning the barcoded full-length cDNAs sequencing information to acquire barcoded information’, ‘curating errors in the barcodes’, ‘curating at least one error’ and ‘selecting consensus reads that mapped to mature mRNA references to detect transcriptional isoforms of the single cells’ are generically recite data analysis steps that can be practically performed in the human mind because the human mind is capable of identifying relevant information, comparing values, and determining information from other values. Therefore, these limitations fall under the "Mental processes" groupings of abstract ideas.
The limitations regarding ‘calculating multi-omics information of the single cells‘, ‘refining the barcoded information through an algorithm iCARLO’, ‘calculating a UMI counts of genes in the single cells using the at least one BAM files’ and ‘calculating single cell mutation profiles from the consensus reads of the single cells’ are verbal equivalents that describe a mathematical calculation that is performed as the limitation and are so simple that they could be performed in the human mind or with pen and paper. Therefore, these limitations fall under the "Mathematical concepts" and "Mental processes" groupings of abstract ideas.
The limitations of claims 7 and 17 that further limit the type of multi-omic information produced from the analysis merely further limits the judicial exceptions but does not change its positions as an abstract idea.
As such, claims 1-20 recite an abstract idea (Step 2A, Prong 1: YES).
Step 2A, Prong 2
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or insignificant extra-solution activity. Specifically, the claims recite the following additional elements:
Claim 11 recites: a non-transitory computer readable medium storing a program to execute a process
Claim 11 recites: a computer
Claims 1 and 11 recite: a method/process of performing single cell nanopore sequencing of genotype-phenotype simultaneously (scNanoGPS), the method/process comprising obtaining barcoded full-length cDNAs sequencing information of single cells
Claims 1 and 11 recite: producing at least one BAM file based on the curated barcoded information
Claims 2 and 12 recite: the method according to claim 1, wherein the barcoded full-length cDNAs sequencing information is obtained via long-read single cell nanopore sequencing technology
Claims 3 and 13 recite: producing a FASTQ file based on the barcoded information acquired in step (2)
Claims 5 and 15 recite: obtaining Unique Molecular Identifiers (UMIs) from the refined barcoded information
Claims 6 and 16 recite: obtaining transcripts from the refined barcoded information
Claims 9 and 19 recite: the method according to claim 1, wherein the method obviates using short read sequencing information of the single cells or barcode whitelist as guidance for processing the barcoded full-length cDNAs sequencing information
Claims 10 and 20 recite: the method according to claim 2, wherein the single cells include approximately 3000-6000 cells per run of the long-read single cell nanopore sequencing
The limitations for ‘obtaining barcoded full-length cDNAs sequencing information’, ‘obtaining transcripts’ and ‘obtaining Unique Molecular Identifiers (UMIs)’ merely serve to gather data that is used an input for the judicial exception. Therefore, these limitations are mere data gathering activities. As set forth in MPEP 2106.05(g), mere data gathering activity has been identified by the courts as insignificant extra-solution activity that does not provide a practical application. The limitations directed to ‘wherein the barcoded full-length cDNAs sequencing information is obtained via long-read single cell nanopore sequencing technology’ and ‘wherein the single cells include approximately 3000-6000 cells per run of the long-read single cell nanopore sequencing’ merely further limits the type of data gathered, but do not change its designation as data gathering activity.
There are no limitations that indicate that the computer and ‘non-transitory computer readable medium’ requires anything other than a generic computing system. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
The limitations for ‘producing a FASTQ file, producing a BAM file, are post-solution activity steps that merely serve to output data from the judicial exception. As set forth in MPEP 2106.05(g), output activity that is incidental to the primary process are insignificant extra-solution activity that do not have a practical application. The limitations that limit the type of data output in claims 9 and 19 fail to integrate the judicial exception into a practical application because they merely further limit the tangential output activities but do not change their position as output activities.
The limitation in claims 9 and 19, directed to ‘wherein the method obviates using short read sequencing information of the single cells or barcode whitelist as guidance for processing the barcoded full-length cDNAs sequencing information’ does not add a practical application because there are no claims that specify how the barcode analysis is accomplished without short reads or without a barcode whitelist. As indicated in the MPEP 2106.05(a) and (f), the claim must reflect the asserted technological improvement. Merely claiming the idea of a solution or desired outcome, without restricting how the result is accomplished, generally amounts to an ‘apply it’ type of limitation rather than integration into a practical application.
The above recited additional elements do not provide a practical application of the recited judicial exception. As such, claims 1-20 are directed to an abstract idea (Step 2A, Prong 2: NO).
Step 2B
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic computing environment or well-understood, and conventional activity.
The limitations of claims 1, 5-6, 11 and 15-16, directed to receiving data, and the limitations of claims 1, 3, 11 and 13, directed to outputting files do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As set forth in MPEP section 2106.05(g), the courts have decided that limitations that merely add an insignificant extra-solution activity, do not amount to an inventive concept, particularly when the activities are well-understood and conventional. As set forth in MPEP section 2106.05(d), the courts have recognized that limitations directed to data gathering that are claimed as insignificant extra-solution activity are routine, well understood and conventional (Mayo Collaborative servs. V. Prometheus Labs., Inc., 566 U.S. at 79, 101 USPQ2d at 1968). Furthermore, as disclosed by Philpott et al. (Nature Biotechnology, 2021, p. 1-28), nanopore sequencing with known error rates (5-15%) and high read count of up to 250M reads per PromethION flow cell which can run ~5000 cells per run was commercially available at the time of the effective filing date (p. 1, col. 1, para. 2). Additionally, outputting data (i.e. storing and retrieving information from memory) has also been deemed well-understood, routine and conventional activity (Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
The limitations of claims 11-14 and 17-20, pertaining to the computer and computer readable medium used to execute the method, are directed to performing judicial exceptions with a generic computing system on a generic computer. These limitations are not sufficient to amount to significantly more than the judicial exception because, as set forth in the MPEP section 2106.05(d)(II)), using a generic computing environment or generic computer to perform the judicial exception, has been deemed well-understood, routine and conventional activity including receiving or transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362), performing repetitive calculations (Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012)), and storing and retrieving information in memory (Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)). Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more.
The limitations of claim 9 and 19 directed to ‘the method obviates using short read sequencing information of the single cells OR barcode whitelist as guidance for processing the barcoded full-length cDNAs sequencing information’, are considered to be well-understood, routine and conventional as there were multiple approaches for doing long-read only analysis with identification of cell barcodes that do not require the addition of matched short reads. As disclosed by You et al. (16 August 2022, BioRxiv, doi: https://doi.org/10.1101/2022.08.16.504056, p. 1-20) there were 6 such approaches including BLAZE, Fan et al. 2021 (third generation sequencing of single cells); Philpott et al. 2021 scCOLOR-seq, Volden and Vollmers (single-cell isoform analysis), Tian et al. 2021 (full length isoform analysis) and ONT Sockeye (abstract; p. 2, para. 3). Note that the limitation to perform the method without a barcode whitelist was determined to be NOT routine, well understood and conventional; however, it is claimed as an optional limitation so there are embodiments that do not include this limitation.
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
9. Claims 1-3, 9, 11-13 and 19 are rejected under 35 U.S.C. 102 (a)(1) as being unpatentable over Philpott et al. (Nature Biotechnology, 2021, Vol. 39, p. 1-8 + supplemental). The italicized text corresponds to the instant claim limitations.
Regarding claim 11, Philpott et al. discloses that after sequencing, base calling was performed on the FAST5 data to generate FASTQ files using Guppy (v4.2.2) in GPU mode from Oxford Nanopore Technologies running on a GTX 1080 Ti graphics card. Philpott et al. further disclose that the custom code for performing the method is available online on GitHub. Therefore, this computer implemented method implicitly includes the use of a computer and storage medium (p. 5, col. 2, para. 5; p. 6, col. 2, para. 2; p. 4, col. 1, para. 3; a non-transitory computer readable medium storing a program and a computer).
Regarding claims 1 and 11, Philpott et al. teaches a method for single-cell corrected long-read sequencing (scCOLOR-seq), which enables error correction of barcode and unique molecular identifier (UMI) oligonucleotide sequences and permits standalone cDNA nanopore sequencing of single
cells. Using this method, Philpott et al. discloses resolving different myeloma cell types at both the gene level (genotype) and the transcript level (phenotype) (p. 2, col. 1, para. 2; abstract; performing single cell nanopore sequencing of genotype-phenotype simultaneously (scNanoGPS), the process comprising [the method]).
Pertaining to claims 1 and 11, Philpott et al. discloses that scCOLOR-seq was applied to a mixture (1:1:1 ratio) of human NCI-H929, JJN3 and DF15 myeloma cell lines and approximately 500 cells were sequenced using a MinION flow cell and 1,200 cells sequenced using a PromethION flow cell. Philpott et al. further discloses that the cDNA sequences were full-length and each contained a barcode and UMI (p. 1, col. 2, para. 3 - p. 2, col. 1, para. 2; p. 5, col. 2, para. 3 and 5; obtaining barcoded full-length cDNAs sequencing information of single cells).
With respect to claims 1 and 11, Philpott et al. discloses performing after nanopore-based single-cell RNA sequencing after library preparation of full-length cDNA samples. Philpot et al. further discloses that after sequencing, base calling was performed on the FAST5 data to generate FASTQ files using Guppy (v4.2.2) in GPU mode from Oxford Nanopore Technologies running on a GTX 1080 Ti graphics card. After base calling and the generation of FASTQ files, for each read the barcode and UMI sequence were identified by searching for the poly(A) region and flanking regions before and after the barcode and UMI (p. 5, col. 2, para. 3 and para. 5; scanning the barcoded full-length cDNAs sequencing information to acquire barcoded information).
Regarding claims 1 and 11, Philpott et al. discloses that accurately sequenced barcodes were identified based on their dual nucleotide complementarity and that unambiguous barcodes were then used as a guide to error-correct the ambiguous barcodes in a second-pass correction analysis approach (p. 5, col. 2, para. 5; Supplementary Fig. 2; curating errors in the barcode information to produce curated barcoded information).
Regarding claims 1 and 11, Philpott et al. discloses that after reads were aligned to the transcriptome using minimap2, the resulting SAM file was converted to a BAM file and then sorted and indexed using samtools software (p. 5, col. 2, para. 5; producing at least one BAM file based on the curated barcoded information).
Regarding claims 1 and 11, Philpott et al. discloses using the processed nanopore sequence data for both genomic and transcriptomic (phenotypic) analysis. Regarding the transcriptomic analysis, Philpott et al. discloses Gene and transcript expression matrices were generated by UMI-tools count (for Oxford Nanopore data) and that gene expression data were used to visualize the single-cell data and determine cell types of each cell by first projecting data onto a UMAP, a non-linear dimensional reduction technique, followed by using clustifyr v.1.0.0 to identify correlated gene expression between single cells and bulk RNA-sequencing gene lists from a harmonize database. Regarding the genomic data, Philpott et al. disclose measuring the presence and structure of EWS-FLI fusion transcripts within each single cell (p. 6, col. 1, para. 3; p. 2, col. 2, para. 2 – p. 3, col. 1, para. 1; Fig. 2c-d; Fig. 2e-l; calculating multi-omics information of the single cells based on the at least one BAM file).
Regarding claims 2 and 12, Philpott et al. discloses that in their method of single-cell corrected long-read sequencing (scCOLOR-seq) enables error correction of barcode and unique molecular identifier oligonucleotide sequences and permits standalone cDNA nanopore sequencing of single cells. Philpott et al. further discloses that in the method, full-length cDNA sequencing information is prepared using Oxford Nanopore Technologies (abstract; p. 5, col. 2, para. 3 and para. 5; the method according to claim 1, wherein the barcoded full-length cDNAs sequencing information is obtained via long-read single cell nanopore sequencing technology).
Regarding claims 3 and 13, Philpott et al. disclose that after sequences were generated, base calling was performed on the FAST5 data to generate FASTQ files using Guppy (v4.2.2) in GPU mode from Oxford Nanopore Technologies and that after base calling and the generation of FASTQ files, for each read the barcode and UMI sequence were identified by searching for the poly(A) region and flanking regions before and after the barcode and UMI (p. 5, col. 2, para. 5; the method according to claim 1 further comprising producing a FASTQ file based on the barcoded information acquired in step (2)).
Regarding claims 9 and 19, Philpott et al. discloses that their method of single-cell corrected long-read sequencing (scCOLOR-seq), which enables error correction of barcode and unique molecular identifier oligonucleotide sequences, permits standalone cDNA nanopore sequencing of single cells (i.e. without the use of short read sequence information) (abstract; the method according to claim 1, wherein the method obviates using short read sequencing information of the single cells or barcode whitelist as guidance for processing the barcoded full-length cDNAs sequencing information).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
10. Claims 4-8 and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Philpott et al. (Nature Biotechnology, 2021, Vol. 39, p. 1-8), as applied to claims 1-3, 9, 11-13 and 19 above, in view of Lyu et al. (BioCellGen course; 2019-10-03 Analysis of single cell RNA-seq data chapter 5 p. 1-30, https://biocellgen-public.svi.edu.au/mig_2019_scrnaseq-workshop/processing-raw-scrna-seq-data.html), as evidenced by Smith (CGAT, February 14, 2019, UMI-tools v1.0.0 has landed, https://cgatoxford.wordpress.com/, p. 1-63). The italicized text corresponds to the instant claim limitations.
The limitations of claims 1-3, 9, 11-13 and 19 were taught by Philpott et al. above.
Pertaining to claims 4 and 14, Philpott et al. are silent to: the method according to claim 3 further comprising refining the barcoded information acquired in step (2) before step (3) to produce refined barcoded information independently through an algorithm iCARLO). However, this limitation was known in the art at the time of the effective filing date of the invention as taught by Lyu et al.
Regarding claims 4 and 14, para. 00152 of the instant application provides an embodiment of iCARLO algorithm to detect true cell barcodes, which included 4 steps: first, all CBs were ordered decreasingly by the number of supporting reads, the number of supporting reads and the order index were transformed into log10 scale. Next, the raw list of true CBs was estimated by thresholding the maximal partial derivatives of supporting reads against the rank of CBs. To buffer the changes, the present invention smoothed the partial derivatives within each 0.001 window of log10-scaled CB ranks.
Pertaining to claims 4 and 14, Lyu et al. does not disclose using the algorithms of iCARLO, but Lyu et al. discloses a method of reducing errors in cell barcode reads for single cell RNA-sequencing applications that effectively performs the same 4 steps disclosed in para. 00152 of the instant application as indicated above. Lyu et al. discloses that variation in droplet size, amplification efficiency, and sequencing will lead both “background” and real cells to have a wide range of library sizes. Lyu et al. further discloses an approach called “knee” point to distinguish those cell barcodes which correspond to real cells. Lyu et al. discloses that the method use the total molecules per barcode and try to find a “break point” between bigger libraries which are cells + some background and smaller libraries assumed to be purely background. The disclosed method including at least 4 steps: 1. Rank barcodes based on UMI per barcode to observe a “knee” point; 2) rank barcodes based on log10(UMI per barcode) to emphasize the “knee” point, 3) calculate derivatives (rawdiff <- diff(log_lib_size)/diff(barcode_rank)) and 4) find the extreme derivative as the inflection point and use that point to establish a threshold for identifying the true cell (barcodesinflection <- which(rawdiff == min(rawdiff[100:length(rawdiff)], na.rm=TRUE)) followed by (threshold <- 10^log_lib_size[inflection])). Lyu et al. further discloses that before the analysis, all barcodes with fewer than 10 total molecules are filtered out. (p. 21, para. 1 – p. 24, para. 1: the method according to claim 3 further comprising refining the barcoded information acquired in step (2) before step (3) to produce refined barcoded information independently through an algorithm iCARLO).
An invention would have been prima facie obvious to one of ordinary skill in the art at the effective filing date of the invention if some motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. Lyu et al. taught that for droplet-based methods only a fraction of droplets contain both beads and an intact cell. However, biology experiments are messy and some RNA will leak out of dead/damaged cells. So droplets without an intact cell are likely to capture a small amount of the ambient RNA which will end up in the sequencing library and contribute a reads to the final sequencing output. The variation in droplet size, amplification efficiency, and sequencing will lead both “background” and real cells to have a wide range of library sizes. The ‘knee’ point approach can distinguish those barcodes that correspond to real reads (p. 21, para. 1). Smith further teaches that the ‘knee’ method (based on filtering barcodes with low read counts) can distinguish true barcodes from those with INDELs (p. 5, para. 1-p. 6. Para. 1) and that the knee method is useful in cases where no ‘whitelist’ of ‘true’ cell barcodes exists (as in the case of droplet scRNA-Seq) (p. 11, para. 2 – p. 12, para. 2). Therefore, one of ordinary skill in the art would have been motivated to utilize the barcode error correction approach taught by Lyu et al. in the single cell nanopore sequencing approach taught by Philpott et al., in order to improve error correction in barcodes without the use of a ‘whitelist’. Furthermore, one of ordinary skill in the art would predict that the ‘knee’ point approach for removing barcode errors could be readily added to the method and system of Philpott with a reasonable expectation of success because they both pertain to methods of error correction for single cell RNA-seq data. The invention is therefore prima facie obvious.
Regarding claims 5 and 15, Philpott et al. discloses that after error correction of ambiguous bar codes, the barcode and UMI sequence of each read were extracted and placed within the read2 header file using UMI-tools extract (p. 5, col. 2, para. 5; the method according to claim 4 further comprising obtaining Unique Molecular Identifiers (UMIs) from the refined barcoded information).
Regarding claims 5 and 15, Philpott et al. discloses UMI-tools was forked on GitHub (https://github.com/Acribbs/UMI-tools) and the counts functionality was modified to handle the double oligonucleotide design and correct for errors. In brief, if a UMI contained at least one sequencing error, the UMI was split into two and then separately collapsed into 8 bp nucleotides. UMIs that did not contain a sequencing error were collapsed into 8 bp nucleotides without splitting. The directional method implemented within the original UMI-tools was then performed to correct UMI sequencing errors (Supplementary Fig. 3; p. 5, col. 2, para, 5 – p. 6, col. 1, para. 2; curating at least one error in the Unique Molecular Identifiers (UMIs) in step (3) for transcriptome analysis).
Regarding claims 6 and 16, Philpott et al. discloses gene and transcript expression matrices were generated by UMI-tools count (for Oxford Nanopore data) and were processed using R/Bioconductor
(v.4.0.3) and the Seurat package (v.3.1.4). Philpott et al. discloses that after this analysis, the top 2,000 highly variable transcripts or genes were selected using Seurat FindVariableFeatures
function (p. 6, col. 1, para. 3; the method according to claim 4, wherein obtaining transcripts from the refined barcoded information).
Regarding claims 6 and 16, Philpott et al. discloses that transcript-read errors are handled through transcript consensus generation: reads assigned to the same transcript/molecule are grouped and a consensus sequence is generated, which reduces the nanopore sequencing errors. In one example of this, Philpott et al. discloses detecting false gene fusion events due to PCR errors as described below: Philpott et al. discloses that scCOLOR-seq was performed on human STA-ET-1 Ewing’s cells, which are known to express the EWS–FLI protein and that they measured the presence of the EWS-FLI fusion transcript within each single cell with error correction. Given that fusion transcripts can be falsely detected as a consequence of PCR artifacts, mixed species data (of a human and mouse cell line) was first used to determine the frequency of false-positive fusion events, which showed a frequency of artifactual fusion events of 5%. A filtering threshold based on a minimum of 5 UMIs for each fusion event removed all the mixed human-mouse fusion reads, which was subsequently applied to eliminate false -positive fusion events in the Ewing’s cell data. In this process of identifying and analyzing the number of UMIs for each fusion event, errors in transcripts are curated (p. 2, col. 2, para. 2 – p. 3, col. 1, para. 1; Supplemental Fig. 18; curating at least one error in the transcripts in step (3) for the transcriptome analysis).
Regarding claims 7 and 17, Philpott et al. disclose that their method includes analysis of differential isoform usage in myeloma cell lines, and fusion transcript detection in a sarcoma cell line. Philpott et al. discloses that in this analysis, they generate both gene expression and transcript isoform expression profiles as they are both used to generate UMAP plots in Fig. 2 b and c, respectively. Philpott et al. further discloses using UMI tools to generate a gene expression count matrix and generating gene expression and isoform expression profiles using nonparametric Wilcoxon test on log2(transcript per million) expression values (abstract; Fig. 2; p. 2, col. 1, para. 2 – p. 3, col. 1, para. 1; p. 6, col. 1, para. 4; p. 5, col. 2, para. 5 – p. 6, col. 1, para. 1; the method according to claim 4, wherein the single cells multi-omics information includes at least one of gene expression matrix, isoforms profile and mutations profile)
Pertaining to claims 8 and 18, Philpott et al. discloses that BAM file was sorted and indexed using samtools and that the BAM file was used to generate the count matrix using UMI tools count, which was modified to allow the program to handle oligonucleotide blocks. Philpott et al. further discloses that UMI-tools ‘count’ was used to count features to cells before being converted to a market matrix format and that UMI-tools ‘count’ was modified to handle the double nucleotide UMIs (p. 5, col. 2, para. 5 – p. 6, col. 1, para. 1; the method according to claim 7, wherein the single cells gene expression matrix is generated via: calculating a UMI counts of genes in the single cells using the at least one BAM files; wherein each of the at least one BAM files is individually mapped).
Pertaining to claims 8 and 18, Philpott et al. discloses that scCOLOR-seq identifies transcript isoform diversity. Philpott et al. applied scCOLOR-seq to detect splice variants wherein gene expression and isoform expression profiles were analyzed using UMAP (which is a projection of each individual cell positioned based on their relative expression profiles). Philpot et al. show isoform expression analysis with a focus on CD74 (aka HLA-DR). Philpott et al. shows the transcripts of three known isoforms for the gene (fig. 2, panel e) and the corresponding expression of each of the three transcripts in a mixture of NCI-H929, DF15 and JJN3 myleoma cell lines. UMAP plots showing the relative expression of the three known Isoforms, ENST00000377775.7 , ENST00000353334.10 and ENST00000009530.12, are shown in Fig 2, f-h, respectively. It is not specifically disclosed by Philpott et al., but in order to detect the three transcriptional isoforms across the single cells (in Fig. 2f-h), the method inherently relies on consensus reads being mapped to the mature mRNA references shown in Fig. 2e (Fig. 2c-h; selecting consensus reads that mapped to mature mRNA references to detect transcriptional isoforms of the single cells).
Regarding claims 8 and 18, as single cell mutation is interpreted to be equivalent to a single cell isoform expression profile. Philpott et al. discloses generating differential transcript usage profiles for each of the three isoforms of CD74 across a population of single cells showing the relative abundance of each mutation/splice variant expressed in each cell (Fig. 2f-h). Philpott et al. also discloses generating a UMAP of relative isoform expression profiles across a population of individual cells, which is based on information from all splice variants detected in each cell (Fig. 2d) (p. 2, col. 1,para. 2 – col. 2, para. 1; Fig. 2c-h; calculating single cell mutation profiles from the consensus reads of the single cells).
11. Claims 10 and 20 are rejected under 35 U.S.C. 102 (a)(1) as being unpatentable over Philpott et al. (Nature Biotechnology, 2021, Vol. 39, p. 1-8), in view of Philpott et al. (US20240102091A1, 2021). The italicized text corresponds to the instant claim limitations.
The limitations of claims 1-3, 9, 11-13 and 19 have been taught by Philpott et al. above.
Pertaining to claims 10 and 20, Philpott et al. discloses that scCOLOR-seq was applied to a mixture (1:1:1 ratio) of human NCI-H929, JJN3 and DF15 myeloma cell lines and approximately 500 cells were sequenced using a MinION flow cell and 1,200 cells sequenced using a PromethION flow cell, thus Philpott et al. is silent to wherein the single cells include approximately 3000-6000 cells per run of the long-read single cell nanopore sequencing. However, this limitation was known in the art at the time of the effective filing date of the invention as taught by Philpott et al. (patent application).
Pertaining to claims 10 and 20, Philpott et al. teaches a method of long-read single-cell sequencing in which barcodes and UMI regions can be better identified and grouped despite errors introduced by amplification and/or sequencing. Philpott et al. teaches that in some cases, the method includes preparing single cell suspensions for the sample and single cells of the sample may be isolated in each of plurality of separate compartments. There may be at least 500, or at least 5,000, or 25,000, or 50,000, or 100,000 separate compartments, each comprising a single cell (Philpott et al. patent application; para. 0006; para. 0193; the method according to claim 2, wherein the single cells include approximately 3000-6000 cells per run of the long-read single cell nanopore sequencing).
An invention would have been prima facie obvious to one of ordinary skill in the art at the effective filing date of the invention if some motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. Philpott et al. taught that the drawback of Nanopore sequencing is the high error rate and that the fidelity of barcode and UMI region is critical for single-cell sequencing (Philpott et al. patent application, para. 0004) Philpott et al. taught that better identification and grouping of barcodes and UMI regions by overcoming errors can help realize the potential of long-read single-cell sequencing (Philpott et al. patent application, para. 0006). Philpott et al. further taught that in some applications, some cell populations are rare (e.g. see Philpott et al. patent application, Fig. 3d, Fig. 9b and Fig. 14a), suggesting that experiments with higher cell numbers can yield better data in these cases. Therefore, one of ordinary skill in the art would have been motivated to utilize the higher cell count experiment taught by Philpott et al. in the single cell nanopore sequencing approach taught by Philpott et al., because error correction of UMI and barcodes can improve utility of scRNA-seq, and some applications have some small cell populations, which would benefit from increased cell numbers. Furthermore, one of ordinary skill in the art would predict that the higher cell number could be readily added to the method and system of Philpott with a reasonable expectation of success because they both pertain to methods of error correction for single cell RNA-seq data and because the methods are identical to those discussed in the manuscript, including the Nanopore library preparation for sequencing and Nanopore-based scRNA-Seq analysis workflow disclosed in the patent application (Philpott et al. patent application, para. 0244 – 0247) and UMI error correction and dimensionality reduction and clustering and differential gene expression (Philpott et al. patent application, para. 0247-0249). Furthermore, Philpott et al. also taught that their method of barcode error detection and correction can be adjusted to work with a high number of cells/barcodes, for example by lowering the edit distance from 6 to 4 in the barcode correction strategy (due to a higher total number of barcodes) (Philpott et al. patent application, para. 0226). The invention is therefore prima facie obvious.
Conclusion
12. No claims are allowed.
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/J.J.S./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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