PROTEIN AND PEPTIDE DATABASE-ENABLED RAPID MONITORING AND QUANTIFICATION OF MICROBES AND ASSOCIATED PRODUCTS

§101 §103 §112

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 . Claim Status Claims 1-18 are currently pending and under examination herein. Claims 1-18 are rejected. Claim 3 is objected to. Priority Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. NL2027256, filed on 12/31/2020. Therefore, the effective filing date of claims 1-18 is 12/31/2020. Information Disclosure Statement The information disclosure statement (IDS) submitted on 06/29/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. A signed copy of a list of references cited from each IDS is included in this Office Action. Drawings The drawings filed on 06/29/2023 are accepted. Specification The specification filed on 06/23/2023 is accepted. Claim Objections Claim 3 is objected to for reciting “according to any of claim 2”. The Examiner recommends that the claim be amended to “according to claim 2” for clarity. Appropriate correction is required. Claim Interpretation Claims 1-18 recite phrases such as “at least one of…” or “selected from…” following with a list of limitations. The Examiner notes that even though the claims have been amended to recite “and” rather than “or”, they still read as if only one of the elements are required to meet the claim limitations. For example in claim 8, the Examiner suggests that the claim be amended to recite “relates to a relative amount and an absolute amount” rather than “at least one of a relative amount and an absolute amount” if the Applicant intends on both elements to be present in the instant application. During patent examination, claims are given their broadest reasonable interpretation consistent with the specification. See MPEP 2111. Therefore, the limitation of "A or B" is interpreted to encompass embodiments comprising A, B, or either alternative, and the prior art need only disclose one of the recited alternatives to satisfy the limitation. Furthermore, the Examiner notes that claim 8 and 10 recite contingent limitations where the broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met (see MPEP 2111.04). Therefore, claims that recite limitations following contingent limitations are not considered in the broadest reasonable interpretation in view of the prior art. For instance, claim limitations that recite a "when" condition is contingent and not considered in view of the prior art. Claim Rejections - 35 USC § 112 The following is a quotation of the first paragraph of 35 U.S.C. 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. The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112: 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 of carrying out his invention. 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. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claim 16-18 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) 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 the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The Examiner notes that computer programs alone cannot do the mass spectroscopy step, protein extraction steps, or any other physical steps described in claim 1 and how the physical steps can be accomplished within a computer program are not sufficiently described. Although the specification generically recites that the “invention relates to a microbiome monitoring computer program comprising instructions for monitoring a microbiome…” on page 6 lines 2-18, instructions alone cannot perform the physical actions described. Appropriate correction is required. Additionally, claim 18 recites “the computer program comprises instructions for learning selected from machine learning, adaptive learning, and combinations thereof”, however, there is no description in the specification as to what the learning architecture is comprised of and what the inclusion of machine learning is supposed to accomplish. The specification generically recites that “selection is done empirically, e.g. looking for sequences at a selected taxonomic ranking (at least genus), and/or peptides that are good to measure/quantify (physicochemical properties), and/or have uniform proportions, representing the community, or genera of interest. Of course, machine learning may be used in an alternative, in particular once inventors have collected data over many plants, over a longer period of time” in lines 15-19 on page 4. However, the learning is generally recited without any detail regarding whether it is related to the monitoring process of claim 1, the reactor of claim 10, or drug response analysis of claim 14. Appropriate correction is required. Claims 1-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The term “directly” or “indirectly” in claim 1 is a relative term which renders the claim indefinite. The term “directly” and “indirectly” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Particularly, there is no support in the specification as to what the difference between directly obtaining an amount of extracted protein sequence versus indirectly would be. The specification does state in [0010] that “typically said amount is determined using chemical analytics,” however, it is unclear what types of chemical analytics are considered a direct measuring tool versus an indirect measuring tool. Furthermore, direct versus indirect analysis in subsequent step 2e is also recited with no details within the specification and therefore, the metes and bounds cannot be determined with reasonably certainty. Thus, it is unclear what acts or techniques fall within the scope of the “indirectly determining” limitation and claim 1 is indefinite under 35 U.S.C. 112(b). In addition, the term “high resolution” in claim 7 is a relative term which renders the claim indefinite. The term “high resolution” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. To one of ordinary skill of the art, “high resolution spectroscopy” allows for spectral features to be measured with very fine detail compared to low resolution spectroscopy provides less detailed measurements, but using the term “high” without any support in the specification as to what “high” amounts to. Therefore, the Examiner will interpret high resolution to be any type of resolution mass spectroscopy. Similarly to claim 1, regarding claim 8, the claim recites “(2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry, and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins”. There is no support in the specification as to what the difference between determining an amount of protein sequence directly is performed using high resolution mass spectrometry versus determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry would be. As aforementioned, it is unclear what acts or techniques fall within the scope of the “indirectly determining” limitation and claim 1 is indefinite under 35 U.S.C. 112(b). In the interest of compact prosecution, the Examiner will interpret the instant claims to mean any method capable of accomplishing the measuring steps recited above. The term “most characterizing” in claim 8 is a relative term which renders the claim indefinite. The term “most characterizing” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Therefore, claim 8 is rendered indefinitely using the term “most” without any support in the specification as to what “most” amounts to. Therefore, the Examiner will interpret the claim as any extracted protein sequence with characterization. Claims 1, 3, 8, 9, 10, 16, and 17 recite “in particular…” followed by further limiting features. According to MPEP 2173(c), use of a narrow numerical range that falls within a broader range in the same claim may render the claim indefinite when the boundaries of the claim are not discernible. If stated in a single claim, examples and preferences lead to confusion over the intended scope of the claim. Therefore, the metes and bounds of the claim are not clearly set forth and are rendered indefinite. Regarding claim 1, the claim recites “wherein microbial species and microbial strains are in particular selected from Archaea, Bacteria, Eukaryote, Algae, Fungi, and small protists” and “in particular of the at least one microbial species and/or microbial strains, being present in the population biomass, in particular characterizing at least 70 wt. % of said population biomass, more in particular characterizing at least 85 wt. % of said population biomass, even more in particular characterizing at least 95 wt. % of said population biomass”. As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation wherein the population of the biome has at least one of a variety of microbial species and a variety of microbial strains wherein at least one of each microbial species and microbial strain individually provides at least one of a species biomass and strain biomass to the population and within the microbiome characterizing at least 50 wt. % of population biomass in terms of biological taxonomy. Regarding claim 3, the claim recites “in particular wherein said genetic sequence is selected from a DNA sequence, a RNA sequence, a gene sequence, an enzyme sequence, a part thereof, and a combination thereof”. As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation wherein the method is performed using a genetic sequence of a species and matching said genetic sequence with a genetic sequence-database comprising genetic sequence-data of possible microbial species Regarding claim 8, the claim recites “in particular selected from an Order level, a Family level, and a Genus level, a metabolic pathway present in at least one variety of species and strain” and “in particular an extracted protein sequence with the most linear quadratic estimate weight". As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation wherein step (2c2) merely requires at least one of protein sequences and peptides are selected which represent at least one characteristic selected from a high taxonomic level and step(2d) merely requires an amount of at least one most characterizing extracted protein sequence is determined. Regarding claim 9, the claim recites “in particular 2*101-106 different species, more in particular 102-105 different species”, “in particular 4-103 of the different species of the population (0.1-1%), more in particular 6-102 different species, such as 7-20 different species”, “in particular 103-104 of different protein sequences”, and “ in particular 102-103 of different peptide fragments”. As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation wherein in step (1) at least once an amplification technique is used, and wherein the population comprises 101-107 different species, the sub-population comprises 2-105 of the different species of the population (0.001-10%), wherein 102-108 of different protein sequences are extracted, and wherein 101-104 of different peptide fragments are formed. Regarding claim 10, the claim recites “in particular oxygen content”. As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation as mere trace elements. Regarding claim 16, the claim recites “in particular by comparing a last amount of extracted protein sequence with a first amount of extracted protein sequence”. As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation wherein step (2f) is merely comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence. Regarding claim 17, the claim recites “in particular for characterizing a microbial species”. As the metes and bounds of the claim are not clearly set forth, the Examiner will interpret the claim with its broadest reasonable interpretation of merely having a microbiome monitoring computer program comprising instructions for storing microbiome data. In the interest of compact prosecution, although these claims are given their broadest reasonable interpretation, if a piece of prior art discloses these additional limiting features, it will be noted below. 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 16-18 are non-statutory as they recite "a microbiome monitoring computer program". The claims as instantly recited read on carrier waves, which are transitory propagating signals and therefore are not proper patentable subject matter because they do not fit within any of the four statutory categories of invention (In re Nuijten, Federal Circuit, 2007). It is noted that the recitation of a "non-transitory computer readable medium" would overcome the rejection with respect to claim 1 reading on signals. However, the amendment to only "non-transitory computer readable medium" would not overcome the rejection under 35 U.S.C. 101 since the claims would still be directed to a judicial exception without significantly more (see below). Claims 1-18 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea and/or a natural phenomenon without significantly more. In accordance with MPEP 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature, or natural phenomenon (Step 2A, Prong 1). Claim 1 recites selecting a sub-population of the microbial species, determining a sub-set of at least one of protein sequences and peptides representing at least one of the sub-population and metabolic functions of the microbiome, at least one of directly and indirectly analysing the amounts of extracted at least one of protein sequences and peptides of the sub-set by comparing the sub-set against a database comprising at least one of protein sequences and peptides of the sub-set, and comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence. Claim 3 recites the method of monitoring a microbiome according to any of claim 2, wherein the characterization in step (1) is performed using a genetic sequence of a species and matching said genetic sequence with a genetic sequence-database comprising genetic sequence-data of possible microbial species, in particular wherein said genetic sequence is selected from a DNA sequence, a RNA sequence, a gene sequence, an enzyme sequence, a part thereof, and a combination thereof. Claim 8 recites wherein the step of (2c1) selecting a sub-population of the microbial species is performed only once, and wherein the step of (2c2) determining a sub-set of protein sequences representing the sub-population is performed only once, and wherein in step (2c2) at least one of protein sequences and peptides are selected which represent at least one characteristic selected from a high taxonomic level, in particular selected from an Order level, a Family level, and a Genus level, a metabolic pathway present in at least one variety of species and strains. Claim 16 recites (2f) comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence, in particular by comparing a last amount of extracted protein sequence with a first amount of extracted protein sequence. The limitations reciting selecting a sub-population of the microbial species; determining a sub-set of at least one of protein sequences and peptides representing at least one of the sub-population and metabolic functions of the microbiome; at least one of directly and indirectly analysing the amounts of extracted at least one of protein sequences and peptides of the sub-set by comparing the sub-set against a database comprising at least one of protein sequences and peptides of the sub-set; comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence; wherein the characterization in step (1) is performed using a genetic sequence of a species and matching said genetic sequence with a genetic sequence-database comprising genetic sequence-data of possible microbial species, in particular wherein said genetic sequence is selected from a DNA sequence, a RNA sequence, a gene sequence, an enzyme sequence, a part thereof, and a combination thereof; selecting a sub-population of the microbial species is performed only once, and wherein the step of (2c2) determining a sub-set of protein sequences representing the sub-population is performed only once, and wherein in step (2c2) at least one of protein sequences and peptides are selected which represent at least one characteristic selected from a high taxonomic level, in particular selected from an Order level, a Family level, and a Genus level, a metabolic pathway present in at least one variety of species and strains; and (2f) comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence, in particular by comparing a last amount of extracted protein sequence with a first amount of extracted protein sequence and fall under the “mental process” grouping of ideas. Selecting a sub-population, identification of relevant protein sequences and peptides from microbial data, comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence, and all limitations requiring comparative analysis all can be practically performed in the human mind or with a pen and paper and is therefore a mental process. The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 and Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016). As such, claims 1-18 recite abstract ideas. Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite additional elements that reflects an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment. Specifically, the claims recite the following additional elements: Claim 1 recites providing the microbiome, the microbiome comprising: a population having a population biomass, the population comprising at least one of a variety of microbial species and a variety of microbial strains wherein at least one of each microbial species and microbial strain individually provides at least one of a species biomass and strain biomass to the population, wherein microbial species and microbial strains are in particular selected from Archaea, Bacteria, Eukaryote, Algae, Fungi, and small protists; within the microbiome characterizing at least 50 wt.% of population biomass in terms of biological taxonomy, in particular of the at least one microbial species and microbial strains, being present in the population biomass, in particular characterizing at least 70 wt.% of said population biomass, more in particular characterizing at least 85 wt.% of said population biomass, even more in particular characterizing at least 95 wt.% of said population biomass; determining biomass per microbial species of the sub-population; at least one of directly and indirectly determining an amount of at least one extracted protein sequence. Claim 2 recites the method of monitoring a microbiome according to claim 1, wherein characterizing the microbial species in step (1) is a qualitative characterization. Claim 4 recites the method of monitoring a microbiome according to claim 1, wherein before (2d) determining an amount per extracted protein sequence, (2b) the extracted protein sequences of step (2a) are cleaved into peptide fragments. Claim 5 recites the method of monitoring a microbiome according to claim 4, wherein the extracted protein sequences of step (2a) are cleaved into peptide fragments each individually comprising 6-100 amino acids. Claim 6 recites the method of monitoring a microbiome according to claim 4, wherein cleavage is obtained by at least one specific protease. Claim 7 recites the method of monitoring a microbiome according to claim 5, wherein (2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry, and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins. Claim 8 recites the method of monitoring a microbiome according to claim 1, wherein the step of (1) characterizing at least 50 wt. % of the species being present in the population is performed only once, and in step (2d) determining an amount of at least one extracted protein sequence relates to at least one of a relative amount and an absolute amount, and wherein a relative amount is relative to one of an earlier determined amount and relative to an amount of at least one other protein sequence, and wherein in step (2d) an amount of at least one most abundant extracted protein sequence is determined, and wherein in step (2d) an amount of at least one most characterizing extracted protein sequence is determined, in particular an extracted protein sequence with the most linear quadratic estimate weight. Claim 9 recites the method of monitoring a microbiome according to claim 1, wherein the steps of (2a) at least two times extracting protein sequences from said population are performed as often as required for process control wherein in step (1) at least once an amplification technique is used, and wherein the population comprises 101-107 different species, in particular 2*101-106 different species, more in particular 102-105 different species, and wherein the sub-population comprises 2-105 of the different species of the population (0.001-10%), in particular 4-103 of the different species of the population (0.1-1%), more in particular 6-102 different species, such as 7-20 different species, and wherein 102-108 of different protein sequences are extracted, in particular 103-104 of different protein sequences, and wherein 101-104 of different peptide fragments are formed, in particular 102-103 of different peptide fragments, and wherein a calibration is provided, and wherein a protein and peptide database of the present microbiome is generated, and wherein a sub-set of the protein and peptide database of the present microbiome is created. Claim 10 recites the method of controlling a reactor comprising a microbiome, comprising monitoring a microbiome according to claim 1, and one of adapting at least one parameter selected from temperature, flow, pH, static residence time, solid retention time, nitrogen content, phosphorous content, amount of biomass, amount of nutrients, oxygen content, flow, alkalinity content, fatty acids content, redox values, feed flux, production installation of input sludge, method of production of input sludge, age of input sludge, organic carbon content COD of input sludge, method of production of input sludge, dosing of chemicals during production of input sludge, remaining concentration of dosing chemicals left, process setting during production of input sludge, polyelectrolyte concentration, type of polyelectrolyte, bowl speed, pressure applied to the sludge, gas produced, stir rate, ammonium concentration in an effluent stream, concentration of protein sequences, concentration of sugars, concentration of cellulosic material, amount of degradable organic matter, cation concentration, differential speed, trace elements, in particular oxygen content, or and not adapting a parameter, and stopping operation of the reactor. Claim 11 recites the method according to claim 10, wherein the reactor is selected from a digestion reactor, a continuous stirred tank reactor, a batch reactor, a repeated batch reactor, a sequence batch reactor, a single reactor with segmented sub-reactors, a plug flow reactor, a post-digestion reactor, a dewatering device, and combinations thereof. Claim 12 recites the method according to claim 10, wherein the reactor comprises a material selected from wastewater, food comprising a mixed microbial population, wine, a dairy product, a fermentation product, a digestion product, an enrichment product, and a microbial consortium product. Claim 13 recites the method according to claim 10, wherein monitoring is performed 1-168 per weeks. Claim 14 recites the method of determining an effect of at least one of a medicament, a drug, an purposive action, a change of habit, in an environment comprising a microbiome, comprising monitoring a microbiome according to claim 1, and adapting at least one of an amount of medication and an amount of drug, and adapting an administration regime of at least one medication and drug, and changing at least one of purposive action and habit. Claim 15 recites the method according to claim 14, wherein the microbiome is selected from mammal. Claim 16 recites a microbiome monitoring computer program comprising instructions for at least one of monitoring a microbiome according to claim 1 and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, the instruction causing the computer to carry out the following steps: (1) Within the microbiome characterizing at least 50% of the microbial species being present in the population, (2d) at least one of directly and indirectly determining an amount per extracted protein sequence. Claim 17 recites the microbiome monitoring computer program according to claim 16, further comprising instructions for storing microbiome data, in particular for characterizing a microbial species, a genetic sequence of said microbial species, a protein sequences produced or present of said microbial species, and at least one of a peptide fragment produced and presented of said microbial species. Claim 18 recites a microbiome monitoring computer program comprising instruction for at least one of monitoring a microbiome according to claim 1, and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, wherein the computer program comprises instructions for learning selected from machine learning, adaptive learning, and combinations thereof. The limitations reciting providing the microbiome, the microbiome comprising: a population having a population biomass, the population comprising at least one of a variety of microbial species and a variety of microbial strains wherein at least one of each microbial species and microbial strain individually provides at least one of a species biomass and strain biomass to the population, wherein microbial species and microbial strains are in particular selected from Archaea, Bacteria, Eukaryote, Algae, Fungi, and small protists; within the microbiome characterizing at least 50 wt.% of population biomass in terms of biological taxonomy, in particular of the at least one microbial species and microbial strains, being present in the population biomass, in particular characterizing at least 70 wt.% of said population biomass, more in particular characterizing at least 85 wt.% of said population biomass, even more in particular characterizing at least 95 wt.% of said population biomass; the method of monitoring a microbiome according to claim 1, wherein before (2d) determining an amount per extracted protein sequence, (2b) the extracted protein sequences of step (2a) are cleaved into peptide fragments; monitoring a microbiome according to claim 1, and one of adapting at least one parameter selected from temperature, flow, pH, static residence time, solid retention time, nitrogen content, phosphorous content, amount of biomass, amount of nutrients, oxygen content, flow, alkalinity content, fatty acids content, redox values, feed flux, production installation of input sludge, method of production of input sludge, age of input sludge, organic carbon content COD of input sludge, method of production of input sludge, dosing of chemicals during production of input sludge, remaining concentration of dosing chemicals left, process setting during production of input sludge, polyelectrolyte concentration, type of polyelectrolyte, bowl speed, pressure applied to the sludge, gas produced, stir rate, ammonium concentration in an effluent stream, concentration of protein sequences, concentration of sugars, concentration of cellulosic material, amount of degradable organic matter, cation concentration, differential speed, trace elements, in particular oxygen content, or and not adapting a parameter, and stopping operation of the reactor; recites the method of determining an effect of at least one of a medicament, a drug, an purposive action, a change of habit, in an environment comprising a microbiome, comprising monitoring a microbiome according to claim 1, and adapting at least one of an amount of medication and an amount of drug and adapting an administration regime of at least one medication and drug, and changing at least one of purposive action and habit; a microbiome monitoring computer program comprising instructions for at least one of monitoring a microbiome according to claim 1 and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, the instruction causing the computer to carry out the following steps: (1) Within the microbiome characterizing at least 50% of the microbial species being present in the population; a microbiome monitoring computer program comprising instruction for at least one of monitoring a microbiome according to claim 1, and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, wherein the computer program comprises instructions for learning selected from machine learning, adaptive learning, and combinations thereof merely limits the claimed judicial exceptions to the microbiome analysis technological environment and thus does not integrate into a practical application. The courts have ruled in Parker V. Flook, 437 U.S. 584, 198 USPQ 193 (1978) that limiting an abstract idea to a field of use or adding post solution components does not make the concept patentable. Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself and cannot integrate a judicial exception into a practical application. The limitations reciting determining biomass per microbial species of the sub-population; at least one of directly and indirectly determining an amount of at least one extracted protein sequence; the method of monitoring a microbiome according to claim 5, wherein (2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry, and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins; in step (2d) determining an amount of at least one extracted protein sequence relates to at least one of a relative amount and an absolute amount, and wherein a relative amount is relative to one of an earlier determined amount and relative to an amount of at least one other protein sequence, and wherein in step (2d) an amount of at least one most abundant extracted protein sequence is determined, and wherein in step (2d) an amount of at least one most characterizing extracted protein sequence is determined, in particular an extracted protein sequence with the most linear quadratic estimate weight; wherein the steps of (2a) at least two times extracting protein sequences from said population are performed as often as required for process control wherein in step (1) at least once an amplification technique is used, and wherein the population comprises 101-107 different species, in particular 2*101-106 different species, more in particular 102-105 different species, and wherein the sub-population comprises 2-105 of the different species of the population (0.001-10%), in particular 4-103 of the different species of the population (0.1-1%), more in particular 6-102 different species, such as 7-20 different species, and wherein 102-108 of different protein sequences are extracted, in particular 103-104 of different protein sequences, and wherein 101-104 of different peptide fragments are formed, in particular 102-103 of different peptide fragments, and wherein a calibration is provided, and wherein a protein and peptide database of the present microbiome is generated, and wherein a sub-set of the protein and peptide database of the present microbiome is created; (2d) at least one of directly and indirectly determining an amount per extracted protein sequence amounts to insignificant data gathering which does not integrate into a practical application. The limitations reciting the method of monitoring a microbiome according to claim 1, wherein characterizing the microbial species in step (1) is a qualitative characterization; the method of monitoring a microbiome according to claim 4, wherein the extracted protein sequences of step (2a) are cleaved into peptide fragments each individually comprising 6-100 amino acids; the method of monitoring a microbiome according to claim 4, wherein cleavage is obtained by at least one specific protease; the method according to claim 10, wherein the reactor is selected from a digestion reactor, a continuous stirred tank reactor, a batch reactor, a repeated batch reactor, a sequence batch reactor, a single reactor with segmented sub-reactors, a plug flow reactor, a post-digestion reactor, a dewatering device, and combinations thereof; the method according to claim 10, wherein the reactor comprises a material selected from wastewater, food comprising a mixed microbial population, wine, a dairy product, a fermentation product, a digestion product, an enrichment product, and a microbial consortium product; the method according to claim 10, wherein monitoring is performed 1-168 per weeks; the microbiome is selected from mammal; the microbiome monitoring computer program according to claim 16, further comprising instructions for storing microbiome data, in particular for characterizing a microbial species, a genetic sequence of said microbial species, a protein sequences produced or present of said microbial species, and at least one of a peptide fragment produced and presented of said microbial species; merely further limits the recited field-of-use limitation and does not integrate into a practical application. As such, claims 1-18 do not integrate the judicial exceptions into a practical application. Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic field-of-use and/or technological environment. The instant claims recite the following additional elements: Claim 1 recites providing the microbiome, the microbiome comprising: a population having a population biomass, the population comprising at least one of a variety of microbial species and a variety of microbial strains wherein at least one of each microbial species and microbial strain individually provides at least one of a species biomass and strain biomass to the population, wherein microbial species and microbial strains are in particular selected from Archaea, Bacteria, Eukaryote, Algae, Fungi, and small protists; within the microbiome characterizing at least 50 wt.% of population biomass in terms of biological taxonomy, in particular of the at least one microbial species and microbial strains, being present in the population biomass, in particular characterizing at least 70 wt.% of said population biomass, more in particular characterizing at least 85 wt.% of said population biomass, even more in particular characterizing at least 95 wt.% of said population biomass; determining biomass per microbial species of the sub-population; at least one of directly and indirectly determining an amount of at least one extracted protein sequence. Claim 2 recites the method of monitoring a microbiome according to claim 1, wherein characterizing the microbial species in step (1) is a qualitative characterization. Claim 4 recites the method of monitoring a microbiome according to claim 1, wherein before (2d) determining an amount per extracted protein sequence, (2b) the extracted protein sequences of step (2a) are cleaved into peptide fragments. Claim 5 recites the method of monitoring a microbiome according to claim 4, wherein the extracted protein sequences of step (2a) are cleaved into peptide fragments each individually comprising 6-100 amino acids. Claim 6 recites the method of monitoring a microbiome according to claim 4, wherein cleavage is obtained by at least one specific protease. Claim 7 recites the method of monitoring a microbiome according to claim 5, wherein (2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry, and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins. Claim 8 recites the method of monitoring a microbiome according to claim 1, wherein the step of (1) characterizing at least 50 wt. % of the species being present in the population is performed only once, and in step (2d) determining an amount of at least one extracted protein sequence relates to at least one of a relative amount and an absolute amount, and wherein a relative amount is relative to one of an earlier determined amount and relative to an amount of at least one other protein sequence, and wherein in step (2d) an amount of at least one most abundant extracted protein sequence is determined, and wherein in step (2d) an amount of at least one most characterizing extracted protein sequence is determined, in particular an extracted protein sequence with the most linear quadratic estimate weight. Claim 9 recites the method of monitoring a microbiome according to claim 1, wherein the steps of (2a) at least two times extracting protein sequences from said population are performed as often as required for process control wherein in step (1) at least once an amplification technique is used, and wherein the population comprises 101-107 different species, in particular 2*101-106 different species, more in particular 102-105 different species, and wherein the sub-population comprises 2-105 of the different species of the population (0.001-10%), in particular 4-103 of the different species of the population (0.1-1%), more in particular 6-102 different species, such as 7-20 different species, and wherein 102-108 of different protein sequences are extracted, in particular 103-104 of different protein sequences, and wherein 101-104 of different peptide fragments are formed, in particular 102-103 of different peptide fragments, and wherein a calibration is provided, and wherein a protein and peptide database of the present microbiome is generated, and wherein a sub-set of the protein and peptide database of the present microbiome is created. Claim 10 recites the method of controlling a reactor comprising a microbiome, comprising monitoring a microbiome according to claim 1, and one of adapting at least one parameter selected from temperature, flow, pH, static residence time, solid retention time, nitrogen content, phosphorous content, amount of biomass, amount of nutrients, oxygen content, flow, alkalinity content, fatty acids content, redox values, feed flux, production installation of input sludge, method of production of input sludge, age of input sludge, organic carbon content COD of input sludge, method of production of input sludge, dosing of chemicals during production of input sludge, remaining concentration of dosing chemicals left, process setting during production of input sludge, polyelectrolyte concentration, type of polyelectrolyte, bowl speed, pressure applied to the sludge, gas produced, stir rate, ammonium concentration in an effluent stream, concentration of protein sequences, concentration of sugars, concentration of cellulosic material, amount of degradable organic matter, cation concentration, differential speed, trace elements, in particular oxygen content, or and not adapting a parameter, and stopping operation of the reactor. Claim 11 recites the method according to claim 10, wherein the reactor is selected from a digestion reactor, a continuous stirred tank reactor, a batch reactor, a repeated batch reactor, a sequence batch reactor, a single reactor with segmented sub-reactors, a plug flow reactor, a post-digestion reactor, a dewatering device, and combinations thereof. Claim 12 recites the method according to claim 10, wherein the reactor comprises a material selected from wastewater, food comprising a mixed microbial population, wine, a dairy product, a fermentation product, a digestion product, an enrichment product, and a microbial consortium product. Claim 13 recites the method according to claim 10, wherein monitoring is performed 1-168 per weeks. Claim 14 recites the method of determining an effect of at least one of a medicament, a drug, an purposive action, a change of habit, in an environment comprising a microbiome, comprising monitoring a microbiome according to claim 1, and adapting at least one of an amount of medication and an amount of drug, and adapting an administration regime of at least one medication and drug, and changing at least one of purposive action and habit. Claim 15 recites the method according to claim 14, wherein the microbiome is selected from mammal. Claim 16 recites a microbiome monitoring computer program comprising instructions for at least one of monitoring a microbiome according to claim 1 and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, the instruction causing the computer to carry out the following steps: (1) Within the microbiome characterizing at least 50% of the microbial species being present in the population, (2d) at least one of directly and indirectly determining an amount per extracted protein sequence. Claim 17 recites the microbiome monitoring computer program according to claim 16, further comprising instructions for storing microbiome data, in particular for characterizing a microbial species, a genetic sequence of said microbial species, a protein sequences produced or present of said microbial species, and at least one of a peptide fragment produced and presented of said microbial species. Claim 18 recites a microbiome monitoring computer program comprising instruction for at least one of monitoring a microbiome according to claim 1, and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, wherein the computer program comprises instructions for learning selected from machine learning, adaptive learning, and combinations thereof. The limitations reciting a population having a population biomass, the population comprising at least one of a variety of microbial species and a variety of microbial strains wherein at least one of each microbial species and microbial strain individually provides at least one of a species biomass and strain biomass to the population, wherein microbial species and microbial strains are in particular selected from Archaea, Bacteria, Eukaryote, Algae, Fungi, and small protists; within the microbiome characterizing at least 50 wt.% of population biomass in terms of biological taxonomy, in particular of the at least one microbial species and microbial strains, being present in the population biomass, in particular characterizing at least 70 wt.% of said population biomass, more in particular characterizing at least 85 wt.% of said population biomass, even more in particular characterizing at least 95 wt.% of said population biomass; and determining biomass per microbial species of the sub-population; and characterizing the microbial species in step (1) is a qualitative characterization are considered conventional activities according to the National Academies of Sciences, Engineering, and Medicine (National Academies of Sciences, Engineering, and Medicine; Division on Earth and Life Studies; Board on Life Sciences; Board on Environmental Studies and Toxicology; Committee on Advancing Understanding of the Implications of Environmental-Chemical Interactions with the Human Microbiome. Environmental Chemicals, the Human Microbiome, and Health Risk: A Research Strategy. Washington (DC): National Academies Press (US); 2017 Dec 29; see page 49-50 where the common methods of microbiome analysis pipelines are disclosed). The limitations reciting the method of monitoring a microbiome according to claim 1, wherein before (2d) determining an amount per extracted protein sequence, (2b) the extracted protein sequences of step (2a) are cleaved into peptide fragments; wherein the extracted protein sequences of step (2a) are cleaved into peptide fragments each individually comprising 6-100 amino acids; wherein cleavage is obtained by at least one specific protease are well-understood, routine, and conventional activities as evidenced by Heissel (Heissel S, Frederiksen SJ, Bunkenborg J, Højrup P. Enhanced trypsin on a budget: Stabilization, purification and high-temperature application of inexpensive commercial trypsin for proteomics applications. PLoS One. 2019 Jun 27; trypsin is commercially available as described in “Abstract”; cleavage by trypsin primarily results in peptides with a length of 8–15 residues in “Introduction”). The limitations reciting wherein (2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry, and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins amounts to well-understood, routine, and conventional activities as evidenced by Xiong et al. (Xiong W, Abraham PE, Li Z, Pan C, Hettich RL. Microbial metaproteomics for characterizing the range of metabolic functions and activities of human gut microbiota. Proteomics. 2015 Oct;15(20):3424-38; see “Abstract” where it is explicitly stated that generally, microbial and human proteins can be extracted and then measured by high performance mass spectrometry (MS)-based proteomics technology). Additionally, the limitations reciting the method of monitoring a microbiome according to claim 5, wherein (2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry, and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins is a well-understood, routine, and conventional activity as evidenced by the Applicant’s specification on page 2 lines 15-20. The Examiner notes that although the applicant mentions that the spectrometry-based proteomics is time consuming, it nevertheless is common in the art. The limitations reciting the method of determining an effect of at least one of a medicament, a drug, an purposive action, a change of habit, in an environment comprising a microbiome, comprising monitoring a microbiome according to claim 1, and adapting at least one of an amount of medication and an amount of drug, and adapting an administration regime of at least one medication and drug, and changing at least one of purposive action and habit; the method according to claim 14, wherein the microbiome is selected from mammal are considered well-understood, routine, and conventional activities as evidenced by Weersma (Weersma RK, Zhernakova A, Fu J. Interaction between drugs and the gut microbiome. Gut. 2020 Aug; see “Abstract” on page 1510 where the study of the human gut microbiome is extensively described with adjustment on administrative regimen). The limitations reciting wherein the population comprises 101-107 different species, in particular 2*101-106 different species, more in particular 102-105 different species, and wherein the sub-population comprises 2-105 of the different species of the population (0.001-10%), in particular 4-103 of the different species of the population (0.1-1%), more in particular 6-102 different species, such as 7-20 different species, and wherein 102-108 of different protein sequences are extracted, in particular 103-104 of different protein sequences, and wherein 101-104 of different peptide fragments are formed, in particular 102-103 of different peptide fragments, and wherein a calibration is provided, and wherein a protein and peptide database of the present microbiome is generated, and wherein a sub-set of the protein and peptide database of the present microbiome is created amounts to well-understood, conventional, and routine activities as evidenced by Blanco-Míguez et al. (Blanco-Míguez A, Fdez-Riverola F, Lourenço A, Sánchez B. P4P: a peptidome-based strain-level genome comparison web tool. Nucleic Acids Res. 2017 Jul 3;45(W1):W265-W269; comparative peptide database is provided via an available web server and assesses similarities between microbial proteomes in “Abstract” on page W265). The limitations reciting the method of controlling a reactor comprising a microbiome, comprising monitoring a microbiome according to claim 1, and one of adapting at least one parameter selected from temperature, flow, pH, static residence time, solid retention time, nitrogen content, phosphorous content, amount of biomass, amount of nutrients, oxygen content, flow, alkalinity content, fatty acids content, redox values, feed flux, production installation of input sludge, method of production of input sludge, age of input sludge, organic carbon content COD of input sludge, method of production of input sludge, dosing of chemicals during production of input sludge, remaining concentration of dosing chemicals left, process setting during production of input sludge, polyelectrolyte concentration, type of polyelectrolyte, bowl speed, pressure applied to the sludge, gas produced, stir rate, ammonium concentration in an effluent stream, concentration of protein sequences, concentration of sugars, concentration of cellulosic material, amount of degradable organic matter, cation concentration, differential speed, trace elements, in particular oxygen content, or and not adapting a parameter, and stopping operation of the reactor; the method according to claim 10, wherein the reactor is selected from a digestion reactor, a continuous stirred tank reactor, a batch reactor, a repeated batch reactor, a sequence batch reactor, a single reactor with segmented sub-reactors, a plug flow reactor, a post-digestion reactor, a dewatering device, and combinations thereof; the method according to claim 10, wherein the reactor comprises a material selected from wastewater, food comprising a mixed microbial population, wine, a dairy product, a fermentation product, a digestion product, an enrichment product, and a microbial consortium product; and the method according to claim 10, wherein monitoring is performed 1-168 per weeks are considered well-understood, routine, and conventional activities as evidenced by Johnston et al. (Johnston J, LaPara T, Behrens S. Composition and Dynamics of the Activated Sludge Microbiome during Seasonal Nitrification Failure. Sci Rep. 2019 Mar 14;9(1):4565; see “Abstract” on page 1 for discussion of monitoring batch reactors over the course of a year; parameters measured found in Table S1 and temperature was explicitly controlled on page “4” in “Statstical Analysis”). The limitations reciting at least one of directly and indirectly determining an amount of at least one extracted protein sequence; in step (2d) determining an amount of at least one extracted protein sequence relates to at least one of a relative amount and an absolute amount, and wherein a relative amount is relative to one of an earlier determined amount and relative to an amount of at least one other protein sequence, and wherein in step (2d) an amount of at least one most abundant extracted protein sequence is determined, and wherein in step (2d) an amount of at least one most characterizing extracted protein sequence is determined, in particular an extracted protein sequence with the most linear quadratic estimate weight is a well-understood, routine, and conventional activity. As per MPEP 2106.05(d), the courts have ruled that analyzing DNA to provide sequence information or detect allelic variants is a conventional laboratory activity within the life science arts (see Genetic Techs. Ltd., 818 F.3d at 1377; 118 USPQ2d at 1546). The limitations reciting the method of monitoring a microbiome according to claim 1, wherein the steps of (2a) at least two times extracting protein sequences from said population are performed as often as required for process control wherein in step (1) at least once an amplification technique is used are well-understood, routine, and conventional activities. The courts have ruled detecting DNA or enzymes in a sample is a conventional laboratory activity within the life science arts (see Sequenom, 788 F.3d at 1377-78, 115 USPQ2d at 1157); Cleveland Clinic Foundation 859 F.3d at 1362, 123 USPQ2d at 1088 (Fed. Cir. 2017)). The limitations reciting further comprising instructions for storing microbiome data, in particular for characterizing a microbial species, a genetic sequence of said microbial species, a protein sequences produced or present of said microbial species, and at least one of a peptide fragment produced and presented of said microbial species; microbiome monitoring computer program comprising instructions for at least one of monitoring a microbiome according to claim 1 and for operating a reactor according claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, the instruction causing the computer to carry out the following steps: (1) Within the microbiome characterizing at least 50% of the microbial species being present in the population, (2d) at least one of directly and indirectly determining an amount per extracted protein sequence; and the computer program comprises instructions for learning selected from machine learning, adaptive learning, and combinations thereof; which amounts to well-understood, conventional, and routine activities. The courts have ruled that storing and retrieving information in memory is well-understood, routine, and conventional in the art (see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93). There are no additional elements that comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-18 are not patent eligible. 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. The present rejection(s) reference specific passages from cited prior art. However, Applicant is advised that the rejections are based on the entirety of each cited prior art. That is, each cited prior art reference “must be considered in its entirety”. (See MPEP 2141.02(VI)) Therefore, Applicant is advised to review all portions of the cited prior art if traversing a rejection based on the cited prior art. Claim 1, 2, 4, and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71). Regarding claim 1, Li teaches: A method of monitoring a microbiome (see “Results”; page 1; explicitly recited as an approach to measure absolute bacterial abundances and functionally profile the microbiome) comprising providing the microbiome (fresh human stool samples are inoculated; see page 2 in first paragraph of “Results”), the microbiome comprising: a population having a population biomass (pipeline contains a feature to assess microbiome biomass and analyze community structure; see page 2), the population comprising at least one of a variety of microbial species wherein at least one of each microbial species and microbial strain individually provides at least one of a species biomass and strain biomass to the population (pipeline utilizes an existing culture model with individual gut microbiomes in 96-well plates in first paragraph of “Results”; subsequent steps show that compounds were administered to see effects on individual microbiomes which includes, Bifidobacterium, Ruminococcus, Butyrivibrio, Paenibacillus, etc in paragraph 3 of “Effects of compounds on microbiome abundance and composition”; see also Fig. 2), wherein microbial species and microbial strains are in particular selected from Archaea, Bacteria, Eukaryote, Algae, Fungi, and small protists (see “Metaproteomics Data Analysis”; in the discussion of the methodology includes a taxonomic analysis of bacteria, eukaryote, viruses, and archaea in paragraph 2 of page 13), (1) within the microbiome characterizing at least 50 wt.% of population biomass in terms of biological taxonomy, in particular of the at least one microbial species and microbial strains, being present in the population biomass, in particular characterizing at least 70 wt.% of said population biomass, more in particular characterizing at least 85 wt.% of said population biomass (explicitly states metaproteomics has been previously validated to estimate the microbiome and individual microbe biomasses and it readily quantifies the bacterial species responsible for > 90% of the total microbiome biomass, making it sufficient for a fast-pass drug screening application; see page 2 in last paragraph of “Background”) (2a) at least two times extracting protein sequences from said population biomass, the two extractions forming a time sequence (a high throughput equal-volume based protein extraction and digestion workflow was applied to enable absolute bio mass assessment along with the functional profiling; see page 2 in last paragraph of “Background”), (2c1) selecting a sub-population of the microbial species, (2c2) determining a sub-set of at least one of protein sequences and peptides representing at least one of the sub-population and metabolic functions of the microbiome (2d) at least one of directly and indirectly determining an amount of at least one extracted protein sequence (Protein/peptide identification and quantification, taxonomic assignment, and functional annotations were done using the MetaLab software; see first paragraph of “Metaproteomics data analysis”). (2e) at least one of directly and indirectly analysing the amounts of extracted at least one of protein sequences and peptides of the sub-set by comparing the sub-set against a database comprising at least one of protein sequences and peptides of the sub-set (explicitly recites the inclusion of MetaLab where MetaLab is a software that automates an iterative database search strategy, i.e., MetaPro-IQ [29]. The search was based on a human gut microbial gene catalog containing 9,878,647 sequences from http://meta.genomics.cn/; mapping is later completed via the pep2tax database which is selected for mapping identified peptides to the taxonomic lineages on page 13 under “Metaproteomics data analysis”), and determining biomass per microbial species of the sub-population (Taxonomic biomass was quantified by summing the intensities of the peptides corresponding to each taxon under “Metaproteomics data analysis”), and (2f) comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence (explicitly states that after 24 h, the cultured microbiomes are prepared for metaproteomic analysis using a microplate-based metaproteomic sample processing workflow (Supplementary Figure S1) adapted from our single-tube protocol in “Results” on page 2 in paragraph 1). Of note, although Li does not teach the characterization step where the microbiome even more in particular characterizing at least 95 wt.% of said population biomass, he does explicitly teach that metaproteomics in the RapidAIM workflow readily quantifies the bacterial species responsible for > 90% of the total microbiome biomass. According to MPEP § 2144.05, the courts have ruled that a prima facie case of obviousness exists where the claimed ranges or amounts do not overlap with the prior art but are merely close. Titanium Metals Corp. of America v. Banner, 778 F.2d 775, 783, 227 USPQ 773, 779 (Fed. Cir. 1985). Thus, although Li does not explicitly teach the 95% wt.% of said population biomass, his disclosure is close enough so that the limitations of the instant claim are substantially met in view of the prior art. Furthermore, although Li does recognize that existing workflows include culturing individual bacteria strains isolated from microbiomes (see second paragraph of “Background” on page 2), Li does not explicitly teach that RapidAIM makes use of a variety of microbial strains, but rather provides the same general workflow onto microbiome species. Yan teaches that various types of amplicon and shotgun metagenomic sequencing can allow for detecting and quantifying different strains (see Table 1 on page 6 where various methods are described to allow for strain-specific microbiome analysis). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Yan’s strain-specific quantification into Li’s microbial biome analysis pipeline in order to provide greater fidelity to preserve amplicon biological variation when present (see “Strain identification from microbial community sequencing” on page 6). This incorporation could have been accomplished with reasonable excitation of success as Li has already developed his pipeline with the 16S rRNA gene fragment amplicons and shotgun metagenomics in mind despite not applying it in his pipeline (explicitly stated that genetic approaches such as sequencing of 16S rRNA gene fragment amplicons and shotgun metagenomics have been regarded as the “gold standard” in microbiome analysis, providing relative quantifications of microbiome composition and functional capabilities in third paragraph on page 2). Regarding claim 2, Li as modified teaches: The method of monitoring a microbiome according to claim 1, wherein characterizing the microbial species in step (1) is a qualitative characterization (along with quantifying the abundance of microbiomes, mass spectroscopy-based proteomics also can estimate functional activities of the microbiome; see page 2). Regarding claim 4, Li as modified teaches: The method of monitoring a microbiome according to claim 1, wherein before (2d) determining an amount per extracted protein sequence (2b) the extracted protein sequences of step (2a) are cleaved into peptide fragments (peptide cleaving included in the workflow as tryptic digestion and is explicitly recited as “the microplate-based workflow consists of bacterial cell purification, cell lysis with ultrasonication in 8 M urea buffer, in-solution tryptic digestion, and desalting”; see “Results” on page 2). Regarding claim 6, Li as modified teaches: The method of monitoring a microbiome according to claim 4, wherein cleavage is obtained by at least one specific protease (peptide cleaving included in the workflow as tryptic digestion and is explicitly recited as “the microplate-based workflow consists of bacterial cell purification, cell lysis with ultrasonication in 8 M urea buffer, in-solution tryptic digestion, and desalting”; see “Results” on page 2). Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71) as evidenced by Komar (The "periodic table" of the genetic code: A new way to look at the code and the decoding process.). Regarding claim 3, Li as modified teaches: Li as modified teaches the method of monitoring a microbiome according to any of claim 2, wherein the characterization in step (1) is performed using a genetic sequence of a species and matching said genetic sequence with a genetic sequence-database comprising genetic sequence-data of possible microbial species, in particular wherein said genetic sequence is selected from a DNA sequence, a RNA sequence, a gene sequence, an enzyme sequence, a part thereof, and a combination thereof (Taxonomic identification was achieved by assigning peptide se quences to lineage of lowest common ancestor (LCA). The “peptide to taxonomy” database (pep2tax database) was selected for mapping identified peptides to the taxo nomic lineages; see second paragraph of “Metaproteomics data analysis” on page 13). The Examiner notes that although peptide sequences are used, it is possible to translate peptide sequences back into a possible DNA/RNA sequence using a codon table as evidenced by Komar (see Fig.1 on page 2 with references to the codon table). Claims 5 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71), as applied in claim 1, further in view of Heissel et al. (Enhanced trypsin on a budget: Stabilization, purification and high-temperature application of inexpensive commercial trypsin for proteomics applications. PLoS One. 2019 Jun 27;14(6):e0218374.). Regarding claim 5, Li as modified teaches the claimed invention substantially as claimed above. Although Li as modified does generically recite trypsin digestion in his pipeline, the method of monitoring a microbiome according to claim 4, wherein the extracted protein sequences of step (2a) are cleaved into peptide fragments each individually comprising 6-100 amino acids. Heissel teaches that tryptic digestions primarily results in peptides with a length of 8-15 residues (see “Introduction” for explicit recitation on page 1). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Heissel’s tryptic digestion method into Li as modified’s existing pipeline in order to apply a known technique to a known method ready for improvement to yield predictable results (see “Abstract” where trypsin is known as the most commonly used and commercially available protease in proteomics on page 1). This incorporation could have been accomplished with reasonable expectation of success as Li as modified’s workflow already includes a tryptic digestion step (peptide cleaving included in the workflow as tryptic digestion and is explicitly recited as “the microplate-based workflow consists of bacterial cell purification, cell lysis with ultrasonication in 8 M urea buffer, in-solution tryptic digestion, and desalting”; see “Results” on page 2). Regarding claim 7, Li as modified teaches: The method of monitoring a microbiome according to claim 5, wherein (2d) determining an amount of protein sequence directly is performed using high resolution mass spectrometry (LC-MS/MS analysis is performed after the digestion step and described in page 3), and wherein (2d) determining an amount of protein sequence indirectly is performed using high resolution mass spectrometry on at least one of peptides and proteins (LC-MS/MS analysis is performed after the digestion step and described in page 3; also see note on 112b rejection and subsequent claim interpretation above). Regarding claim 8, Li as modified teaches: The method of monitoring a microbiome according to claim 1, wherein the step of (1) characterizing at least 50 wt. % of the species being present in the population is performed only once (explicitly states metaproteomics has been previously validated to estimate the microbiome and individual microbe biomasses and it readily quantifies the bacterial species responsible for > 90% of the total microbiome biomass, making it sufficient for a fast-pass drug screening application; see page 2 in last paragraph of “Background”), and wherein the step of (2c1) selecting a sub-population of the microbial species is performed only once (Protein/peptide identification and quantification, taxonomic assignment, and functional annotations were done using the MetaLab software; see first paragraph of “Metaproteomics data analysis”), and wherein the step of (2c2) determining a sub-set of protein sequences representing the sub-population is performed only once (Protein/peptide identification and quantification, taxonomic assignment, and functional annotations were done using the MetaLab software; see first paragraph of “Metaproteomics data analysis”), and wherein in step (2c2) at least one of protein sequences and peptides are selected which represent at least one characteristic selected from a high taxonomic level, in particular selected from an Order level, a Family level, and a Genus level, a metabolic pathway present in at least one variety of species and strains (see “Specific proteins and enzymatic pathways in response to compounds” on page 7; explicitly recited as Protein groups were annotated to KEGG (Kyoto Encyclopedia of Genes and Genomes) enzymes and were mapped against the KEGG pathway database; additionally, RapidAIM measures the effect on compounds on many bacterial genera at the genus and species level in paragraph 3 of “Effects of compounds on microbiome abundance and composition” on page 4), and in step (2d) determining an amount of at least one extracted protein sequence relates to at least one of a relative amount and an absolute amount (absolute amount explicitly disclosed as an estimate of all peptide intensities for each taxon on page 4 in paragraph 3 of “Effects of compounds on microbiome abundance and composition”), and wherein a relative amount is relative to one of an earlier determined amount and relative to an amount of at least one other protein sequence (see notes on “Claim Interpretation” on contingent limitations), and wherein in step (2d) an amount of at least one most abundant extracted protein sequence is determined (LC-MS/MS analysis provides abundance data which is used within the pipeline; see “Background” on page 2), and wherein in step (2d) an amount of at least one most characterizing extracted protein sequence is determined, in particular an extracted protein sequence with the most linear quadratic estimate weight (see also notes on regarding the “most characterizing” and “in particular” claim interpretations under 112(b) rejections; LC-MS/MS analysis provides protein data which is used within the pipeline; see “Background” on page 2). Claims 5 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71), as applied in claim 1, further in view of Heissel et al. (Enhanced trypsin on a budget: Stabilization, purification and high-temperature application of inexpensive commercial trypsin for proteomics applications. PLoS One. 2019 Jun 27;14(6):e0218374.), further in view of Kleiner et al. (Assessing species biomass contributions in microbial communities via metaproteomics. Nat Commun 8, 1558 (2017)). Regarding claim 9, Li as modified teaches the claimed invention substantially as claimed above. He does not teach the subsequent steps of protein extraction, amplification, calibration, and database generation. Kleiner teaches the method of monitoring a microbiome according to claim 1, wherein the steps of (2a) at least two times extracting protein sequences from said population are performed as often as required for process control (see Fig. 5 for 2x protein extraction over 260 minutes and 460 minutes (process control)), and wherein in step (1) at least once an amplification technique is used (16S rRNA gene amplicon-based quantification disclosed throughout pipeline; see paragraphs 1-2 of “Metaproteomics is more accurate for biomass estimates than sequencing methods” on page 5), and wherein the population comprises 101-107 different species (see “Metaproteomics enables accurate species-level quantification” on page 5 where 32 species and strains are explicitly recited), in particular 2*101-106 different species, more in particular 102-105 different species (for the following “in particulars”, see the 112(b) rejections and the broadest reasonable interpretation above), and wherein the sub-population comprises 2-105 of the different species of the population (0.001-10%) (see Fig. 3 which discloses different community selections and each were comprised of different ratios of 28-32 strains), in particular 4-103 of the different species of the population (0.1-1%), more in particular 6-102 different species, such as 7-20 different species, and wherein 102-108 of different protein sequences are extracted (pipeline operated with community database of extracted proteins throughout in “Protein identification” and “Data availability” on page 12; for example, 123,100 protein sequences exist in the final database), in particular 103-104 of different protein sequences, and wherein a calibration is provided (normalization provided within the Supplementary Data 1 and described in “Metaproteomics enables accurate species-level quantification” on page 5 in paragraph 3), and wherein a protein and peptide database of the present microbiome is generated (see Supplementary Table 8 for the database generated), and wherein a sub-set of the protein and peptide database of the present microbiome is created (see “Data availability” on page 12 for final database via the PRIDE partner repository). Of note, although tryptic digests are disclosed within the sample preparation pipeline (see “Sample preparations for proteomics”), Kleiner does not explicitly disclose wherein 101-104 of different peptide fragments are formed in particular 102-103 of different peptide fragments. However, as aforementioned by Heissel, the average peptide fragment retrieved from tryptic digestion is 8-15 residues (see “Introduction” for explicit recitation on page 1). By virtue of inherency, introducing a tryptic digestion pipeline prior to the 123,100 protein sequence final database would mean that the amount of tryptic fragments would have to fall in between the disclosed range. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kleiner’s microbiome database composition into Li as modified’s existing microbiome analysis pipeline in order to optimize the accuracy and sensitivity of existing methods and add a dimension of analysis to microbial community structure (see “Abstract” on page 1). The incorporation could have been accomplished with reasonable expectation of success as both operate in the same field of endeavor of microbiome analysis. Claims 10, 12, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71), as applied in claim 1, further in view of Herold et al. (Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nat Commun 11, 5281 (2020)). Regarding claim 10, Li as modified teaches the method of controlling a reactor comprising a microbiome, comprising monitoring a microbiome according to claim 1 (see rejection on claim 1). Li does not teach one of adapting at least one parameter selected from temperature, flow, pH, static residence time, solid retention time, nitrogen content, phosphorous content, amount of biomass, amount of nutrients, oxygen content, flow, alkalinity content, fatty acids content, redox values, feed flux, production installation of input sludge, method of production of input sludge, age of input sludge, organic carbon content COD of input sludge, method of production of input sludge, dosing of chemicals during production of input sludge, remaining concentration of dosing chemicals left, process setting during production of input sludge, polyelectrolyte concentration, type of polyelectrolyte, bowl speed, pressure applied to the sludge, gas produced, stir rate, ammonium concentration in an effluent stream, concentration of protein sequences, concentration of sugars, concentration of cellulosic material, amount of degradable organic matter, cation concentration, differential speed, trace elements, in particular oxygen content, and not adapting a parameter, and stopping operation of the reactor. Herold teaches a microbial community analysis method involves assessing the response of individual oleaginous populations to oleic acid addition under shifting dissolved oxygen concentrations (see paragraph 3 on page 2 where it is explicitly recited; also see note on broadest reasonable interpretation and contingent claims in “Claim Interpretation” as the non-adaptation and stopping limitation is not required if a parameter is selected). Therefore, it would have been obvious before the effective filing date of the claimed invention to incorporate Herold’s shifting parameter step into Li as modified’s existing analysis pipeline in order to reveal how microbial ecosystems respond to disturbance and provide more informed ecological engineering (see paragraph 3 on page 2). This incorporation would have been accomplished with reasonable expectation of success as both operate in the same field of endeavor of microbial ecosystem analysis (see page 1). Regarding claim 12, Herold teaches: The method according to claim 10, wherein the reactor comprises a material selected from wastewater, a food comprising a mixed microbial population, wine, a dairy product, a fermentation product, a digestion product, of an enrichment product, and a microbial consortium product (the entire disclosure is directed to analyzing microbial populations from a biological wastewater treatment plant; see “Abstract” on page 1). The Examiner notes that under the broadest reasonable interpretation, the claim recites “a material selected from…” which means that only one of the elements needs to be present for the claim to be rendered obvious in view of the prior art. Regarding claim 13, Herold teaches: The method according to claim 10, wherein monitoring is performed 1-168 times per week (see “Results”; explicitly stated as sampled a municipal BWWTP weekly over a 14-months period). Claims 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71), as applied in claim 1, further in view of Herold et al. (Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nat Commun 11, 5281 (2020)) further in view of Belizário et al. (Belizário, José E., Faintuch, Joel, Garay-Malpartida, Miguel, Gut Microbiome Dysbiosis and Immunometabolism: New Frontiers for Treatment of Metabolic Diseases, Mediators of Inflammation, 2018, 2037838, 12 pages, 2018.). Regarding claim 14, Li as modified teaches: The method of determining an effect of at least one of a medicament, a drug, an purposive action, or a change of habit, in an environment comprising a microbiome (explicitly states that RapidAIM was used with 43 compounds and 5 individual gut biomes and monitored microbiome responses; see page 2), comprising monitoring a microbiome according to claim 1 (see rejection on claim 1). Li as modified does not teach adapting at least one of an amount of medication and an amount of drug, and adapting an administration regime of at least one of medication and drug, and changing at least one of purposive action and habit. Belizario teaches the administration of oral dietary supplementation as one form of treatment to produce various physiological effects (see last paragraph of “5. Gut Dysbiosis Associated with Metabolic Diseases” on page 5 for discoveries of different forms of treatment for gut microbiota; see also “6. Targeting Gut Microbiota Dysbiosis and Metabolic Pathways” on page 6 where there are different types of treatment meant to produce different responses such as probiotics modulating negative effects of high-fat diets and oral supplements stimulating insulin signaling to reduce adiposity). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Belizario’s various treatment methods into Li as modified’s microbiome analysis pipeline in order to reduce the inflammation driving from gut microbiota-derived products (see “Abstract”). This incorporation could have been accomplished with reasonable expectation of success as both operate in the field of endeavor of microbiome analysis. Regarding claim 15, Li as modified teaches: The method according to claim 14, wherein the microbiome is selected from a mammal (fresh human stool samples are inoculated; see page 2 in first paragraph of “Results”). Regarding claim 16, Li as modified teaches: A microbiome monitoring computer program (Li’s pipeline is implemented on software/computer-implemented as seen in Fig. 1) comprising instructions for at least one of monitoring a microbiome according to claim 1, and for operating a reactor according to claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, the instructions causing the computer to carry out the following steps: (1) within the microbiome characterizing at least 50% of the microbial species being present in the population (explicitly states metaproteomics has been previously validated to estimate the microbiome and individual microbe biomasses and it readily quantifies the bacterial species responsible for > 90% of the total microbiome biomass, making it sufficient for a fast-pass drug screening application; see page 2 in last paragraph of “Background”), (2d) at least one of directly and indirectly determining an amount per extracted protein sequence (Protein/peptide identification and quantification, taxonomic assignment, and functional annotations were done using the MetaLab software; see first paragraph of “Metaproteomics data analysis”), and (2f) comparing in the time sequence a later amount of extracted protein sequence with an earlier amount of protein sequence, in particular by comparing a last amount of extracted protein sequence with a first amount of extracted protein sequence (explicitly states that after 24 h, the cultured microbiomes are prepared for metaproteomic analysis using a microplate-based metaproteomic sample processing workflow (Supplementary Figure S1) adapted from our single-tube protocol in “Results” on page 2 in paragraph 1). Regarding claim 17, Li as modified teaches: The microbiome monitoring computer program according to claim 16, further comprising instructions for storing microbiome data, in particular for characterizing a microbial species, a genetic sequence of said microbial species, a protein sequence produced or present of said microbial species, and at least one of a peptide fragment produced and present of said microbial species (a high throughput equal-volume based protein extraction and digestion workflow was applied to enable absolute bio mass assessment along with the functional profiling; see page 2 in last paragraph of “Background”; additionally,; see also Komar for raw sequence translation). Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71), as applied in claim 1, further in view of Herold et al. (Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nat Commun 11, 5281 (2020)), further in view of Bonnet (Bioreactor-Compare decontamination technologies- Guidance and orientation for the selection of technologies-Contaminated sites-Pollution and waste management-Environment and natural resources). Regarding claim 11, Li as modified teaches: Li as modified by Herold teaches the claimed invention substantially as claimed above. Although Herold does mention that his entire disclosure is directed towards a bioreactor (see “Ex Situ experiments” on page; where it is explicitly recited that the ex situ experiments were performed in bioreactors seeded with sludge samples on page 11-12), he does not teach the method according to claim 10, wherein the reactor is selected from a digestion reactor, a continuous stirred tank reactor, a batch reactor, a repeated batch reactor, a sequence batch reactor, a single reactor with segmented sub-reactors, a plug flow reactor, a post-digestion reactor, a dewatering device, and combinations thereof. However, Bonnet teaches that biomass resulting from the process can be clarified and returned to the system or accumulated as sludge for disposal (see “Implementation of the technology” on page 2-3). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Bonnet’s alternatives of bioreactors into Li as modified by Herold’s existing microbial analysis pipeline in order to provide an alterative to existing configurations and to meet various criteria (e.g. mobilization, pumping contaminated groundwater, etc) (see “Implementation of the technology” on page 2-3). This incorporation would have been accomplished with reasonable expectation of success as Herold already includes a bioreactor in his pipeline. The Examiner notes that under the broadest reasonable interpretation, the claim recites “the reactor is selected from a …” which means that only one of the elements needs to be present for the claim to be rendered obvious in view of the prior art. Claims 18 is rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (RapidAIM: A culture- and metaproteomics-based rapid assay of individual microbiome responses to drugs. Microbiome, 8(1)) in view of Yan et al. (Strain-level epidemiology of microbial communities and the human microbiome. Genome Med. 2020 Aug 13;12(1):71), as applied in claim 1, further in view of Herold et al. (Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nat Commun 11, 5281 (2020)), and further in view of Topçuoğlu et al. (A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems. mBio. 2020 Jun 9;11(3):e00434-20). Regarding claim 18, Li as modified teaches the claimed invention substantially as claimed above. Li as modified does not explicitly teach a microbiome monitoring computer program comprising instructions for at least one of monitoring a microbiome according to claim 1, and for operating a reactor according to claim 10, and for determining an effect of at least one of a medicament and drug in an environment comprising a microbiome according to claim 14, wherein the computer program comprises instructions for learning selected from machine learning, adaptive learning, and combinations thereof. Topçuoğlu teaches a method implementing machine learning into microbiome analysis pipelines (see “Abstract” on page 1). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Topçuoğlu’s machine learning algorithms into Li as modified’s pipeline in order to identify microbial biomarkers and aid in the diagnosis of many diseases (see “Abstract” on page 1). This incorporation would have been accomplished with reasonable expectation of success as both operate in the same field of endeavor. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to PETER NGUYEN whose telephone number is (571)272-0127. The examiner can normally be reached Monday - Friday 7:30am - 5:00pm. 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 M. Wise can be reached at (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 published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /P.N./Examiner, Art Unit 1685 /OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685