DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
As detailed on the Filing Receipt filed 9/2/2025, the instant application is a national stage application (371) of PCT/CN/2021/115705 (filed 8/31/2021) and further claims foreign priority to CN 202010790095.7 (filed 8/7/2020).
Applicant has not supplied an English translation of the listed foreign priority document, and may be required to provide an English translation if an intervening prior art reference is applied. See 37 CFR 1.55(g)(3); MPEP 213.04 and 216.
Information Disclosure Statement
The Information Disclosure Statements filed on 2/7/2023 and 2/14/2023 are in compliance with the provisions of 37 CFR 1.97 and have been considered in full. Signed copies of the IDS are included with this Office Action.
Claim Status
Claims 1-19 are pending, and under examination.
Claim Objections
Claims 17-19 are objected to under 37 CFR 1.75(c) as being in improper form because a multiple dependent claim cannot depend from any other multiple dependent claim (see MPEP § 608.01(n)). Claims 17-18 each refer to the prior multiple dependent claims 5, 9 and 15; while claim 19 refers to the prior multiple dependent claims 5, 9, 15 and 17-18. Accordingly, the improper multiple dependent claims have not been further treated on the merits.
Appropriate correction to resolve dependency is required.
Claims 1-4, 6-8, 11-12 and 16 are objected to because of the following informalities:
With respect to claim 1, the recited term “a first threshold on read coverage metrics” (line 27) should be amended to, e.g., “a first read coverage threshold” for improved clarity.
Additionally, the recited term “reads coverage” (line 22) and “coverage metrics of seed sequences” (line 23) should respectively be amended to “read coverage metrics” and “the read coverage metrics” to accord with later references to “read coverage metrics” (lines 26-27) and clarify antecedent basis.
Additionally, the recited terms “reads quantity obtained” (line 32), “reads quantity of multiple reference species” (lines 33-34) and “sum of reads quantity” (line 36) should respectively be amended to “read quantities obtained”, “read quantities of multiple reference species” and “sum of read quantities” since each of the recited terms refers to a plurality of quantities. In contrast, please note that the recited term “total reads quantity” (lines 35-36) is grammatically proper since this term refers to a singular quantity.
With respect to claims 1, 6 and 16, the recited phrase “remov[ing] iteratively seed sequences” (claim 1, lines 26-27; claim 6, line 9; claim 16, lines 29-30) should be amended to “iteratively remov[ing] seed sequences”.
With respect to claims 1 and 16, the recited phrase “perform[ing] statistical independence test… sequences, select[ing]” (claim 1, lines 17-18; claim 16, lines 19-21) should be amended to “perform[ing] a statistical independence test… sequences, and select[ing]”.
Additionally, the recited phrase “belonging to same species” (claim 1, line 34; claim 16, lines 37-38) should be amended to “belonging to the same species”.
With respect to claims 2-4 and 6-8, the recited term “claim I” (claim 2, line 1; claim 3, line 1; claim 4, line 1; claim 6, line 1; claim 7, line 1; claim 8, line 1) should be amended to “claim 1”.
With respect to claim 3, the recited phrase “wherein reaction mode can be” (line 4) should be amended to “wherein the reaction mode can be”.
With respect to claim 6, the recited phrase “screening… cluster: performing” (lines 2-4) should be amended to, e.g., “screening… cluster by: performing” to clarify that the following steps (e.g., “performing”) are constituent steps of the process of “screening” (line 2).
Additionally, the recited term “read coverage” (line 7) should be amended to “read coverage metrics” to accord with prior and later references to “read coverage metrics” (claim 1; lines 23 and 26-27; claim 6, lines 2 and 8).
With respect to claim 7, the recited phrase “in experimental environment” (line 2) should be amended to “in the experimental environment”.
With respect to claim 11, the following recited phrases:
“against NCBI NT/NR database, a set” (line 2);
“selecting most” (line 5);
“from species annotation” (line 5);
“and use” (line 6);
should be respectively amended to:
“against the NCBI NT/NR database, wherein a set”;
“selecting the most”;
“from species annotations”;
“and using”.
With respect to claim 12, the recited phrase “a first clustering: performing clustering…; or 1) performing clustering… within same species, and 2) perform clustering” (lines 1-6) should be amended to “a first clustering comprising: performing clustering…; or 1) performing clustering… within the same species, and 2) performing clustering”.
Additionally, the recited phrase “replacing old clusters… with newly formed clusters” (lines 9-10) should be amended to “replacing the old clusters… with the newly formed clusters” to clarify antecedent basis.
With respect to claim 16, the recited terms “read coverage” (line 24) and “coverage metrics” (line 25) should be respectively be amended to “read coverage metrics” and “the read coverage metrics” to accord with later usage of “read coverage metrics” (lines 29-30) and clarify antecedent basis.
Additionally, the extra space in the recited phrase “sequences , wherein” (line 28) should be removed.
Additionally, the recited terms “read quantity obtained” (line 36), “read quantity of multiple reference species” (line 37) and “sum of reads quantity” (line 39) should respectively be amended to “read quantities obtained”, “read quantities of multiple reference species” and “sum of read quantities” since each of the recited terms refers to a plurality of quantities. In contrast, please note that the recited term “total read quantity” (lines 38-39) is grammatically proper since this term refers to a singular quantity.
Appropriate correction, in accordance with Applicant intent, is required.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood
by one of ordinary skill in the art. This section documents the Examiner’s interpretation of certain claim elements under prosecutorial standards.
Claim 8 recites the term “the reference sequence database” (lines 5-6). Prior language does not use the term “reference sequence database”, but does refer to a “characteristic sequence database containing reference sequences” (claim 1, lines 6-7). The recited term is interpreted as referring to the same database as the prior language.
Optional Limitations
Claim language that suggests or makes a feature or step optional, but does not require that feature or step, does not limit the scope of a claim under the broadest reasonable claim interpretation (MPEP 2143.03).
Interpretation Under 35 USC § 112(f)
The following is a quotation of 35 USC § 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 USC § 112(f) is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 USC § 112(f):
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term, or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 USC § 112(f). The presumption that the claim limitation is interpreted under 35 USC § 112(f) is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 USC § 112(f). The presumption that the claim limitation is not interpreted under 35 USC § 112(f) is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 USC § 112(f), except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 USC § 112(f), except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means”, but are nonetheless being interpreted under 35 USC § 112(f), because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited functions and the generic placeholder is not preceded by a structural modifier. Said claim limitations are directed to constituents of the device of claim 16, and include:
a “sequencing data acquisition module” (line 3);
a “characteristic sequence database construction module” (line 7); and
a “comparative analysis module” (line 12) that includes a “first module” (line 15), a “second module” (line 17), a “third module” (line 22), a “fourth module” (line 27), a “fifth module” (line 32), and a “sixth module” (line 35).
Because these claim limitation are being interpreted under 35 USC § 112(f), they are being interpreted to cover the corresponding structures described in the specification as performing the claimed functions, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 USC § 112(f), applicant may:
(1) amend the claim limitations to avoid them being interpreted under 35 USC § 112(f) (e.g., by reciting sufficient structures to perform the claimed functions); or
(2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed functions so as to avoid them being interpreted under 35 USC § 112(f).
The specification reads, in relevant part: “this invention also relates to an electronic device, including… [o]ne or more processors; and… [a] storage device that stores one or more programs, when one or more programs are executed by said one or more processors such that said one or more processors implement [a step] of the method described above… Herein the processor can be CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute the various exemplary logic boxes, modules and circuits described in conjunction with the contents disclosed in this application” (paras. 98-100, emphasis added).
The specification thus indicates that hardware processors may implement or execute the ‘modules’. The ‘modules’ are interpreted, in light of the specification, as encompassing computer programs and the recited functions of each ‘module’ are accordingly interpreted as computer-implemented functions. See ‘Claim Rejections – 35 USC 112’ section.
Claim Rejections - 35 USC § 112
Rejection Under 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 USC § 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claim 16 is rejected under 35 USC § 112(a) for failing to comply with the written description requirement. The claim contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that a joint inventor, at the time the application was filed, had possession of the claimed invention.
With respect to claim 16, the following recited computer-implemented (see ‘Claim Interpretation’ section) limitations invoke 112(f) and lack adequate written description support:
a “sequencing data acquisition module” (line 3);
a “characteristic sequence database construction module” (line 7); and
a “comparative analysis module” (line 12) that includes a “first module” (line 15), a “second module” (line 17), a “third module” (line 22), a “fourth module” (line 27), a “fifth module” (line 32), and a “sixth module” (line 35).
In cases involving computer-implemented means-plus-function limitations, the Federal Circuit has consistently required that the structure be more than simply a general purpose computer, or microprocessor, and that the specification must disclose an algorithm for performing the claimed function. Thus, to adequately support computer-implemented ‘means-plus-function’ limitations, the specification must disclose an implementing computer and algorithms in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention at time of filing. See MPEP 2161.01 and 2181 § IV. See also Aristocrat Techs. Australia PTY Ltd. v. Int’l Game Tech., 521 F.3d 1328, 1333 (Fed. Cir. 2008, hereafter “Aristocrat”); Net MoneyIN, Inc. v. Verisign. Inc., 545 F.3d 1359, 1367 (Fed. Cir. 2008); Noah Systems Inc. v. Intuit Inc., 675 F.3d 1302, 1312 (Fed. Cir. 2012).
The specification states that the claimed device may comprise general purpose computer processors, which may execute or implement the claimed ‘modules’ (paras 98-100). The specification does not describe any particular algorithms that implement the functions ascribed to each claimed ‘module’, and thus fails provide a disclosure of an implementing computer and algorithms in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention at time of filing.
Applicant may:
(a) Amend the claim so that the claim limitations will no longer be interpreted as limitations under 35 USC § 112(f);
(b) Amend the written description of the specification such that it expressly recites what structures, materials, or acts perform the entire claimed functions, without introducing any new matter (35 USC § 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structures, materials, or acts disclosed therein to the functions recited in the claim, without introducing any new matter (35 USC § 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the functions so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed functions, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structures, materials, or acts for performing the claimed functions and clearly links or associates the structures, materials, or acts to the claimed functions, without introducing any new matter (35 USC § 132(a)); or
(b) Stating on the record what the corresponding structures, materials, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed functions. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Rejections Under 35 USC § 112(b)
The following is a quotation of 35 USC § 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-16 are rejected under 35 USC § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor, or a joint inventor, regards as the invention. The claims are generally narrative and indefinite, failing to conform with current U.S. practice. They appear to be a literal translation into English from a foreign document and are replete with grammatical and idiomatic errors. Particular issues are noted below.
With respect to claim 1 and dependents therefrom, there is uncertainty regarding scope of the recited limitation of “wherein said characteristic sequence database has been cluster processed… to obtain one-tier or multitier clusters, wherein… there is one or more seeds as reference sequences in a bottom tier cluster” (lines 8-11). The limitation allows the user to obtain one-tier or multitier clusters, however, one-tier clusters are not arranged in a plurality of tiers (e.g., a bottom tier). It is unclear how a user could obtain one-tier clusters including a bottom tier cluster.
For purposes of compact prosecution, the term “bottom tier cluster” is interpreted as encompassing either a cluster from the bottom tier of a multitier hierarchy or a cluster from a one-tier clustering scheme.
Additionally, the limiting effect of the recited differential limitation of a first sequence alignment step to performance “wherein… seed sequences do not compete with each other for read sequences” (lines 21-22) and a second sequence alignment step to performance “wherein… seed sequences compete against each other for read sequences” (lines 25-26) is unclear.
Additionally, there is uncertainty regarding scope of the recited term “relative proportion (abundance)” (line 35). It unclear if the Applicant intends to recite alternatives (i.e., “proportion, and/or abundance”) with this language, or refers to one metric. The terms “relative proportion” (or “proportion”) and “abundance” are not equivalent, although the terms “relative abundance” and “proportion” do refer to conventionally interchangeable statistical concepts. For purposes of compact prosecution, the term is interpreted as reciting alternatives.
With respect to claims 1, 16 and dependents therefrom, there is uncertainty regarding the term “low quality reads” (claim 1, line 13; claim 16, line 15). The specification mentions supplies no objective standard for measuring the scope of the term. See discussion of relative terminology in MPEP 2173.05(b). For purposes of compact prosecution, the term is interpreted as encompassing reads having a quality metric that falls below any given threshold.
Additionally, the recited limitation of “perform[ing] [a] statistical independence test between an event ‘has read aligned’ and the seed sequences, [and] select[ing] seed sequences associated with the event ‘has read aligned’” (claim 1, lines 17-18; claim 16, lines 19-21) is incomprehensible.
With respect to claim 2 and dependents therefrom, it is unclear if the claim language following the term “preferably” (line 5) simply describes preferred embodiments or limits the scope of what is claimed. Description of examples or preferences is properly set forth in the specification rather than the claims, as statement of examples and preferences in the claims may lead to confusion over the intended scope of a claim. See discussion of exemplary claim language in MPEP 2173.05(d).
The claim also recites lists of specific sample types and states that both samples from microbial hosts and environmental samples “include but are not limited to: at least one of” (lines 7 and 11) the listed sample types. The membership of these groupings, beyond those members recited, is unclear and could not be ascertained by one of ordinary skill in the art. See discussion of closed vs. open listing of alternatives in MPEP 2173.05(h) § I.
For purposes of compact prosecution, the language of the claim is interpreted as though the terms “preferably” and “but are not limited to” were absent. That is, the claim language at issue is interpreted as definite and limiting.
With respect to claim 4 and dependents therefrom, there is uncertainty regarding the scope of the recited limitation of “wherein said sample is from microbial hosts, wherein [a prior step] further includes: removing nucleic acid sequencing data of said hosts in said sample” (lines 1-2). It is unclear how particular sequencing data may be “in a sample”, or how the user is meant to remove it therefrom. For purposes of compact prosecution, the recited process at issue is interpreted as removing host sequences from the obtained sequencing data prior to sequence alignment.
With respect to claim 6 and dependents therefrom, there is uncertainty regarding scope of the recited term “the cluster” (lines 3) and “the cluster obtained in [the] last step to which each seed belongs” (lines 4-5). Prior claim language includes a step of “obtaining one-tier or multitier clusters” (claim 1; lines 9-10), i.e., a plurality of clusters. The identity of the particular referenced cluster is unclear. For purposes of compact prosecution, the term is interpreted as encompassing any obtained cluster.
Additionally, the limiting effect of the recited limitation of the sequence alignment step to performance “wherein reference sequences within the same cluster compete for reads” (lines 5-6) is unclear.
Additionally, there is uncertainty regarding scope of the recited term “a read coverage metrics” (line 8). It is unclear if the recited term refers to any particular singular, or plural, coverage metric(s), e.g., the read coverage calculated for each reference sequence. For purposes of compact prosecution, the term is interpreted as referring to the read coverage calculated for each reference sequence
Additionally, there is uncertainty regarding scope of the recited term “poor read coverage” (line 9). It is unclear if the recited term encompasses all levels of read coverage that fall below the recited threshold, or encompasses some subset range that is not necessarily equivalent to the sub-threshold range. The specification provides no objective standard for “poor read coverage”. See discussion of relative terminology in MPEP 2173.05(b). For purposes of compact prosecution, the term is interpreted as encompassing all levels of read coverage that fall below the recited threshold.
With respect to claim 8 and dependents therefrom, there is uncertainty regarding scope of the recited limitation of “labelling reference sequences aligned with reads of more than a certain number as ‘has read aligned’ or as ‘no read aligned’ otherwise” (lines 3-4). The criteria for labelling a given reference sequence aligned with reads as ‘has read aligned’ or ‘no read aligned’ is unclear.
For purposes of compact prosecution, the recited limitation is interpreted as “labelling reference sequences aligned with more than a certain number of reads as ‘has read aligned’, and labelling reference sequences aligned with less than or equal to the certain number of reads as ‘no read aligned’”.
Additionally, there is uncertainty regarding scope of the recited limitation of “wherein… according to clustering hierarchical relationship of seeds in the reference sequence database, performing statistical testing for each seed in the clustering tree to determine whether it is significantly enriched with reference sequences labeled as ‘has read aligned’ in its leaf nodes, and identifying seeds meeting requirements via screening tier by tier” (lines 5-9). Prior claim language allows the user to obtain one-tier or multitier clusters, but one-tier clustering schemes do not indicate a hierarchical relationship among clusters, do not arrange data in a clustering tree with leaf nodes, and do not facilitate tier-by-tier analysis. Thus, despite the allowance by prior claim language for the obtained clusters to be one-tier or multitier, the dependent claim operates on data features that require analysis of multitier clusters.
For purposes of compact prosecution, the recited term “wherein” (line 1) is interpreted as “wherein the obtained clusters are multitier clusters, and”. Thus, the claim is interpreted as explicitly claiming direction to embodiments where the clusters are multitier to provide context for the recited performance of operations using multitier data features.
With respect to claim 9 and dependents therefrom, the meaning of the recited term “reference sequences of said characteristic sequences” (lines 3-4) is unclear.
Additionally, there is uncertainty over scope of the recited term “said database” (line 5). Prior claim language refers to both “said characteristic sequence database” (lines 1-2) and “public databases” (line 3), and it is unclear if the recited term refers to the former or to any particular database of the latter. For purposes of compact prosecution, the recited term is interpreted as referring to any one of the obtained public databases.
With respect to claim 11 and dependents therefrom, there is uncertainty regarding scope of the recited limitation of “a set of matched reference sequences is screened from the NCBI NT/NR database according to rules based on sequence similarity and/or coverage” (lines 2-4). For purposes of compact prosecution, the recited limitation is interpreted as “wherein a set of matching database sequences is filtered according to sequence similarity and/or read coverage”.
With respect to claim 12 and dependents therefrom, the function of the recited phrase “involving in re-clustering computation” (line 10) is unclear. For purposes of compact prosecution, the surrounding limitation of “replacing [the] old clusters… with [the] newly formed clusters” (lines 9-10) is interpreted as if the recited phrase were absent.
With respect to claim 13 and dependents thereof, there is uncertainty regarding scope of the recited limitation of “wherein said clustering includes a second clustering: in case that there are too many child sequences in a cluster, splitting the cluster… and replacing…” (lines 1-2). It is unclear if the steps of “splitting… and replacing…” are required in all claimed embodiments, as the term “including” indicates that these steps are affirmative constituents of the method but the “in case” clause indicates that these steps are contingent. The scope of “too many” (line 2) is furthermore unclear.
For purposes of compact prosecution, the claim is interpreted as if the “in case” clause were absent and the steps of “splitting… and replacing…” are considered non-contingent.
Additionally, there is uncertainty of scope regarding the term “a sequence similarity standard higher than that used in said first clustering” (lines 3-4). Prior claim language does not use the term “sequence similarity standard”, and it is unclear if “that used in said first clustering” refers to the previously-mentioned “99.5% sequence similarity” (claim 12, line 8) or to some other criterion.
With respect to claim 16, there is uncertainty regarding scope of the recited limitation of “wherein said characteristic sequence database contains one or more tiers of clusters, wherein… there is one or several seeds as reference sequences in a bottom tier cluster” (lines 9-11). The limitation allows the user to obtain one-tier or multitier clusters, however, one-tier clusters are not arranged in a plurality of tiers (e.g., a bottom tier). It is unclear how a user could obtain one-tier clusters including a bottom tier cluster.
For purposes of compact prosecution, the term “bottom tier cluster” is interpreted as encompassing either a cluster from the bottom tier of a multitier hierarchy or a cluster from a one-tier clustering scheme.
Additionally, the limiting effect of the recited differential limitation of a first sequence alignment step to performance “wherein… seed sequences do not compete for reads” (lines 23-24) and a second sequence alignment step to performance “wherein… seed sequences compete among each other for reads” (lines 28-29) is unclear.
Additionally, the mathematical operations entailed by the recited limitation of “wherein in the calculation, read quantit[ies] of multiple reference sequences belonging to [the] same species to obtain a total read quantity for this species” (lines 37-38) are unclear. The recited limitation is interpreted, in accordance with a similar limitation recited in claim 1, as “wherein in the calculation, read[] quantit[ies] of multiple reference sequences belonging to [the] same species are added to obtain a total reads quantity for this species” (claim 1, lines 33-35).
Additionally, there is uncertainty regarding scope of the recited term “relative proportion (abundance)” (lines 38-39). It unclear if the Applicant intends to recite alternatives (i.e., “proportion, and/or abundance”) with this language, or refers to one metric. The terms “relative proportion” (or “proportion”) and “abundance” are not equivalent, although the terms “relative abundance” and “proportion” do refer to conventionally interchangeable statistical concepts. For purposes of compact prosecution, the term is interpreted as reciting alternatives.
Additionally, the claim includes numerous ‘means-plus-function’ limitations invoking 35 USC § 112(f), but the written description fails to disclose the corresponding structure(s), material(s), or act(s) for performing the entire claimed functions and to clearly link the structure(s), material(s), or act(s) to the functions. The limitations at issue include the following, which are directed to various device ‘modules’:
a “sequencing data acquisition module” (line 3);
a “characteristic sequence database construction module” (line 7); and
a “comparative analysis module” (line 12) that includes a “first module” (line 15), a “second module” (line 17), a “third module” (line 22), a “fourth module” (line 27), a “fifth module” (line 32), and a “sixth module” (line 35).
The specification indicates that the claimed device encompasses a general purpose computer, wherein the claimed ‘modules’ effect their respective functions via constituent processors during operation of the device. However, the specification discloses no corresponding algorithm(s) associated with a computer that implements said functions.
Mere reference to a general purpose computer with appropriate programming (e.g., functionally-defined “modules”), without providing an explanation of the appropriate programming, is not an adequate disclosure of the corresponding structure. See, e.g., Aristocrat, 521 F.3d at 1333-34 and 1337-38; Finisar Corp. v. DirecTV Group, Inc., 523 F.3d 1323, 1340-41 (Fed. Cir. 2008); see also MPEP 2181 § II(B). Therefore, the claim is indefinite and is rejected under 35 USC § 112(b).
For the above reasons, the claims are indefinite. The Examiner suggests amendment to bring the recited claim language into accordance with the Examiner’s stated interpretations, wherever these have been provided and align with Applicant intent.
With regard to resolving the indefiniteness of the means-plus-function limitations (the ‘modules’) of claim 16, in particular, Applicant may:
(a) Amend the claim so that the claim limitations will no longer be interpreted as limitations under 35 USC § 112(f);
(b) Amend the written description of the specification such that it expressly recites what structure(s), material(s), or act(s) perform the entire claimed functions, without introducing any new matter (35 USC § 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure(s), material(s), or act(s) disclosed therein to the functions recited in the claims, without introducing any new matter (35 USC § 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure(s), material(s), or act(s) and clearly links them to the functions so that one of ordinary skill in the art would recognize what structure(s), material(s), or act(s) perform the claimed functions, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure(s), material(s), or act(s) for performing the claimed functions and clearly links or associates the structure(s), material(s), or act(s) to the claimed functions, without introducing any new matter (35 USC § 132(a)); or
(b) Stating on the record what corresponding structure(s), material(s), or act(s), which are implicitly or inherently set forth in the written description of the specification, perform the claimed functions. For more information, see 37 CFR 1.75(d) and MPEP 608.01(o) and 2181.
Claim Rejections - 35 USC § 101
35 USC § 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.
Claims 1-16 are rejected under 35 USC § 101 because the claimed invention is directed to judicial exceptions without significantly more (i.e., non-statutory subject matter).
"Claims directed to nothing more than abstract ideas, natural phenomena, and laws of nature are not eligible for patent protection" (MPEP 2106.04 § I).
Abstract ideas include mathematical concepts (including formulas, equations and calculations), and procedures for evaluating, analyzing or organizing information, which are a type of mental process (MPEP 2106.04(a)(2)).
Natural phenomena and laws of nature and include principles, relations, and products that are naturally occurring or do not have markedly different characteristics compared to what occurs in nature (MPEP 2106.04(b)).
The claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea and a natural phenomenon.
Step 1: The Four Categories of Statutory Subject Matter (MPEP 2106.03)
Claims 1-15 are directed to a method, which falls under the ‘process’ category of statutory subject matter.
Claim 16 is directed to a device comprising a number of ‘modules’, which are being interpreted as encompassing computer programs (see ‘Claim Interpretation’ section). No hardware components are recited. The claimed subject matter therefore encompasses transitory embodiments (e.g., propagating signals) which do not fall under any category of statutory subject matter. See In re Nuijten, 500 F.3d 1346, 1356-57 (Fed. Cir. 2007); Mentor Graphics Corp. v. EVE-USA, Inc., 851 F.3d 1275, 1294 (Fed. Cir. 2017).
The Examiner suggests amendment to recite, e.g., “A device… [wherein] said device comprises a non-transitory computer readable storage medium storing: a sequence data acquisition module” (lines 1-3), and so on. Direction of the claim to non-transitory embodiments would cause the claim to fall under a category of statutory subject matter and overcome this portion of the rejection.
However, this amendment alone would likely not overcome rejection for recitation of
judicial exceptions without significantly more. In the interest of compact prosecution, the recited subject matter of claim 16 has been interpreted according to the Examiner’s suggestion for further analysis below regarding recitation of judicial exceptions without significantly more.
Step 2A, Prong One: Whether the Claims Set Forth or Describe a Judicial Exception (MPEP 2106.04 § II.A.1)
‘Mathematical concepts’ are relationships between variables and numbers, numerical formulas or equations, or acts of calculation, which need not be expressed in mathematical symbols (MPEP 2106.04(a)(2) § I). The claims recite elements which encompass mathematical concepts, at least under their broadest reasonable interpretation, including:
cluster processing based on sequence similarity among reference sequences to obtain one-tier or multi-tier clusters, wherein there is at least one child seed in each cluster (claim 1), i.e., clustering a dataset based on a similarity metric, via a non-hierarchically or hierarchically clustering method;
performing a statistical independence test (claim 1), wherein:
said statistical independence test is Fischer’s exact test (claim 8);
calculating read coverage metrics (claims 1 and 6);
employing a threshold that is ‘more stringent than’ a prior threshold (claims 1 and 6);
based on said reference sequences and reads quantity obtained, calculating content and proportions of reads at species level, wherein in the calculation, reads quantity of multiple reference sequences belonging to same species are added to obtain a total reads quantity for this species, and a species' relative proportion (abundance) is obtained by dividing the total reads quantity of each species by a sum of reads quantity of all species present in the sample (claim 1);
according to clustering hierarchical relationship of seeds in the reference sequence database, performing statistical testing for each seed in the clustering tree to determine whether it is significantly enriched with reference sequences labeled as "has read aligned" in its leaf nodes (claim 8);
performing clustering on said reference sequences based on sequence similarity (claim 9);
performing clustering on all non-redundant reference sequences based on sequence similarity (claim 12);
performing clustering based on sequence similarity of all non-redundant reference sequences within the same species (claim 12);
performing clustering on seeds obtained… based on sequence similarity (claim 12);
performing clustering according to 99.5% sequence similarity (claim 12); and
according to different sequence similarity thresholds, performing hierarchical clustering on seed reference sequences of the clusters obtained by said second clustering to construct a hierarchical tree (claim 14).
The recited acts of calculation constitute mathematical concepts.
‘Mental processes’ are processes that can be performed in the human mind at least with use of a physical aid, e.g., a slide rule or pen and paper (MPEP 2106.04(a)(2) § III). The claims recite elements that encompass processes that are practicably performable in the human mind, at least under their broadest reasonable interpretation, including:
removing low quality reads and reads containing sequencing adaptor sequences from sequencing data (claim 1), i.e., removing data from a dataset based on attributes;
performing sequence alignment between read sequences and seed or reference sequences (claims 1, 6);
removing completely duplicated reads generated by PCR amplification (claim 1);
evaluating coverage metrics to obtain screened seed sequences (claim 1), i.e., filtering data based on attribute values;
iteratively removing seed sequences that do not meet a read coverage threshold [to obtain screened seed sequences] (claims 1 and 2), i.e., filtering data based on attribute values;
merging seed sequences (claim 1), i.e., concatenating data strings;
obtaining reference sequences that meet a second [read coverage] threshold by iterative screening (claim 1), i.e., filtering data based on attribute values;
removing nucleic acid sequencing data of said hosts [from the obtained sequencing data] (claim 4);
filtering reference sequences according to read coverage metrics (claim 6);
removing nucleic acid sequencing data of background contaminating species in [the] experimental environment (claim 7);
labelling reference sequences based on number of alignments (claim 8);
identifying seeds meeting requirements via screening tier by tier (claim 8), i.e. filtering tiered data;
removing sequences at both ends of the amplification primers of said reference sequences (claim 9);
based on intra-species sequence similarity, performing base correction on said reference sequences with ambiguous bases and removing redundant reference sequences of 100% sequence similarity based on their species annotations and sequence similarity (claim 9), i.e., filtering and editing data based on attribute values;
removing sequences of said amplification primers and sequences at both ends of and external to the said amplification primers of said reference sequences (claim 10);
selecting the most representative species classification from species annotations of said set of matched reference sequences (claim 11);
using classification information to correct species annotation of the reference sequence (claim 11);
merging seeds that belong to different species but are clustered into the same cluster with their child sequences (claim 12);
replacing old clusters… with newly formed clusters (claim 12); and
splitting the cluster obtained by said first clustering using a sequence similarity standard higher than that used in said first clustering, and replacing clusters before splitting with new clusters formed after splitting (claim 13).
The recited steps of evaluating information, which are practicably performable in the human mind, constitute mental processes.
Mathematical concepts and mental processes constitute enumerated groupings of abstract ideas (MPEP 2106.04(a)(2) §§ I and III). Hence, the claims recite elements that, individually and in combination, constitute an abstract idea.
The claims further recite the following claim elements, which require that analyzed data embodies particular natural phenomena and/or laws of nature:
said microbial species include bacteria, archaea, fungi, mycoplasma, chlamydia, rickettsia, spirochete, and viruses, wherein characteristic nucleic acid sequences of RNA viruses are obtained by reverse transcription of viral RNA genomes to generate cDNA (claim 2);
said samples to be tested are from microbial hosts or environmental samples containing microbial species (claim 2);
said samples from microbial hosts include: at least one of feces, intestinal contents, skin, sputum, blood, saliva, dental plaque, urine, vaginal discharge, bile, bronchoalveolar lavage fluid, cerebrospinal fluid, pleural fluid, ascites, pelvic effusion, pus, and rumen (claim 2);
said environmental samples containing microbial species include: at least one of internal and external surfaces of objects, domestic water, medical water, industrial water, food, beverage, fertilizer, waste water, volcanic ash, frozen soil, silt, soil, compost, polluted river, aquaculture water bodies and air (claim 2);
said hosts are human beings (claim 5); and
said microbial characteristic nucleic acid sequences include sequences of 16S rRNA gene, 18S rRNA gene, ITS nucleic acid sequence, RNA dependent RNA polymerase (RdRp) gene of RNA viruses, viral capsid protein coding gene, and pol gene of retrovirus, or other full-length sequences of one or more among nucleic acid sequences capable of reflecting microbial taxonomic characteristics (claim 15).
The above elements specify that analyzed data represents naturally occurring user attributes, i.e., natural phenomena, having naturally occurring relationships with user creatinine levels and health risk, i.e., laws of nature, that the claimed invention allows a user of the claimed device, system, method and/or storage medium to observe.
The claims must therefore be examined further to determine whether they integrate these judicial exceptions into a practical application (MPEP 2106.04(d)).
Step 2A, Prong Two: Whether the Claims Contain Additional Elements that Integrate the Judicial Exception(s) into a Practical Application (MPEP 2106.04 § II.A.2)
The claims recite additional elements that pertain to means of gathering data that is necessary for performance of claimed method steps, including:
obtaining sequencing data by targeted enrichment of microbial characteristic nucleic acid sequences followed by next-generation sequencing of the enriched microbial characteristic nucleic acid sequences (claim 1), wherein:
the targeted enrichment in is by a method including PCR, nucleic acid probe hybridization capture, biotin labeling capture, digoxin labeling capture, isotope labeling capture, magnetic bead capture, antibody capture, CRISPR/Cas technologies, or a combination thereof, wherein reaction mode can be in a liquid, on a solid surface, or a combination thereof (claim 3); and
data includes sequences generated by PCR amplification (claim 1).
Necessary data gathering is considered to be insignificant pre-solution activity, and as such insufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
The claims further recite additional elements that require performance of claimed functions on a computer, or comprise computer hardware and/or software for performing claimed functions, including:
“with a characteristic sequence database” (claim 1);
“of said characteristic sequence database” (claim 1);
“in the reference sequence database” (claim 8);
obtaining public databases (claim 9)
“in said database” (claim 8);
performing BLAST search for each reference sequence against the NCBI NT/NR database (claim 11); and
a device comprising various ‘modules’ (claim 16).
The claims do not describe any specific computational steps by which a computer performs or carries out functions drawn to the judicial exceptions, nor do they provide any details of how specific structures of a computer are used to implement these functions. The claims state nothing more than that a generic computer performs functions drawn to the judicial exceptions, and are therefore mere instructions to apply the judicial exceptions using a computer. As such, the claims do not integrate the judicial exceptions into a practical application (see MPEP 2106.04(d) § I and 2106.05(f)).
No further additional elements are recited.
When the claims are considered as a whole: they do not improve the functioning of a computer, other technology, or technical field (MPEP 2106.04(d)(1) and 2106.05(a)); they do not apply the judicial exceptions to effect a particular treatment or prophylaxis for a disease or medical condition (MPEP 2106.04(d)(2)); they do not implement the judicial exceptions with, or in conjunction with, a particular machine (MPEP 2106.05(b)); they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)); and they do not apply or use the judicial exceptions in some other meaningful way beyond linking the use of the judicial exceptions to a particular technological environment and/or field of use (e.g., computational microbiome analysis; MPEP 2106.05(e) and 2106.05(h)).
Hence, the recited judicial exceptions are not integrated into a practical application. See MPEP 2106.04(d) § I.
Because the claims recite an abstract idea and a natural phenomenon, and do not integrate those judicial exceptions into a practical application, the claims are directed to those judicial exceptions. Claims that are directed to judicial exceptions must be examined further to determine whether the additional elements besides the judicial exceptions render the claims significantly more than the judicial exceptions. Additional elements besides the judicial exceptions may constitute inventive concepts that are sufficient to render the claims significantly more (MPEP 2106.05).
Step 2B: Whether the Claims Contain Additional Elements that Amount to an Inventive Concept (MPEP 2106.05)
As noted above, several recited additional elements amount to insignificant extra-solution activity. Mere addition of insignificant extra-solution activity does not amount to an inventive concept that would render the claims significantly more than the recited judicial exceptions, particularly when the activities are well-understood or conventional (MPEP 2106.05(g)). The conventionality of recited additional elements that amount to insignificant extra-solution activity must be further considered.
Recited additional elements amounting to insignificant extra-solution activity encompass the following processes, which are indicated as activity that may be performed with commercially-available products by the instant specification (see MPEP 2106.07(a) § III):
obtaining sequencing data via recited techniques (para. 42: “Perform sequencing according to the instrument manuals, device model, and instructions for reagents. The technology herein is compatible with NGS sequencing instruments manufactured by, but not limited to, Thermo Fisher, lllumina, BGI and other major suppliers, and all currently marketed instruments and reagents”);
Additionally, recited additional elements amounting to insignificant extra-solution activity encompass the following computer-implemented functions, which the courts have held as coextensive with a general-purpose computer and/or well-understood, routine and conventional:
Receiving, storing, and processing data (In re Katz Interactive Call Processing Patent Litigation, 639 F.3d 1303, 1316 (Fed. Cir. 2011); EON Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 622 (Fed. Cir. 2015)), including:
Receiving data over a network, e.g., from public databases (buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)); and
Constructing a database (Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014)).
Hence, the encompassed extra-solution activity is considered well-understood, routine and conventional. Well-understood, routine and conventional activity is insufficient to constitute an inventive concept that would render the claims significantly more than judicial exceptions (MPEP 2106.05(d)).
Mere instructions to implement judicial exceptions using a computer are, when considered individually, similarly insufficient to constitute an inventive concept that would render the claims significantly more than said judicial exceptions (see MPEP 2106.05(f)).
When the claims are considered as a whole, they do not integrate the judicial exceptions into a practical application; they do not confine the use of the judicial exceptions to a particular technology; they do not solve a problem rooted in or arising from the use of a
particular technology; they do not improve a technology by allowing the technology to
perform a function that it previously was not capable of performing; and they do not
provide any limitations beyond generally linking the use of the judicial exceptions to a particular technological environment and/or field of use (e.g., computational microbiome analysis; MPEP 2106.05(e) and 2106.05(h)).
Hence, the claims do not include additional elements that are sufficient to amount to significantly more than the recited judicial exceptions. See MPEP 2106.05.
Conclusion: Claims are Directed to Non-statutory Subject Matter
For these reasons, the claims, when the limitations are considered individually and as a whole, are directed to judicial exceptions and lack an inventive concept. Hence, the claimed invention does not constitute significantly more than the judicial exceptions, so the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 USC §§ 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 USC § 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 USC § 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 USC § 102(b)(2)(C) for any potential 35 USC § 102(a)(2) prior art against the later invention.
Claims 1-7, 9-13 and 15-16 are rejected under 35 USC § 103 as being unpatentable over Li (US 2015/0242565; effectively filed 4/30/2015; corresponds to CN 104039982 listed on IDS filed 2/7/2023), in view of Edgar (Nature Methods 10: 996-998; published 8/18/2013).
Claim 1 is directed to a method for identifying microbial species and obtaining related information by sequencing in a sample, comprising the following steps: obtaining sequencing data by targeted enrichment of microbial characteristic nucleic acid sequences followed by next-generation sequencing of the enriched microbial characteristic nucleic acid sequences; comparing and analyzing said sequencing data with a characteristic sequence database
containing reference sequences to identify microbial composition in said sample.
The claim particularly claims embodiments wherein: said characteristic sequence database has been cluster processed in advance based on sequence similarity among reference sequences to obtain one-tier or multi-tier clusters; there is at least one child seed in each cluster and there is one or more seeds as reference sequences in a bottom tier cluster.
The claim further specifies that said comparing and analyzing includes steps of: removing low quality reads and reads containing sequencing adaptor sequences from said sequencing data; performing sequence alignment between read sequences and seed sequences of said characteristic sequence database, removing completely duplicated reads generated by PCR amplification, performing statistical independence test between an event “has read aligned” and the seed sequences, selecting seed sequences associated with the event "has read aligned" as primary screened seed sequences; performing sequence alignment between read sequences and said primary screened seed sequences, wherein said primary screened seed sequences do not compete with each other for read sequences, calculating reads coverage for each seed sequence, then evaluating coverage metrics of seed sequences to obtain secondary screened seed sequences; performing sequence alignment between read sequences and said secondary screened seed sequences, wherein said secondary seed sequences compete against each other for read sequences, calculating read coverage metrics for each seed sequence, and removing iteratively seed sequences that do not meet a first threshold on read coverage metrics to obtain tertiary screened seed sequences; merging said tertiary screened seed sequences and aligning them with read sequences, obtaining reference sequences that meet a second threshold by iterative screening, wherein the second threshold is more stringent than the first threshold of step d); and based on said reference sequences and reads quantity obtained in step e), calculating content and proportions of reads at species level, wherein in the calculation, reads quantity of multiple reference sequences belonging to same species are added to obtain a total reads quantity for this species, and a species' relative proportion (abundance) is obtained by dividing the total reads quantity of each species by a sum of reads quantity of all species present in the sample.
With respect to claim 1, Li discloses a method and system to analyze composition of microbial communities from environmental samples (para. 0001), including steps of: performing library construction and next-generation sequencing on genomic DNA extracted from an environmental sample, which contains the metagenome of a microbial community, to obtain sequencing data (paras. 0024 and 0040-45); removing low quality reads and adapter sequences (paras. 0048-49); performing sequence alignment between sequencing fragments (i.e., read sequences) and elements (contigs) in a constructed or known reference set (para. 0026 and 0122); removing duplicates and combining non-redundant reference contigs/sets (i.e., merging screened reference sequences) to construct a final, non-redundant reference set (paras. 0017, 0025, 0053-54 and 0120); and calculating relative abundance of each reference element (contig) within the sample based on the number of reads mapped to the element and the element length, i.e., read coverage metrics ((paras. 0026, 0057 and 0122-23; see pg. 8, Table 2).
Li describes application of their methodology to data obtained by sequencing the 16S rRNA V6 hypervariable region in samples (para. 0155), which necessary involves targeted enrichment prior to sequencing. Li further discloses calculating correlation coefficients between each two reference elements based on their relative abundances and performing hierarchical clustering of reference elements based on the correlation coefficients to generate initial bins (para. 0126); and iteratively optimizing bins via an expectation-maximization algorithm (paras. 0130-33).
Li additionally discloses an iterative ‘advanced assembly’ process, comprising steps of: performing sequence alignment of all reads to the fragments in each reference bin, collecting reads that map to a given bin better than an identity threshold, assembling collected reads, performing similarity-based binning to divide existing bins into new bins, and replacing the old bins with the new bins if precision is improved; wherein these steps are repeated until the size of the genome sequence in each bin is extended by less than 5% relative to the previous bin sequence (paras. 0090-93 and 0138). The constituent iterative performance of alignment steps is considered equivalent to repeated performance of sequence alignment as claimed.
Li discusses the significance of bins as groupings of elements having covariant abundance in many samples, discloses determination of a single ‘best matched bacterium’ for each bin based on percentage of child contigs in the bin, and states that each optimized bin represents one species (paras. 0059, 00128 and 0136). This means that the summed relative abundance of elements in a given optimized bin, within a given sample, is the relative abundance of the corresponding species.
Li does not expressly disclose performing a statistical independence test for read alignment as claimed. However, Li does disclose calculation of reference element abundance based in part of the number of mapped reads (paras. 0026, 0057 and 0122-23), and abundance-based binning of reference elements (para. 0126). All reference elements with 0 mapped reads would be clustered together, partitioning the reference set on the basis of ‘having aligned reads’. In this way, the abundance-based binning process of Li is considered at least functionally equivalent to testing statistical independence between a reference sequence and ‘having reads aligned’ as claimed. One of ordinary skill in the art would find it obvious to select non-zero abundance (i.e., supported) reference elements for further analysis.
Li does not disclose cluster processing of reference sequences in advance to yield clusters containing seed sequences as claimed, and does not disclose performance of described analytical steps with respect to seed sequences (e.g., removing seed sequences that do not meet read coverage thresholds) as claimed.
Edgar presents a pipeline, called UPARSE, for characterizing microbial community structure by constructing accurate operational taxonomic units (OTUs) from amplicon reads (pg. 996, Abstract and l. column). Edgar teaches clustering of reads into OTUs (i.e., clusters) based on sequence identity wherein: each unique read sequence is aligned (matched) against the representative sequences of any existing OTUs, and if a match exceeds an identity threshold then the abundance of the considered OTU is updated (i.e., the read is assigned to the cluster); otherwise (no matches above threshold) the pipeline assesses chimerism by constructing a parsimonious model sequence and discarding the read if the model sequence is chimeric, wherein ‘Chimeric’ classification is based in part on a <97% match between the reads and the reference sequences; otherwise the read is added to the database as the representative sequence of a new OTU (pg. 999, r. column). Each cluster (OTU) is defined by a single representative sequence, i.e., a seed sequence (and additional members are child sequences).
Edgar further teaches discarding singleton reads, and discusses the (acceptable) consequence of effectively removing representative sequences that do not meet a read coverage threshold (pg. 999, l. column).
Additionally, Edgar presents findings that UPARSE achieves a substantial improvement in OTU construction over current methods. Specifically, Edgar teaches that UPARSE consistently recovers almost all detectable species, with sensitivity sufficient to detect several contaminants, from variably-sized pools of reads (10,000 to >2 million) in three widely-employed data formats (454, Illumina unpaired and Illumina paired), while not requiring technology- or gene-specific parameter tuning (hence, being applicable to a wide range of marker genes and sequencing data generated by a wide range of technologies) and having substantially low computational resource requirements (pg. 996, l. column; pg. 998, l. column).
With respect to claim 2, Li exemplifies microorganisms including bacteria, fungi and viruses (para. 0012). Li discloses embodiments wherein the environmental sample is obtained from internal environments, e.g., intestinal, or natural environments, e.g., soil (para. 0039).
With respect to claim 3, Li describes application of their methodology to data obtained by sequencing of the 16S rRNA V6 hypervariable region, wherein high quality tags were extracted from raw tags by filtering primer sequences (para. 0155). In other words, data obtained by targeted enrichment of said region via PCR prior to sequencing.
With respect to claim 4, Li discloses filtering sequences of the host genome (para. 0075).
With respect to claim 5, Li discusses application of metagenomic approaches to investigating microbial communities that inhabit human bodies (para. 0004), and discloses an embodiment wherein the sample is a human intestinal sample (para. 0055).
With respect to claim 6, Li discloses an iterative ‘advanced assembly’ process, comprising steps of: performing sequence alignment of all reads to the fragments in each reference bin, collecting reads that map to a given bin better than an identity threshold, assembling collected reads, performing similarity-based binning to divide existing bins into new bins, and replacing the old bins with the new bins if precision is improved (paras. 0090-93 and 0138).
The application of more-stringent identity thresholds is considered an obvious variant of the disclosed iterative optimization process.
With respect to claim 7, Edgar teaches detection of contaminants, wherein a constructed OTU sequences exhibiting a high-identity match to a species that is not in the targeted community are classified as ‘Contaminant’ (pg. 996, r. column; pg. 998, l. column). Although Edgar does not expressly teach removal of contaminant sequences, one of ordinary skill in the art would find this an obvious application of the disclosed differential identification of non-target contaminant sequences that are present in the sample.
With respect to claim 9, Li discloses removing adapter sequences from the obtained fragments (para. 0048). In other words, removing sequences at both ends of the amplification primers. Edgar teaches merging identical reads, i.e., removing redundant sequences of 100% sequence similarity, and merging paired reads by calculating the most probable base calls in overlapped regions, i.e., base correction (pg. 999, l. column).
With respect to claim 10, Li discloses extraction of high-quality tags from raw tags by filtering adapter sequences, overlap and primer sequences (para. 0155). In other words, removing amplification primer sequences and sequences at both ends of and external to the said amplification primers.
With respect to claim 11, Li discloses annotating taxonomy of assembled genomes based on their alignment to sequenced genomes of the NCBI NR database via BLASTn (paras. 0062-64). Edgar also teaches searching each read sequence against the NCBI NT database using MEGABLAST (pg. 1000, l. column).
With respect to claim 12, Edgar teaches greedy clustering of reads into OTUs (i.e., clusters) based on sequence identity wherein: each unique read sequence is aligned (matched) against the representative sequences of any existing OTUs, and if a match exceeds an identity threshold then the abundance of the considered OTU is updated (i.e., the read is assigned to the cluster); otherwise (no matches above threshold) the pipeline assesses chimerism by constructing a parsimonious model sequence and discarding the read if the model sequence is chimeric, wherein ‘Chimeric’ classification is based in part on a <97% match between the reads and the reference sequences; otherwise the read is added to the database as the representative sequence of a new OTU (pg. 999, r. column).
With respect to claim 13, Li discloses confirming assembly precision via a similarity-based binning (i.e., clustering) approach, dividing each particular bin by re-binning the elements within each to achieve higher precision (paras. 0036, 0090-93 and 0138), i.e., splitting the clusters using a higher sequence similarity standard) into a plurality of bins.
With respect to claim 15, Li describes application of their methodology to data obtained by sequencing a hypervariable region of the 16S rRNA gene (para. 0155).
Edgar also teaches applicability of their method to a wide range of marker genes and sequencing technologies, and demonstrates evaluation of 16S rRNA and ITS sequences (pg. 996, r. column).
With respect to claim 16, Li discloses implementation of described functions with a system comprising various ‘modules’, and exemplifies numerous ‘modules’ including a DNA extraction module, library construction module, sequencing module, filter module, assembly and construct module, aligning module, binning modules, advanced assembly module and demonstration module (paras. 0065-66).
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the claimed invention, said practitioner would have combined OTU clustering, as taught by Edgar, with the analytical method disclosed by Li, because Edgar teaches that their method consistently recovers almost all detectable species in a sample, with sensitivity sufficient to detect several contaminants, from variably-sized pools of reads in variable data formats, while not requiring technology- or gene-specific parameter tuning and having substantially low computational resource requirements (pg. 996, l. column; pg. 998, l. column). Said practitioner would have had a reasonable expectation of success because Li and Edgar both concern methods of microbial community profiling based on cluster analysis of sequencing reads.
In this way the disclosure of Li, in view of Edgar, makes obvious the limitations of claims 1-7, 9-13 and 15-16. Thus, the claimed invention is prima facie obvious.
Claims 8 and 14 are rejected under 35 USC § 103 as being unpatentable over Li, in view of Edgar, as applied to claims 1, 9 and 12-13 above, and further in view of Huang (Bioinform. 26(5): 680-682; published 1/6/2010).
With respect to claims 8 and 14, Li discloses calculation of reference element abundance based in part of the number of mapped reads (paras. 0026, 0057 and 0122-23), and abundance-based binning of reference elements (para. 0126). All reference elements with 0 mapped reads would be clustered together, partitioning the reference set on the basis of ‘having aligned reads’. In this way, the abundance-based binning process of Li is considered at least functionally equivalent to labeling reference sequences as ‘has read aligned’ or ‘no read aligned’ as claimed.
Li does not disclose according to clustering hierarchical relationship of seeds in the reference sequence database, performing Fischer’s exact test for each seed in the clustering tree to determine whether it is significantly enriched with reference sequences labeled as ‘has read aligned’ in its leaf nodes, and identifying seeds meeting requirements via screening tier by tier. Edgar teaches clustering of reads into OTUs (pg. 999, r. column). Edgar does not teach according to clustering hierarchical relationship of seeds in the reference sequence database, performing Fischer’s exact test for each seed in the clustering tree to determine whether it is significantly enriched with reference sequences labeled as ‘has read aligned’ in its leaf nodes, and identifying seeds meeting requirements via screening tier by tier.
Huang presents improvements to CD-HIT, a program for clustering and comparing large biological sequence datasets (pg. 680, Abstract), and describes an incremental, hierarchical clustering process where read sequences are compared to existing cluster representatives (i.e., seed sequences) and, based on identity thresholds, either assigned to an existing most-similar cluster or assigned as the representative of a new cluster (pg. 681, r. column). Huang specifies a number of criteria available to a user as clustering parameters, including alignment length, unaligned length and alignment coverage (pg. 680, r. column – pg. 681, l. column).
Huang also teaches joint analysis of sequence clustering and annotation enrichment, involving calculation of a P-value using Fischer’s exact test to assess whether a given annotation term is enriched for sequences within a given hierarchical cluster (pg. 681, l. column), i.e., leaf node. Huang suggests application of this functionality to check cluster quality at different identity levels (pg. 681, l. column), i.e., screen seeds tier by tier.
The annotation enrichment analysis of Huang is considered equivalent to the label enrichment analysis of the claim, as the recited sequence labels are considered equivalent to annotation terms. The specific names of the labels (‘has read aligned’ and ‘no read aligned’) are considered to be nonfunctional descriptive material, and do not patentably distinguish the claim from the teachings of Huang.
Huang teaches that CD-HIT is freely available as a command-line executable and has also been implemented as a publicly-available web server that provides an interactive interface, additional data visualization tool, and precalculated, regularly updated sequence cluster for several widely used databases including the NCBI NR (pg. 680, Abstract - r. column).
With respect to claim 14, Huang further describes the implemented clustering as comprising: clustering the original input dataset using a high identity threshold, and performing additional clustering runs at a lower threshold, wherein the representatives of each previous clustering are the input of the following clustering run, to produce a hierarchical structure (pg. 681, l. column) . In other words, according to different sequence similarity thresholds, performing hierarchical clustering on seed sequences of previously-obtained clusters to construct a hierarchical tree.
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the claimed invention, said practitioner would have implemented clustering at multiple thresholds and annotation enrichment analysis using Fisher’s exact test, as taught by Huang, with the analytical method disclosed by Li, in view of Edgar, because Huang teaches that their method is implemented as a publicly-available web server that performs biological sequence clustering, and allows users to implement alignment coverage criteria, while also providing additional data visualization tools and precalculated clusters for the NCBI NR database (pg. pg. 680, Abstract - r. column). Said practitioner would have had a reasonable expectation of success because Li and Huang both concern methods of microbial community profiling based on cluster analysis of sequencing reads. Additionally, Edgar and Huang both particularly discuss methods for hierarchical, similarity-based clustering of sequence data based on identity thresholds to determine representative sequences.
In this way the disclosure of Li, in view of Edgar and Huang, makes obvious the limitations of claims 8 and 14. Thus, the claimed invention is prima facie obvious.
Conclusion
At this time in prosecution, no claim is allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Theodore C. Striegel whose telephone number is (571)272-1860. The examiner can normally be reached Mon-Fri 12pm-8pm ET.
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/T.C.S./Examiner, Art Unit 1685
/JESSE P FRUMKIN/Primary Examiner, Art Unit 1685 June 23, 2026
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