DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 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.
Claim Status
Claims 38-52 are pending.
Claims 38 and 47 are objected to.
Claims 38-52 are rejected.
Priority
The instant Application claims domestic benefit to US provisional application 62/941,557, filed Nov 27 2019.
Applicant's claim for the benefit of a prior-filed application, PCT/US2020/061787, filed Nov 23 2020, is acknowledged.
Accordingly, each of claims 38-52 are afforded the effective filing date of Nov 27 2019.
Information Disclosure Statement
The information disclosure statement (IDS) filed on May 25 2022 is in compliance with the provisions of 37 CFR 1.97 and has therefore been considered. A signed copy of the IDS document is included with this Office Action.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: 1006 and 1014 in FIG. 10; 1408 in FIG. 14; and 1510 and 1514 in FIG. 15D.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: microbiome visualizer 224 at [0040]; reference characters 800-816 mentioned at [0095-0108]; edges 197, 166, 167, and 168 and nodes 0, 48, 75, 76, and 90 at [00110]; and 902 and 904 at [00113-00114].
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “214” has been used to designate both Storage and Microbiome Visualizer in FIG. 2. Reference characters “500” through “516” have also been used in FIG. 5 and FIG. 8.
The drawings are objected to for the following informalities: in FIG. 8, 10, 12, and 14, “metabolytes" should be changed to “metabolites”; and in FIG. 15D, the shading used for Treatments A, B, C, and D are not distinguishable.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The amendments to the specification submitted May 25 2022 are accepted.
The disclosure is objected to for the following informalities. It is noted that for purposes of the instant Office Action, any reference to the specification pertains to the specification as originally filed on May 25 2022.
Disclosure
The specification contains sever instances of incorrect formatting or grammar, such as in the first and second to last lines of [0003] and line 7 of [0020].
At least at [0023-0024; 0196; 0223; 0226], the specification refers to color portions of FIG. 13 and 16-17. However, the figure was submitted in black and white and no petition to accept color drawings was submitted.
At [00164], reference is made to 1302 as both the bottom right and the top left squares in FIG. 13B. The top left square should be 1304.
At [00200], reference is made to processors 1204. However, 1204 only occurs in the drawings to reference a step of process 1200. It is recommended to delete “1204” in [00200].
Hyperlinks
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code. Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01. Non-limiting examples include paragraphs [0035; 0051; 0094; 0216-0217]. Applicant will note that this is exemplary and other instances may exist. It is requested that all instances be corrected.
Appropriate correction for all objections to the specification is required.
Claim Objections
The claims are objected to for the following informalities:
Claim 38 should be amended to include an “and” after “a display” on line 5.
In claim 47, “performing” on the 3rd line should be changed to “perform”, and “by applied condition” is not grammatically correct and should be amended.
Claim Rejections - 35 USC § 112
35 U.S.C. 112(b)
The following is a quotation of 35 U.S.C. 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 38-52 are rejected under 35 U.S.C. 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.
Claim 38, final limitation, recites “dynamically update the network displayed on the display”. However, the claim does not previously recite a network being displayed on the display. It is therefore not clear what the claim intends to further limit, or whether the processor is required to perform displaying the network in the first place. For compact examination, it is assumed that the claim intends to recite that the network generated in the second to last limitation is first required to be displayed on the display. The rejection may be overcome by clarifying the metes and bounds of the claim. Claims 39-50 are rejected based on their dependency from claim 38. Claims 51-52 are similarly rejected.
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.
Claims 38-52 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more.
MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
Step 1
With respect to Step 1: yes, the claims are directed to a system, a method, and a non-transitory computer readable storage medium, i.e., a process, machine, or manufacture within the above 101 categories [Step 1: YES; See MPEP § 2106.03].
Step 2A, Prong One
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) as well as a law of nature or a natural phenomenon are as follows:
Independent claims 38 and 51-52: identifying respective microbes and/or genes in the microbiome data stored in the database;
wherein the database of said microbiome data represents microbiomes, in a plurality of samples acquired at respective times, from each of a plurality of groups of animals including at least one control group and at least one treatment group (claims 51-52);
generate a network comprising nodes interconnected by edges in the memory, each node representing one or more identified microbes or one or more microbial metabolites, and each edge of the network representing an association between a respective pair of the one or more identified microbes or a reaction mediated between two metabolites by an enzyme encoded in the one or more identified genes, wherein at least some nodes and edges of the network are each associated with a condition attribute identifying one of said plurality of groups from and/or a timestamp attribute identifying a time of one of said samples; and
responsive to interactive input, dynamically update the network displayed… in accordance with a filtering, of the microbiome data, based at least on the condition attribute and/or the timestamp attribute associated with respective nodes and/or edges in the network.
Dependent claim 42: calculate a correlation, in the microbiome data, of the microbes represented by the first and second nodes; and
indicate at least some of the calculated correlation in the displayed network.
Dependent claim 47: in response to receiving interactive input, performing taxonomic restructuring of the network by applied condition.
Dependent claim 48: in response to receiving interactive input, perform said taxonomic restructuring providing identification of conditions to selectively increase or decrease relative abundance of selected organisms in the microbiome.
Dependent claim 49: in response to receiving interactive input, perform said taxonomic restructuring providing identification of conditions that maximize commensal-istic conditions that benefit a host of the sample or minimize competition that causes conditions detrimental to the host.
Dependent claims 39-41, 43-44, 47, and 50 recite further steps that limit the judicial exceptions in independent claim 38 and, as such, also are directed to those abstract ideas. For example, claim 39 further limits what microbes the generated network includes; and claims 40-41, 43-44, 47, and 50 further limit what the nodes of the network represent.
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind and/or by mathematical operation because the method only requires a user to manually update a displayed network after filtering based on an attribute. Without further detail as to the methodology involved in “identifying”, generating”, “updating”, “filtering”, “calculating”, and “performing taxonomic reconstruction”, under the BRI, one may simply, for example, use pen and paper to identify microbes and/or genes in data, generate a network comprising nodes and edges of the identified microbes or metabolites/genes, filtering the network based on attributes associated with the nodes and/or edges, updating the network after filtering, calculate and display a correlation in the network, and performing taxonomic reconstruction based on a condition. The display of an abstract idea (i.e., displaying a network) is considered to recite that same abstract idea (see Interval Licensing LLC v AOL, Inc., 896 F.3d 1335, 1344-45 (Fed. Cir. 2018), which recognized that information “is an intangible” and that “the collection, organization, and display of two sets of information on a generic display device is abstract absent a specific improvement to the way computers operate”). Some of these steps, such as calculate a correlation, require mathematical techniques as the only supported embodiments, as is disclosed in the specification as published at least at [0069; 0081; 0087-0088].
Therefore, claim 38 and 51-52 and those claims dependent therefrom recite an abstract idea [Step 2A, Prong 1: YES; See MPEP § 2106.04].
Step 2A, Prong Two
Because the claims do recite judicial exceptions, direction under Step 2A, Prong Two, provides that the claims must be examined further to determine whether they integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III).
Additional elements, Step 2A, Prong Two
With respect to the instant recitations, the claims recite the following additional elements:
Independent claim 38: storing a database of said microbiome data representing microbiomes, in a plurality of samples acquired at respective times, from each of a plurality of groups of animals including at least one control group and at least one treatment group.
Dependent claims 45-46 recite steps that further limit the recited additional elements in the claims. For example, claim 45-46 further limits the stored microbiome data;
The claims also include non-abstract computing elements. For example, independent claim 38 includes a system comprising a memory, a display, and a processor; claim 51 includes a display; and claim 52 includes a non-transitory computer readable storage medium storing instructions, which, when executed by one or more processors of a computer, causes the computer to perform operations, and a display.
Considerations under Step 2A, Prong Two
With respect to Step 2A, Prong Two, the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “storing a database”, perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
Further steps directed to additional non-abstract elements of the computing system in claims 38 and 51-52 do not describe any specific computational steps by which the “computer parts” perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, and therefore the claim does not integrate that judicial exceptions into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc.… are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (MPEP 2106.05(f)).
The specification as published discloses that there is a need for systems and methods capable of visualizing digitized microbiome data from animals in a format that allows a scientist to interpret the data and reach actionable conclusions, including, but not limited to the identification of biomarkers and therapeutic targets at [0005], but does not provide a clear explanation for how the additional elements provide these improvements. Therefore, the additional elements do not clearly improve the functioning of a computer, or comprise an improvement to any other technical field. Further, the additional elements do not clearly affect a particular treatment; they do not clearly require or set forth a particular machine; they do not clearly effect a transformation of matter; nor do they clearly provide a nonconventional or unconventional step (MPEP2106.04(d)).
Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [Step 2A, Prong 2: NO; See MPEP § 2106.04(d)].
Step 2B (MPEP 2106.05.A i-vi)
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant claims, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)). As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
With respect to claims 38 and 51-52 and those claims dependent therefrom, the computer-related elements or the general purpose computer do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)). The specification as published also notes that computer processors and systems, as example, are commercially available or widely used at [0040-0041; 0200-0208]. The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III).
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself [Step 2B: NO; See MPEP § 2106.05].
Therefore, the instant claims are not drawn to eligible subject matter as they are directed to one or more judicial exceptions without significantly more. For additional guidance, applicant is directed generally to the MPEP § 2106.
Claim Rejections - 35 USC § 103
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.
A. Claims 38-43 and 45-52 are rejected under 35 U.S.C. 103 as being unpatentable over DeHaven et al. (US 2016/0019335; newly cited) in view of Ma et al. (Scientific Reports, 2016, 6(28048):1-13; cited on the May 25 2022 IDS).
The prior art to DeHaven discloses a method for analyzing metabolite data in a sample (abstract). DeHaven, indicated by the open circles, teaches the instant features, indicated by the closed circles, as follows. Instantly claimed elements which are considered to be equivalent to the prior art teachings are described in bold for all claims.
Claim 38 discloses a system for visualizing microbiome data, comprising a memory storing a database, a display, and a processor configured to perform method steps. Claim 51 discloses a method for visualizing microbiome data. Claim 52 discloses a non-transitory computer readable storage medium storing instructions, which, when executed by one or more processors of a computer, causes the computer to perform operations. DeHaven teaches a method, system, and computer program product for analyzing metabolomics data for a plurality of metabolites in a sample ([0003]; FIG. 16), where the present disclosure is directed to implementing a system that provides storage, query-tools, and visualization of a biochemical knowledgebase [0020].
The method and operations of claims 38 and 51-52 comprise:
identifying respective microbes and/or genes in microbiome data stored in a database, wherein the database of said microbiome data represents microbiomes, in a plurality of samples acquired at respective times, from each of a plurality of groups of animals including at least one control group and at least one treatment group;
DeHaven teaches storing extensive and, in some instances, complete, biochemical pathway information including, for example, biochemicals, reactants, products, cofactors, directionality, intra-pathway relationships, combinations thereof, and/or any other suitable relationships or associations related to the biochemical pathway information [0020]. DeHaven teaches storing attributes in a database [0024], where the attributes related to additional types of -omics data (e.g., genomics (i.e., genes), transcriptomics, proteomics, DNA copy number, etc.) besides the metabolomics data [0024]. DeHaven teaches that information such as organism, species, and metadata can be associated with the data in storage [0024]. DeHaven teaches accessing metabolite profiles for a single, a group, or multiple groups (e.g., control vs. disease (i.e., control and treatment groups)) of patients at different time points [0033].
generating a network comprising nodes interconnected by edges in the memory, each node representing one or more identified microbes or one or more microbial metabolites, and each edge of the network representing an association between a respective pair of the one or more identified microbes or a reaction mediated between two metabolites by an enzyme encoded in the one or more identified genes, wherein at least some nodes and edges of the network are each associated with a condition attribute identifying one of said plurality of groups from and/or a timestamp attribute identifying a time of one of said samples; and
DeHaven teaches assigning each of a plurality of metabolites to a node, connecting corresponding nodes according to a defined relationship between corresponding metabolites to form and graphically display a nodal network (FIG. 1, 3, 4-5, 10-11; [0020]). DeHaven teaches that metabolites and/or enzymes may be assigned to nodes, and the reaction between metabolites may be assigned to edges [0024]. DeHaven teaches that at least one of the nodes and one of the relationships is annotated with at least one of empirical information associated therewith and relational information associated with other nodes and relationships [0020; 0039]. DeHaven teaches accessing metabolite profiles for a single, a group, or multiple groups (e.g., control vs. disease) of patients at different time points [0033].
responsive to interactive input, dynamically updating the network displayed on a display in accordance with a filtering, of the microbiome data, based at least on the condition attribute and/or the timestamp attribute associated with respective nodes and/or edges in the network.
DeHaven teaches that the nodal network may be searched according to at least one attribute or search characteristic of one of the metabolites, the nodes, the relationships, and the annotations, and the results of the search may be graphically displayed in relation to the nodal network [0021; 0026-0028] using, for example, a relational database and toggling between different functionalities (i.e., dynamically updating the network in response to interactive input) [0024] or using different filters [0032]. DeHaven teaches that when metabolite profiles are available for a single, a group, or multiple groups (e.g., control vs. disease) of patients at different time points, aspects of the systems, methods, and computer program products of the present disclosure may allow the user to browse these profiles directly mapped on the pathway/relationship/association networks (see, e.g., FIG. 10) via dynamic frames that appear when a node is selected [0033].
DeHaven does not explicitly teach visualizing microbiome data as instantly claimed.
However, the prior art to Ma discloses the effects of Hodgkin’s lymphoma and the chemotherapy for treating the disease on the human milk microbiome through integrated network and community diversity analyses (abstract). Ma teaches displaying bacterial species interaction networks for each of the sample groups comprised of nodes as microbial species and edges as interactions (Figures 1-10), including metabolite-OTU interaction networks built based on the correlation between the metabolite abundance and OTU, or bacterial species, abundance (p. 2, par. 4).
Regarding claims 38 and 51-52, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, DeHaven and Ma because both reference disclose methods for visualizing -omics level data. The prior art to Ma shows that microbiome data which comprises metabolite and microbiome species content is a known type of data which lends itself to network analysis. Therefore, it would have been obvious to one of ordinary skill in the art to substitute or include the data analyzed by Ma in the method of DeHaven, because one of ordinary skill in the art would have been able to carry out such a substitution and would have reasonably expected predictable dynamic network analysis of that data.
Regarding claim 39, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 39 further adds that the network includes all microbes identified for the microbiome in the microbiome data, each microbe in the microbiome data being represented by a node of the network.
DeHaven teaches visualizing large scale networks such as the human interactome and mapping images or annotations to those large scale networks [0029].
While DeHaven does not teach including microbes in the networks as discussed above, Ma teaches displaying bacterial species interaction networks for each of the sample groups comprised of nodes as microbial species and edges as interactions (Figures 1-10; p. 2, par. 4). It would have been prima facie obvious to one of ordinary skill in the art to include all identified microbes in the microbiome data of Ma as a large scale network as taught by DeHaven, because one could have merely combined each of the elements of Ma and DeHaven and each element would have performed the same function as it did separately with the predictable result of displaying a large scale microbial interaction network.
Regarding claims 40 and 43, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 40 further adds that each node of the network represents one of an operational taxonomic unit (OTU), a microbe ID, a taxonomy, or a metabolite. Claim 43 further adds that a first node and a second node in the network each represents a respective metabolite and an edge between the first and second nodes represents a gene annotation, sequence, or a reaction between two metabolites.
DeHaven teaches nodes as metabolites (see at least [0024] and FIG. 1, 3-5, 7, 10-11). DeHaven teaches that metabolites and/or enzymes may be assigned to nodes, and the reaction between metabolites may be assigned to edges [0024], which reads on claim 43.
Further, Ma teaches nodes as OTUs (Figure 1-6), which reads on OTU, microbe ID, or taxonomy as recited in claim 40.
Regarding claims 41-42, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 41 further adds that a first node and a second node in the network each represents a respective microbe and an edge between the first and second nodes represents a statistical correlation, observation, or a characteristic associating organisms together. Claim 42 further adds calculating a correlation, in the microbiome data, of the microbes represented by the first and second nodes; and indicating at least some of the calculated correlation in the displayed network.
DeHaven teaches that attributes can be statistical comparison of biochemical/metabolite levels [0022-0023; 0044], where the results of statistical procedures may be realized in association with the visually displayed results of the user query [0032], but DeHaven does not teach making networks of microbes.
However, Ma teaches displaying bacterial species interaction networks for each of the sample groups comprised of nodes as microbial species and edges as interactions (Figures 1-10; p. 2, par. 4). Ma teaches that networks were built based on pair-wise correlation between OTU abundances, community diversities and metabolite abundances, and metabolite abundances and OTU abundances (i.e., calculating correlations) (p. 2, par. 4 through p. 3, par. 1). Ma teaches displaying positive and negative correlations as edge colors and most abundant nodes based on color and size (i.e., indicating at least some of the calculated correlation in the displayed network) (Figures 1-10).
Regarding claim 45, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 45 further adds that the microbiome data includes taxonomic data derived from 16S marker gene surveys, metagenomic sequencing, or another technique allowing identification, delineation, and counting of separate organisms.
DeHaven does not teach microbiome data.
However, Ma teaches using 16S rRNA and metabolite datasets of the breast milk microbiomes (p. 2, par. 3).
Regarding claim 46, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 46 further adds that the microbiome data includes metabolic pathway data derived from predicted metagenomes, shotgun metagenomic sequencing, or another technique that allows identification, delineation, and counting of separate genes.
DeHaven teaches analyzing genetic data [0031; 0039] and performing statistical comparisons of biochemical data [0044], which reads on data generated by a technique that allows identification, delineation, and counting of separate genes.
Regarding claims 47-50, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 47 further adds that nodes in the network each represents a respective microbe, and wherein the processor is further configured to, in response to receiving interactive input, performing taxonomic restructuring of the network by applied condition. Claim 48 further adds, in response to receiving interactive input, performing said taxonomic restructuring providing identification of conditions to selectively increase or decrease relative abundance of selected organisms in the microbiome. Claim 49 further adds, in response to receiving interactive input, performing said taxonomic restructuring providing identification of conditions that maximize commensal-istic conditions that benefit a host of the sample or minimize competition that causes conditions detrimental to the host. Claim 50 further adds that nodes in the network each represents a respective microbe and, in response to receiving interactive input, performing network restructuring of the network.
DeHaven teaches that users may examine relationship between various -omics data types and between biological experiments by rank-ordering metabolic pathways maps using an enrichment fold change calculation, and bipartite networks connecting a node representing an experiment or statistical comparison to nodes representing either (1) biochemicals, (2) metabolic pathway maps, (3) pathway ontologies, or (4) keyword ontologies [0058], which is considered to read on restructuring a network based on an applied condition as in claim 47 and claim 50.
DeHaven does not teach nodes representing microbes as in claims 47-50 or performing taxonomic restructuring as in claims 47-49.
However, Ma teaches displaying bacterial species interaction networks for each of the sample groups comprised of nodes as microbial species and edges as interactions (Figures 1-10; p. 2, par. 4). Ma teaches displaying bacterial species interaction networks for each of the sample groups comprised of nodes as microbial species and edges as interactions (Figures 1-10), including metabolite-OTU interaction networks built based on the correlation between the metabolite abundance and OTU, or bacterial species, abundance (p. 2, par. 4).
Regarding claims 47-50, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, DeHaven and Ma because both reference disclose methods for visualizing -omics level data. It would have been obvious to one of ordinary skill in the art to include all identified microbes in the microbiome data of Ma as a large scale network as taught by DeHaven, because one could have merely combined each of the elements of Ma and DeHaven and each element would have performed the same function as it did separately with the predictable result of displaying a large scale microbial interaction network. It would have further been obvious to one of ordinary skill in the art to the select any attribute of the data shown in the large scale microbial interaction network to view only the portion of data relevant to that attribute and to generate new connections between the microbes (i.e., taxonomic restructuring) based on the selected attributes, to arrive at the networks disclosed by Ma, because Ma teaches that the networks produced by each of the conditions are different (Figures 1-3). Therefore, one of ordinary skill in the art would have been motivated to examine how the different conditions affect the microbial interaction networks using the dynamic method taught by DeHaven. As Ma teaches that the microbial abundances are used for each condition to build the networks (p. 2, par. 4), it is considered that DeHaven in view of Ma fairly teaches selectively increasing or decreasing the relative abundance of selected organisms in the microbiome through the taxonomic reconstruction as recited in claim 48. As Ma teaches identifying changes in the abundance of beneficial and potentially harmful metabolites and bacteria associated with breastfeeding in humans (i.e., a host) in Figure 10 (p. 6, par. 3 through p. 10, par. 1) based on health condition and treatment time point of the subjects, it is considered that DeHaven in view of Ma fairly teaches identifying conditions that maximize commensal-istic conditions that benefit a host of the sample or minimize competition that causes conditions detrimental to the host as recited in claim 49.
B. Claim 44 is rejected under 35 U.S.C. 103 as being unpatentable over DeHaven in view of Ma, as applied to claim 38 as above, and in further view of Borenstein et al. (PNAS, 2007, 105(38:14482-14487; newly cited).
Regarding claim 44, DeHaven in view of Ma teaches the system of claim 38 as described above. Claim 44 further adds that nodes of the network are constrained to exist within separate metabolic clusters representing respective organisms such that respective multiple metabolic networks each represent a different microbe and connections between metabolic clusters are connected through metabolite nodes deemed as extracellular.
DeHaven does not teach nodes representing microbes.
However, Ma teaches displaying metabolite-OTU networks (Figure 10), where metabolite nodes are distinguished based on groups and are associated with certain bacterial nodes (p. 6, par. 3 through p. 10, par. 1), which reads on metabolic clusters representing respective organisms such that respective multiple metabolic networks each represent a different microbe and connections between metabolic clusters are connected through metabolite nodes as instantly claimed. Ma does not teach extracellular metabolites as instantly claimed.
However, the prior art to Borenstein discloses the identification of a seed set of a metabolic network, the set of compounds that, based on the network topology, are exogenously acquired (i.e., extracellular metabolites) (abstract; Fig. 1; entire document is relevant). Borenstein teaches displaying the metabolic network of an organism with the seed compounds indicated in a different color (Fig. 1C). Borenstein also teaches constructing a phylogenetic tree based on seed compounds content, where the phylogenetic tree contains species as nodes connected based on exogenous compounds (Fig. 3; p. 14485, col. 1, par. 4).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, DeHaven in view of Ma with Borenstein because each reference discloses methods for performing network analysis. Ma already teaches networks of microbes clustered by metabolites. It would have been obvious to use the method of Borenstein to identify extracellular metabolites and identify which microbe clusters are connected by extracellular metabolites. The motivation to examine extracellular metabolites in the network of DeHaven in view of Ma would have been to understand interactions between the microbes and their environment, as taught by Borenstein (p. 1482, col. 1, par. 2 through col. 2, par. 2).
Conclusion
No claims are allowed.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JANNA NICOLE SCHULTZHAUS whose telephone number is (571)272-0812. The examiner can normally be reached on Monday - Friday 8-4.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached on (571)272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JANNA NICOLE SCHULTZHAUS/Examiner, Art Unit 1685