CN112204139A

CN112204139A - General method for extracting nucleic acid molecules from different populations of one or more types of microorganisms in a sample

Info

Publication number: CN112204139A
Application number: CN201980036347.2A
Authority: CN
Inventors: S·杰恩
Original assignee: Sun Genomics Inc
Current assignee: Sun Genomics Inc
Priority date: 2018-04-02
Filing date: 2019-04-02
Publication date: 2021-01-08
Also published as: WO2019195342A1; IL277682A; AU2019247693A1; JP2021520191A; KR20200140303A; GB2587545B; CA3095745A1; GB2587545A; SG11202009744WA; EP3775197A1; GB202017361D0; JP2024063020A

Abstract

Disclosed herein are methods of extracting genetic material from different populations of one or more types of microorganisms in a sample. The microorganism may be a prokaryote or eukaryote and may include bacteria, archaea, fungi, protozoa, helminths, parasites, viruses, bacteriophages and the like. Extraction can be performed from a single sample, and subsequent identification can be performed by molecular methods (such as qPCR, PCR, RFLP, SSCP, allele-specific PCR, targeted sequencing, pull-down sequencing, whole shotgun sequencing), or other methods. Also provided are methods comprising extracting nucleic acid molecules from various organisms such as fungi (i.e., saccharomyces), animal cells (bovine), plants (e.g., barley) from the gut of a human subject, performing a metagenomic analysis therefrom, and determining probiotic treatment or dietary guidance for the subject based on the metagenomic analysis.

Description

General method for extracting nucleic acid molecules from different populations of one or more types of microorganisms in a sample

Cross Reference to Related Applications

The present application claims benefit of U.S. application serial No. 62/651,620 filed on 2018, 4/2/35/s.c. § 119 (e). The disclosure of this prior application is considered part of the disclosure of the present application and is incorporated by reference into the disclosure of the present application.

Technical Field

The present invention relates generally to genomic analysis and more particularly to a method of extracting and analyzing food-associated nucleic acid molecules from different populations of microorganisms in a biological sample.

Background

About 100 trillion microorganisms live in and on the human body, far exceeding about 10 trillion individual somatic cells of the human body. These generally harmless viruses, bacteria and fungi are called commensals or symbionts. Commensal and symbiont organisms help our body to maintain health in many ways. All microorganisms living in and on the body, commensal, symbiotic and pathogenic, are collectively referred to as the microbiome, and their balance and associated metabolic groups are closely related to the health status of an individual, and vice versa.

Advances in nucleic acid sequencing have created an opportunity to quickly and accurately identify and profile the microbiome residing in intestinal and subcutaneous tissues. The optimal flora also interacts in a synergistic manner with the host immune system, further spreading its health benefits. The associated metabolome of an individual can also be summarized by mass spectrometry based systems or using genomics based metabolome modeling and flux balance analysis, and used to make a healthy metabolome profile. All of these methods can be used to profile the complexity of a microbial community.

Disclosure of Invention

The present invention relates to a method for extracting nucleic acid molecules from different microbial populations in a sample of a heterogeneous population of biological, environmental, dietary supplements or other ecological microbial organisms, and the use of the nucleic acids or extracts for determining probiotic customization in an individual by processing steps and analysis. The special processing steps of the invention comprise: clearing, fragmenting, isolating or digesting RNA or DNA; library or nucleic acid preparation for downstream applications, such as PCR, qPCR, digital PCR, or sequencing; pre-processing for bioinformatics QC, filtering, alignment, or data separation; a metagenomics or human genome bioinformatics process for classification assignment of microbial species; and other organisms, alignment, identification and variation interpretation.

The invention also describes a general method for using samples for DNA extraction and for determining food consumption based on food DNA sequences in a database of meat, plants, fruits, vegetables and/or microorganisms from these organisms. Disclosed herein are methods of extracting genetic material from different populations of one or more types of cells or cellular components in a sample and determining food consumed and nutrient breakdown to improve health and prevent disease.

Accordingly, in one aspect, the present invention provides a method for preparing a sample for analysis. The method comprises the following steps: a) mixing the sample with a first lysis solution comprising a detergent (e.g. SDS) and a chelating agent (e.g. EDTA); b) adding a second lysis solution with lysozyme to the mixture of step a); and c) adding a third lysis solution comprising a chaotropic agent (e.g., urea, lithium acetate, guanidine hydrochloride, etc.) to the mixture of step b). The pretreatment step may include physical lysis that may be used to further optimize nucleic acid yield. Examples of mechanical lysis include sonication, bead mixing and bead mill homogenization.

In a similar aspect, the method comprises: a) mixing a sample (such as a stool sample) with a liquid nitrogen solution; b) adding a first lysis solution comprising a detergent and a chelating agent (e.g., SDS), and a chelating agent (e.g., EDTA); and c) adding a second lysis solution comprising a chaotropic agent, such as urea, lithium acetate, guanidine hydrochloride. The pretreatment step may include physical lysis that may be used to further optimize nucleic acid yield. Examples of mechanical lysis include sonication, bead mixing and bead mill homogenization.

In another aspect, the invention provides a method of determining food consumption of a subject. The method comprises the following steps: a) extracting genetic material from a stool sample obtained from a subject, the genetic material extracted according to the methods of the present disclosure; and b) performing a metagenomics analysis of the genetic material extracted from the first sample to determine the food consumption of the subject. In embodiments, the method further comprises treating the subject with a probiotic or a food based on the analysis of food consumption.

In another aspect, the invention provides a method of monitoring probiotic treatment in a subject. The method comprises the following steps: a) extracting genetic material from any microorganisms present in a first sample obtained from a subject, the genetic material being extracted according to the methods of the present disclosure; b) performing a metagenomics analysis of genetic material extracted from the first sample; c) treating the subject with a probiotic and then extracting genetic material from any microorganisms present in a second sample obtained from the subject in the same manner as the genetic material is extracted from the first sample; d) performing a metagenomics analysis of genetic material extracted from the second sample; and e) comparing the results of the metagenomic analysis of the first sample with the results of the metagenomic analysis of the second sample.

In yet another aspect, the present invention provides a method comprising calculating a probiotic score based on probiotic organisms detected in the gut, with or without additional chemical or genetic testing.

In yet another aspect, the invention provides a method comprising calculating a score for a microbiome, the score being used to assess whether the microbiome is in a dysbiosis, neutral, or stable state.

The present invention further provides a computing system comprising: a memory; and one or more processors coupled to the memory, the one or more processors configured to perform operations to perform the methods of the present invention.

The invention also provides an automated platform for performing the method of the invention.

The present invention provides an integrated method for extracting nucleic acids from different microbial populations of a heterogeneous population of biological, environmental, dietary supplements or other ecological microbial organisms.

In embodiments, the present invention can be used to determine the composition and relative abundance of microorganisms by analyzing the nucleic acids of each of the microorganisms in the probiotic and environmental samples. The DNA is purified and used for downstream nucleic acid analysis (particularly for metagenomic analysis, where more than one species/subspecies of the genome is identified).

Both the foregoing general description and the following detailed description are exemplary and explanatory only and are intended to provide further explanation of the invention as claimed. The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate several embodiments of the invention and together with the description serve to explain the principles of the invention.

Drawings

Figure 1 is a schematic diagram illustrating the presence of highly prevalent organisms of the microbiome signature of humans (> 50 years old, supplement users).

Figure 2A is a schematic diagram illustrating the presence of highly prevalent organisms (bacteria) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years old, vegetarian diet).

FIG. 2B is a schematic diagram illustrating the presence of highly prevalent organisms (viruses and phages) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years of age, vegetarian diet).

Figure 2C is a schematic diagram illustrating the presence of highly prevalent organisms (archaea) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years old, vegetarian diet).

Figure 2D is a schematic diagram illustrating the presence of highly prevalent organisms (fungi and other eukaryotes) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years old, vegetarian diet).

Figure 3A is a schematic diagram illustrating the presence of highly prevalent organisms (bacteria) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years old, non-vegetarian diet).

Figure 3B is a schematic diagram illustrating the presence of highly prevalent organisms (viruses and phages) characteristic of microbiome (high carbohydrate diet, 18-50 years old, non-vegetarian diet) in humans.

Figure 3C is a schematic diagram illustrating the presence of highly prevalent organisms (archaea) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years old, non-vegetarian diet).

Figure 3D is a schematic diagram illustrating the presence of highly prevalent organisms (fungi and other eukaryotes) characteristic of the microbiome of humans (high carbohydrate diet, 18-50 years old, non-vegetarian diet).

Figure 4A is a schematic diagram illustrating the presence of highly prevalent organisms (bacteria) characteristic of microbiome (high milk protein diet, 0-2 years old, vegetarian non-lactating) in humans.

Figure 4B is a schematic diagram illustrating the presence of highly prevalent organisms (viruses and phages) characteristic of microbiome of humans (high milk protein diet, 0-2 years of age, vegetarian non-lactating).

Figure 4C is a schematic diagram illustrating the presence of highly prevalent organisms (archaea) characteristic of microbiome (high milk protein diet, 0-2 years old, vegetarian non-lactating) in humans.

Figure 4D is a schematic diagram illustrating the presence of highly prevalent organisms (fungi and other eukaryotes) characteristic of the microbiome of humans (high milk protein diet, 0-2 years old, vegetarian non-lactating).

FIG. 5 is a schematic illustrating the presence of less prevalent organisms and the identification of opportunistic pathogens characteristic of the microbiome of humans.

Fig. 6 is a schematic diagram illustrating typical probiotics detected in the microbiome signature of humans.

Fig. 7 is a schematic diagram illustrating typical probiotics detected in the microbiome signature of humans.

Fig. 8 is a schematic diagram illustrating the comparison of individual relative abundances of a normal population to database averages.

FIG. 9 is a table illustrating organisms identified from cultures of dietary supplement mixes by the methods of the present invention.

FIG. 10 is a table illustrating the classification of unique species of various microorganisms stored in the database of the present invention.

FIG. 11 illustrates exemplary demographic information from an individual in one embodiment of the present invention.

FIG. 12 illustrates exemplary organisms detected in one embodiment of the invention that are associated with seafood.

FIG. 13 illustrates exemplary organisms associated with mammalian meat detected in one embodiment of the present invention.

FIG. 14 illustrates exemplary organisms associated with grain detected in one embodiment of the invention.

Detailed Description

The present invention provides a general method for extracting nucleic acid molecules from different populations of one or more types of microorganisms in a sample. Types of microorganisms include: gram-positive bacteria, gram-positive bacterial spores, gram-negative bacteria, archaea, protozoa, worms, algae, fungi, fungal spores, viruses, viroids, bacteriophages and rotifers. In some embodiments, the different populations are a plurality of different microorganisms of the same type, such as gram positive bacteria. In some embodiments, the different populations are a plurality of different types of microorganisms, such as bacteria (gram positive bacteria, gram positive bacterial spores, and/or gram negative), fungi, viruses, and bacteriophages.

Because different types of microorganisms have different compositions and mechanisms to protect their own genetic material, it is often difficult to extract genetic material from one type of microorganism without compromising the ability to extract the genetic material of another type of microorganism in the same biological sample. However, the present invention allows the extraction of genetic material from different types of microorganisms in a sample without sacrificing the amount of genetic material that can be obtained from one type of microorganism by extracting the genetic material of another type of microorganism in the same sample. According to the present invention, the sample comprising the microorganism may be a biological sample, an environmental sample, an artificially produced sample (e.g., a laboratory test or control sample, a sample of a probiotic composition or supplement, etc.), and the like. Examples of biological samples include tissue samples, blood samples, plasma samples, cerebrospinal fluid samples, urine samples, stool samples, samples of substances obtained from the alimentary tract, biological secretions (e.g., semen, vaginal secretions, breast milk, tears, saliva, etc.), and so forth. The solid sample may be liquefied or mixed with a solution, and then the genetic material of the microorganism present in the liquefied sample, mixture or solution obtained from the mixture may be extracted according to the invention. The extracted genetic material may be subjected to further processing and analysis, such as purification, amplification and sequencing.

In some embodiments, a metagenomic analysis is performed on the extracted genetic material, for example, to identify one or more types of microorganisms in the sample from which the genetic material was extracted. In further embodiments, whole genome shotgun sequencing may be performed on extracted nucleic acid material prepared from human stool samples. Preparation involves nucleic acid cleaning reactions to remove organic solvents, impurities, salts, phenols and other process inhibiting contaminants. Additional preparation includes preparing a nucleic acid library from each sample, wherein the gDNA undergoes modification and/or amplification to prepare the sample for sequencing on a sequencing platform, such as massively parallel sequencing by synthesis, nanopore, long read, and/or CMOS electronic sequencing methods.

As disclosed herein, the methods of the present invention allow for the successful extraction of genetic material from one or more different types of microorganisms present in the same sample by subjecting the microorganisms to three different compositions in a particular order. The method according to the invention comprises first lysing any gram-negative bacteria present in the sample, followed by digesting the polysaccharide component of the cell walls of any yeast and bacteria present in the sample, and then disrupting any cell walls intact after the second step with a chaotropic agent.

Briefly, in one embodiment, the first step comprises contacting the sample with a reagent comprising a detergent (e.g., Sodium Dodecyl Sulfate (SDS)) and a chelating agent(e.g., ethylenediaminetetraacetic acid (EDTA)) to lyse any gram-negative bacteria present in the sample. The first lysis solution may further comprise one or more buffers (e.g., Tris), one or more mild detergents (e.g., Triton @)^TMX-100) and/or one or more proteases (e.g. proteinase K).

After the first step, the sample is mixed with a second lysis solution comprising lysozyme to digest any polysaccharide components of the yeast and bacterial cell walls present in the mixture. Since lysozyme may inhibit the activity of the first lysis solution, it is important that the contacting of the sample with the second lysis solution occurs after the sample is treated with the first lysis solution.

After treatment with the second lysis solution, a third lysis solution comprising a chaotropic agent (e.g., urea, lithium acetate, guanidine hydrochloride, etc.) is added to the mixture to disrupt any cell walls not digested by the second lysis solution. The third lysis solution may comprise a detergent, such as SDS.

In some embodiments, both the first lysis solution and the third lysis solution comprise SDS at a working concentration between 1-10% w/v. In some embodiments, after treatment with the third lysis solution, the mixture is further treated with a fourth lysis solution comprising a chaotropic agent (e.g., urea, lithium acetate, guanidine hydrochloride, etc.) and proteinase K. In some embodiments where the chaotropic agent of the third lysis solution is lithium acetate, the mixture is then subjected to a thermal shock treatment, and may then be treated with a fourth lysis solution.

In certain aspects, the following disclosure describes a general method for DNA extraction using stool samples and determining food consumption based on food DNA sequences from a database of meats, plants, fruits, vegetables, and/or microorganisms contained in these organisms. Disclosed herein are methods of extracting genetic material from different populations of one or more types of cells or cellular components in a sample and determining food consumed and nutrient breakdown to improve health and prevent disease.

In some embodiments, the biological secretions (e.g., semen, vaginal secretions, breast milk, tears, saliva, blood, urine, etc.) are obtained from the alimentary tract or the like. The solid sample may be liquefied or mixed with a solution, and the liquefied sample, mixture, or any food-based genetic material, such as plant-based (seedlings, leaves, cotyledons, seeds, endosperm, tissue culture callus, roots, etc.), animal-based, fungal-based, or protist-based food in the solution obtained from the mixture, may then be extracted according to the present invention or other standard nucleic acid extraction protocols known in the art. In some embodiments, the extracted genetic material may be subjected to further processing and analysis, such as purification, amplification and sequencing. In some embodiments, a metagenomic analysis is performed on the extracted genetic material, for example, to identify one or more types of organisms in the sample from which the genetic material was extracted.

In some embodiments, the database that the metagenomic analysis will utilize has been tailored for a particular purpose, i.e., in appropriate phylogeny, to identify and classify nucleic acids that partition the relative abundance of an organism or a component of an organism ingested by a human or other animal. In some embodiments, and additional data tables or databases may be used as a lookup of the relative abundance of an organism to determine the macronutrient content of an intestinal sample of the organism as representative of its diet. In some embodiments, this breakdown of macronutrients may include fats, carbohydrates, proteins, vitamins, minerals, and any sub-components of macronutrients.

As disclosed herein, the methods of the invention allow for the successful extraction of genetic material from one or more different types of organisms, cells of one or more organisms, or cell matrices or organelles present in the same sample by isolating, purifying, or other methods for capturing nucleic acids from the sample. The method according to the invention comprises lysing or disrupting any food cells (including but not limited to any cell wall and cell membrane) in the sample, digesting any cell wall or cell membrane polysaccharide or lignin component of any fungal, plant, mammalian or protist cell present in the sample, and disrupting any cell wall intact after the digestion step with a chaotropic agent.

The present invention includes the steps of physically disrupting the cell walls or membranes of food cells by rapid freezing with liquid nitrogen and immediate mechanical disruption or grinding to disrupt the cell walls and keep harmful cellular enzymes inactive prior to chemical lysis. The invention includes the step of mixing the sample with a first lysis solution comprising a detergent, such as Sodium Dodecyl Sulfate (SDS), and a chelating agent, such as ethylenediaminetetraacetic acid (EDTA), to lyse any animal cells present in the sample. The first lysis solution may further comprise one or more buffers (e.g., Tris), one or more mild detergents (e.g., Triton @)^TMX-100, cetyltrimethylammonium bromide) and/or one or more proteases (e.g., proteinase K). In particular embodiments, the first lysis solution comprises SDS at a working concentration of 1-10% w/v. The present invention includes the step of mixing the sample with a second lysis solution comprising a chaotropic agent (e.g., urea, lithium acetate, guanidine hydrochloride, etc.). The second lysis solution may comprise a detergent, such as SDS. In certain exemplary embodiments, the first lysis solution and the second lysis solution may be added in any particular order.

In some embodiments, the invention may include the step of mixing the sample with a third lysis solution comprising lysozyme to digest any polysaccharide component of the fungal or bacterial cell walls present in the mixture. In some embodiments, the mixture may be further treated with a fourth lysis solution comprising a chaotropic agent (e.g., urea, lithium acetate, guanidine hydrochloride, etc.) and proteinase K. In some embodiments where the chaotropic agent of the fourth lysis solution is lithium acetate, the mixture may then be subjected to a thermal shock treatment, and may then be treated with the fourth lysis solution. In certain exemplary embodiments, the third solution and/or the fourth solution may be added to the mixture at any point to disrupt any cell walls that were not digested by any previous lysis solution.

In some embodiments, if the sample has or is suspected of having bacterial and/or fungal spores, the sample may be subjected to a pretreatment step that induces cell wall germination of the spores prior to contact with the first lysis solution. The pre-treatment step may comprise mixing the sample with a chemical such as a mild detergent (e.g. tween 80) to induce germination or incubating the sample under conditions (e.g. temperature) to induce germination. In some embodiments, wherein germination is induced with a chemical, the chemical is preferably one that does not inhibit, reduce, or alter the activity or effectiveness of the first lysis solution, the second lysis solution, and the third lysis solution.

In some embodiments, the method according to the present invention may further comprise one or more mechanical processing steps that cause physical lysis by mechanical methods (including sonication, bead mixing, bead mill homogenization, pressurization, microfluidization, and the like). In some embodiments, the mechanical processing step is performed prior to subjecting the sample to the first lysis solution.

In an embodiment, the method according to the invention enables the extraction of nucleic acid molecules from a variety of microorganisms including yeasts (i.e., certain species of the genus Saccharomyces), gram-negative bacteria (e.g., certain species of the genus Acinetobacter), gram-positive bacteria (e.g., certain species of the genus Bifidobacterium), viruses (e.g., certain species of the genus Sclerotinia), spores (certain species of the genus Bacillus), worms (certain species of the genus Echinococcus), protozoa phyla (Dermatophaga-proteobacteria, e.g., Entamoeba), and bacteriophages (e.g., lactic bacteriophages).

In an embodiment, the method according to the invention enables the extraction of nucleic acid molecules from a variety of organisms including fungi (i.e., certain species of Saccharomyces), animal cells (Bos taurus), plants (e.g., barley).

The following examples are intended to illustrate, but not to limit, the present invention.

Extraction method A

Samples ranging from 10mg to 5000mg were added to sterile 2 milliliter (mL) microcentrifuge tubes. Optionally, the beads may be slurried by adding 400 microliters (μ L) of the pure bead mixture and vortexing at 8000rpm for about 30 seconds. However, if it is desired to obtain high molecular weight nucleic acids, e.g., genomic DNA, bead beating is preferably avoided.

First lysis solution treatment step

In order to lyse any of the sampleGram-negative bacteria were prepared by adding approximately 400. mu.L of digestion buffer (1% w/v SDS, 25mM Tris HCl, 2.5mM EDTA, 1% Triton) to the sample^TMX-100, pH 8) and about 20 μ L proteinase K, the sample was subjected to the first lysis solution and gently mixed. The mixture was then incubated at 55 ℃ for about 30 minutes.

Second lysis solution treatment step

To lyse any gram positive bacteria in the sample, a second lysis solution comprising a glucoside hydrolase ("lysozyme") was added to the mixture obtained from the first lysis solution treatment step to give a final lysozyme concentration of 1mg/mL and a pH of about 8.0. Suitable glucoside hydrolyzing enzymes may be obtained from a variety of sources, including egg white, tears of various animals, or mucus or saliva. The mixture is then incubated at 37 ℃ for a period of about 1 to 24 hours.

Third lysis solution treatment step

To lyse any fungal and/or yeast cells present in the sample, sterile H is added, which is contained in the distillation₂A third lysis solution of 1M lithium acetate and 5% w/v SDS in O to obtain about a 1:5 dilution of the mixture resulting from the second lysis solution treatment step. The treated mixture was incubated at 70 ℃ for 15 minutes, followed by heat shock at 95 ℃ for 1 minute, and then brought to room temperature by placing into a water bath at 22 ℃.

Since the second and third lysis solution treatment steps are sufficient to lyse the coat of phages and viruses, no additional steps are required to extract genetic material from phages and viruses that may be present in the sample.

Extraction method B

Pretreatment step for cracking

100-200mg of the sample was added to a sterile 2 mL (mL) microcentrifuge tube. 500mL of liquid nitrogen was added and the samples were allowed to freeze for 30 seconds. The sample is then ground thoroughly using a particle pestle or saw tooth generator probe before proceeding to the next step.

First lysis solution treatment step

In order to lyse the sampleBy adding about 400. mu.L of digestion buffer (1% w/v SDS, 25mM Tris HCl, 2.5mM EDTA, 1% Triton) to the sample^TMX-100, 1.2M NaCl pH 8) and about 20 μ L proteinase K, the sample was subjected to the first lysis solution and gently mixed. The mixture was then incubated at 55 ℃ for about 30 minutes.

Second lysis solution treatment step

To lyse any fungal and/or yeast cells present in the sample, sterile H is added, which is contained in the distillation₂A second lysis solution of 1M lithium acetate and 5% w/v SDS in O to obtain about a 1:5 dilution of the mixture resulting from the first lysis solution treatment step. The treated mixture was incubated at 70 ℃ for 15 minutes, followed by heat shock at 95 ℃ for 1 minute, and then brought to room temperature by placing into a water bath at 22 ℃.

Nucleic acid purification

In one embodiment, the genetic material extracted from the lysed microorganisms, i.e., the nucleic acid molecules present in the mixture after being subjected to the first, second, and third lysis solution treatment steps, is then purified into DNA and RNA purification by dividing the mixture into two microcentrifuge tubes. DNA was extracted from one tube by adding about 20. mu.L of RNase A and incubating at room temperature for 5 minutes. The mixture was passed through a biopolymer tissue homogenizer column. If the beads are previously slurried, it is preferred to avoid subjecting the mixture to a tissue homogenizer column.

The eluate was then centrifuged at 1000g for 5 minutes. The supernatant was treated with about 400. mu.L of DNA lysis solution (guanidine hydrochloride, Tris-EDTA and 70% EtOH) and about 20. mu.L of proteinase K, mixed and then incubated at 55 ℃ for 10 minutes. EtOH at-22 ℃ was then added and the mixture was mixed by inversion. The mixture may be subjected to one or more additional DNA extraction and purification methods known in the art.

RNA was extracted from the second microcentrifuge tube by passing the mixture through a biopolymer tissue homogenizer column. Also, if the beads are beaten previously, it is preferable to avoidThe mixture was not subjected to a tissue homogenizer column. The eluate was then centrifuged at 1000g for 5 minutes. Supernatant was applied to 25mM MgCl₂About 40. mu.L of DNase I (1U) in the solution of (1) and then incubated at 37 ℃ for about 15 minutes. The mixture was then subjected to acidic guanidinium thiocyanate-phenol-chloroform extraction. The mixture may be subjected to one or more additional RNA extraction and purification methods known in the art.

In one embodiment, the genetic material extracted from the lysed microorganism, i.e. the nucleic acid molecules present in the mixture after being subjected to the first, second and pre-lysis treatment steps, is then purified into DNA and RNA purification by dividing the mixture into two microcentrifuge tubes. DNA was extracted from one tube by adding about 20L of RNase and incubating at room temperature for 5 minutes.

RNA was extracted from the second microcentrifuge tube. The eluate was then centrifuged at 1000g for 5 minutes. Supernatant was applied to 25mM MgCl₂About 40. mu.L of DNase I (1U) in the solution of (1) and then incubated at 37 ℃ for about 15 minutes. The mixture was then subjected to acidic guanidinium thiocyanate-phenol-chloroform extraction. The mixture may be subjected to one or more additional RNA extraction and purification methods known in the art.

In some embodiments where quantitative expression of RNA molecules is desired, it is preferred to use RNA stabilization buffers and bead beating to ensure release and limited degradation of RNA nucleic acid molecules.

In some embodiments where extraction of high molecular weight nucleic acid molecules is desired, bead beating and homogenization columns are avoided, and a phenol-chloroform-ethanol extraction is performed instead of a silica gel column-based extraction. In some embodiments, magnetic bead-based nucleic acid purification can be performed. In order to remove the selective molecular weight of nucleic acids and purify the sample, agarose gel based purification and enrichment may be performed.

Macrogenomics analysis

In one embodiment, the extracted and purified genetic material is prepared for sequencing using the Illumina indexing adaptor and checked for size and quantity. For any input of less than 50ng of DNA, low-cycle PCR is performed between 1-20 cycles, otherwise, for 50ng or more of nucleic acid, a PCR-free library preparation method can be used. Gel Purification Using Qiagen Gel Purification Kit^TM(Qiagen, Frederick, MD). Using qubits^TMClean PCR products were quantified with a fluorometer (Life Technologies, Carlsbad, Calif.). The samples were mixed in equimolar amounts. Library pool Using Fragment Analyzer^TMCE (Advanced Analytical Technologies Inc., Ames IA) was subjected to size verification and using a Qubit^TMQuantification was performed with a high sensitivity dsDNA kit (Life Technologies, Carlsbad, CA). After dilution, PhiX^TMThe 1% to 10% spike of the V3 library control (Illumina, San Diego CA) was denatured in an equal volume of 0.1N NaOH for 5 minutes, then further diluted in Illumina HT1 buffer. Will be denatured and carry PhiX^TMPool of spikes loaded into Illumina Next Generation with Illumina sequencing primers^TMOn a sequencer and set to 50-550 bases, paired ends or single reads.

Reads from the 1000 or greater range for sequencing of the short insertion method can be used for this method. Large insertion methods such as Pac Bio^TM、Nanopore^TMOr other next gene sequencing method can be used<1000 sequencing reads. Bioinformatic quality filtering is performed prior to classification assignment. Quality trimming of the original sequencing file may include removing sequencing adapters or indices; based on the quality score (Q20)>) Terminal base pairing or signal intensity to trim the 3 'or 5' end of the read; removing reads based on mass scores, GC content, or misaligned base pairs; overlapping reads were removed over a fixed number of base pairs. The processed sequencing files were aligned using a custom microbial genome database from refseq^TM、Greengeens^TM、HMP^TM、NCBI^TM、PATRIC^TMOr other public/private data stores or sequences of internal data sets. This database can be used as a whole genome alignment scaffold, k-mer fragment alignment or other protocols practiced in the fields of metagenomics and bioinformatics. Based on the number of sequencing reads/fragments that match the database genome, we assigned a taxonomic identifier common or unique to the organisms. This identifier may be a barcode, a nucleotide sequence, or some other computational tag that associates a matching sequencing read with an organism or strain in the taxonomic group. Some identifiers will have a higher rank and will identify a domain, kingdom, phylum, class, order, family or genus of an organism.

The present invention enables identification of organisms at the lowest strain level in a species.

In an embodiment, the invention comprises the identification and/or analysis of one or more bacteria contained in our database (fig. 10). Some examples of choices are strains of Bacillus clausii, Bifidobacterium animalis, Pediococcus acidilactici, Acinetobacter indiani, Lactobacillus salivarius, Acinetobacter, Bacillus amyloliquefaciens, Lactobacillus helveticus, Bacillus subtilis, Lactobacillus plantarum, Bifidobacterium longum subsp.

In an embodiment, the invention comprises the identification and/or analysis of one or more yeasts contained in our database (fig. 10). Examples of some choices are Saccharomyces, Saccharomyces boulardii, Saccharomyces kurariavzkii (Saccharomyces kudriavzevii), Saccharomyces pastorianus (Saccharomyces pastorianus), and Saccharomyces cerevisiae.

In an embodiment, the invention comprises the identification and/or analysis of one or more bacteriophages or viruses contained in our database (fig. 10). Some examples of selections are the bacillus phage phi29, the enterobacter phage HK022, the lactobacillus phage a2, the escherichia phage HK639, the phage cdtI, the sclerotinia split virus S segment 2, the burkholderia phage BcepMu, the lactococcus prophage bIL311, the enterococcus phage phiFL4A, and the streptococcal phage SM 1.

Future database improvements will increase or improve the organisms that can be detected by this method.

In one embodiment, the extracted and purified genetic material is prepared for sequencing using the Illumina indexing adaptor and checked for size and quantity. Low cycle PCR or standard PCR-free methods can be performed. Gel Purification Using Qiagen Gel Purification Kit^TM(Qiagen, Frederick, MD). Using qubits^TMClean PCR products were quantified with a fluorometer (Life Technologies, Carlsbad, Calif.). The samples were mixed in equimolar amounts. Library pool Using Fragment Analyzer^TMCE (Advanced Analytical Technologies Inc., Ames IA) was subjected to size verification and using a Qubit^TMQuantification was performed with a high sensitivity dsDNA kit (Life Technologies, Carlsbad, CA). After dilution, PhiX^TMThe 10% spike of the V3 library control (Illumina, San Diego CA) was denatured in an equal volume of 0.1N NaOH for 5 minutes, followed by further dilution in Illumina HT1 buffer. Will be denatured and carry PhiX^TMPool of spikes loaded into Illumina with Illumina sequencing primers^TMNext generation sequencer, and set to 150 bases, paired end reads. Bioinformatic quality filtering is performed prior to classification assignment.

Using table 1, we determined that the individual has consumed the following:

TABLE 1

Monitoring macronutrient intake and dietary guidance

In some embodiments, the invention can be used to monitor food intake nutrition, quantity, and quality of a subject. For example, prior to treatment with probiotics, a sample obtained from the digestive tract of a subject can be obtained and the genetic material of the food organism therein extracted as disclosed herein and subjected to a macro-genomics analysis. Customized food-specific databases consisting of complete, partial, or incomplete reference genomic, RNA, or nucleic acid components or fragments will be utilized by bioinformatics tools to identify, quantify, and categorically distribute nucleic acid information from sequencing. The output of which is illustrated in table 2 below and contains the species of organism or the identification of the cells of the organism in the gut.

TABLE 2

Then, during and/or after treatment with a given probiotic, a second sample may be obtained from the digestive tract of the subject, and the genetic material of the microorganisms in the second sample is extracted and subjected to a macro-genomic analysis, the results of which are compared to the results of the macro-genomic analysis of the first sample. Then, based on the comparison results, the food organism results can be compared to the microbiome organism results to learn the microorganisms associated with the food and the overall food quality assessment. In some embodiments, this may provide information to the species of organism: the individual is ingesting through its food source and through selection or direct modification of any genetic modification, mutation or irregularity of that species.

In some embodiments, the second sample of the microbiome analysis will be capable of detecting microorganisms common to food organisms and providing information about the health of the food organisms. In some embodiments, the food consumed by humans may be part of a common food source, such as chickens, cattle, pigs, or even plants and protists, where species will be identified and matched to their specific microorganisms. In certain exemplary embodiments, chicken species that may have a chicken sarcoma virus can be detected in the analyzed second gut microbiome sample. In some embodiments, the health of the ingested food organism may be determined by the presence or absence of microorganisms that negatively impact the health of the host organism. In certain exemplary embodiments, a disease that may affect the health of the host organism, such as equine herpes virus 2, which is a respiratory disease in horses, may be detected.

In some embodiments, the present invention can be used to screen the gut microbiome of a given subject and then tailor a food or dietary regimen that enables them to improve their quality of health with respect to nutritional balance, improved gut profile of microorganisms, and absorption of nutrients.

Monitoring probiotic treatment

In some embodiments, the present invention may be used to monitor probiotic treatment of a subject. For example, prior to treatment with probiotics, a sample obtained from the digestive tract of a subject can be obtained and the genetic material of the microorganisms therein extracted and subjected to a macro-genomic analysis as disclosed herein. Then, during and/or after treatment with a given probiotic, a second sample may be obtained from the digestive tract of the subject and the genetic material of the microorganisms in the second sample is extracted as disclosed herein and subjected to a macrogenomic analysis, the results of which are compared to the results of the macrogenomic analysis of the first sample. Then, based on the comparison results, the probiotic treatment of the subject may be modified to obtain the desired population of microorganisms in the intestinal tract of the subject. For example, a probiotic comprising a microorganism whose amount is desired to be increased in the intestinal tract of a subject may be administered to the subject.

In some embodiments, fecal samples can be mixed or cultured for determination of metabolomics of microbial fecal communities. The metabolomics profile can then be used to determine the probiotic strain that will benefit the individual. Examples of metabolomic profiles include those that affect energy metabolism, nutrient utilization, insulin resistance, obesity, dyslipidemia, inflammation, short chain fatty acids, organic acids, cytokines, neurotransmitter chemicals or phenotypes, and may include other metabolomic markers.

Microbiome screening and probiotic selection

The present invention has been successfully used to determine the microbial content of various commercially available probiotics. Furthermore, the method of the invention is used to determine the microbiome content of various probiotics and the microbiome content in the intestinal tract of a subject. In one embodiment, based on the microbiome content in the intestinal tract of the subject and any desired changes thereof, one or more probiotics containing microorganisms that are desired to be increased and/or maintained in the microbiome health of the subject may be selected. In one embodiment, based on the microbiome content in the intestinal tract of the subject and any desired changes thereof, one or more probiotics can be selected that contain microorganisms that are desired to be increased and/or maintained in the intestinal balance of the subject in relation to their macronutrient content obtained from their food source, as recorded directly from survey information from the individual or as recorded by the intestinal biont nucleic acid analysis of the invention.

Wherein the microbiome represents a complete image of their microbiota and organisms contained therein from bacteria, fungi, viruses, bacteriophages and parasites. For example, using the methods described herein, the subject's gut microbiome was determined to contain 25% a and 75% B, probiotic 1 was determined to contain 75% a and 25% B, and probiotic 2 was determined to contain 25% a and 75% B. If the subject's gut microbiome is desired to be maintained, probiotic 2 may be selected for administration to the subject. However, if the amount of a and B in the intestinal tract of the subject is desired to be 50/50, then both

probiotics

1 and 2 may be selected for administration to the subject. Alternatively, probiotic 1 may be selected for administration to the subject until the amount of a and B in the intestinal tract of the subject reaches 50/50. In some embodiments, the probiotic formulation may be customized, e.g., containing the same, varying, or different amounts of a and B or other probiotic bacterial strains, for administration to a subject. Using a computational model of the relative abundance of microorganisms present in the gut of an individual will help determine the type, dosage and mixture of microorganisms to include in the probiotic. For example, if it is determined that organism a is reduced or absent compared to the general population or previous microbiome analysis, we will provide a probiotic or prebiotic that will increase the concentration of organism a. This prebiotic or probiotic may be the exact organism a or another organism that will support the growth of organism a. A given dose will take into account the relative abundance of the organism, the performance characteristics of the prebiotic/probiotic, such as growth rate, compatibility, receptor or receptor density, gene or expression pattern, or metabolite in the individual.

The amounts of customized probiotics may not be equal, but are formulated based on the relative abundance detected from the individual gut/stool samples. These formulations are suitable for regulating the microbiome to a healthy state. The health status of the microbiome is determined by using existing aggregate private and public databases (such as metaHIT)^TM、Human Microbiome Project^TM、American Gut Project^TMEtc.). From the blood biomarker examination perspective, when a person has no known problems and is in good health, the health status can also be determined individually and their full microbiome profile then completed. After one or several microbiome features have been completed, the average of some/all of the individual's findings can then be learned and the differences in the average can be obtained to determine whether they are in an dysbiosis state. The microbiome profiles may be aggregated into groups, which are then assigned barcodes for rapid bioinformatics assignment. Groups may be created by single or multiple phenotypic, diagnostic, or demographic information relating to the individual from which the sample was collected. A unique group can be determined from another group by using statistical models such as linear distance calculations, diversity values, classifiers such as C4.5 decision trees, or principal component analysis, and comparing with an aggregated known population such as "normal persons" as defined by the human microbiome plan or the us gut plan.

Thus, in some embodiments, the present invention may be used to screen the gut microbiome of a given subject and then tailor a probiotic regimen for the given subject based on the gut microbiome of the subject.

Treatment of dysbiosis

In some embodiments, the present invention may be used to restore the subject's intestinal flora and/or fauna to homeostasis after an event that has caused a shift in the subject's microbiota from a balanced microbiome to one that leads to or may cause negative side effects, disorders, and/or diseases. Health conditions may include, but are not limited to, a variety of conditions, from acne and allergies, to gastrointestinal diseases, obesity, and cancer. One example of such dysbiosis is the case of the onset of obesity. Strains of several microorganisms in the intestinal tract of a subject have been shown to be associated with obesity or weight management problems suffered by the subject. See, for example, Ley, et al (2005) PNAS USA 102: 11070-. For example, in obese animal and human subjects, the ratio of bacteroidetes (bacillides) to Firmicutes (phyla) microorganisms plays an important role in metabolic performance. See, e.g., Turnbaugh, et al (2012) PLOS ONE 7: e 41079. Some of the gut microorganisms known to be associated with obesity and weight management problems include bacteroides monomorphus, bacteroides pectophilus, gluconobacter oxydans, brevibacterium smith, and bifidobacterium animalis.

Thus, in some embodiments, the ratio of a first given microorganism to a second given microorganism in the gut of a subject is determined using the methods described herein, and then if the ratio is undesirable or abnormal, the subject administers a treatment to change the ratio to the desired ratio. In some embodiments, the method described herein is used to determine the amount of a first given microorganism in the gut of a subject relative to the total amount of all microorganisms in the gut of a subject, and then if the relative amount of the first given microorganism is undesirable or abnormal, the subject administers a treatment to change that amount to a desired amount. Retesting of their gut microbiome can be used to determine whether they are well compliant with macronutrients and food guidelines. Such treatment comprises administering to the subject: probiotics containing one or more microorganisms of which the amount is desired to be increased in the intestinal tract of a subject, antimicrobial agents, such as antibiotics, antifungal agents, antiviral agents, and the like (to kill or slow the growth of one or more microorganisms of which the amount is desired to be reduced in the intestinal tract of a subject), dietary and/or dietary supplements that support the growth or maintenance of a healthy gut microbiome, such as prebiotics, magnesium, fish oil, L-glutamine, vitamin D, and the like. For example, Million, et al ((2005) int.J.Obes.36:817-825) indicate that the intestinal microbiota of obese subjects is enriched in Lactobacillus reuteri, and depleted in Bifidobacterium animalis and Brevibacterium smini smith. Thus, after determining the amount of lactobacillus reuteri, bifidobacterium animalis and brevibacterium smini in the gut of a subject using the methods described herein and finding that the amount is typical or indicative of the gut microbiota associated with obesity, the subject may be administered a probiotic containing bifidobacterium animalis and brevibacterium smini and relatively little to no lactobacillus reuteri. In embodiments, the gut microbiota of an obese subject will benefit from a food containing flavonoids, polyphenols and short chain fatty acids.

Scoring of your microbiome

Scoring of microbiome features generally uses similar decision trees, algorithms, artificial intelligence, scripts, or logic trees as shown in table 3. The system will be able to provide a score that helps users understand the health of their gut microbiome and whether they need to take action on some or many of the challenges found. Challenges may include, but are not limited to: identification of known pathogenic organisms, enumeration and identification of opportunistic pathogens, latent organisms known to cause pathogenic effects at a given opportunity, lack of support for a good microbial environment or lack of critical strains in addition to their composition, unique organisms found in the top 10, and/or overall diversity and enumeration of organisms with prevalence greater than 0.1%.

A diversity cutoff is determined from the set of sample analyses, and the cutoff is determined at the x relative abundance. For example, if x is 0.1%, then 352 unique organisms constitute an average health profile. Then applying the standard deviation around this number and using the gaussian distribution and percentile under curve analysis, we can derive the closeness to the average diversity number from our database mean. The lower and further away from the mean your diversity figure, the lower the microbiome score. The higher the number and the greater your diversity, the higher the microbiome score. This type of scoring category, as well as probiotic scores, will determine numerical and visual metric scores for custom understanding the health of their microbiome. Examples of graphical visualizations include the following. Wherein low equals low microbiome mass and high equals high microbiome mass and score. 30 in low- >100, 65 in medium- >100, 65 in high-100 or higher.

Examples of scoring and probiotic formulation algorithms are included in table 3 below. Table 3 may be represented as a decision tree, algorithm, artificial intelligence, script, or logic tree. The function of such a decision tree, algorithm, artificial intelligence, script or logic tree is to output a score as to the health of the individual microbiome associated with the detected probiotic and to provide formula and dosage recommendations for the use of the probiotic.

An exemplary list of potential categories into which microorganisms may be grouped is set forth in table 4 below.

TABLE 3

Exemplary decision tables for probiotic scoring and formulation.

Including the utilization of a probiotic strain database, a metagenomic analysis database and a document management database

TABLE 4

Potential categories from which to create groups

Unless defined otherwise, all scientific and technical terms used herein have the meanings commonly used in the art.

As used herein, the term "subject" includes both human and non-human animals. The term "non-human animal" includes all vertebrates, e.g., mammals and non-mammals, such as non-human primates, horses, sheep, dogs, cows, pigs, chickens and other veterinary subjects and test animals.

The use of the singular may include the plural unless specifically stated otherwise. As used in the specification and the appended claims, the singular forms "a", "an", and "the" may include plural referents unless the context clearly dictates otherwise. The use of "or" may mean "and/or" unless stated otherwise. As used herein, "and/or" means "and" or ". For example, "A and/or B" means "A, B or both A and B," and "A, B, C and/or D" means "A, B, C, D or a combination thereof," and the "combination thereof" means any subset of A, B, C and D, e.g., a subset of a single member (e.g., A or B or C or D), a subset of two members (e.g., A and B; A and C; etc.), or a subset of three members (e.g., A, B and C; or A, B and D; etc.), or all four members (e.g., A, B, C and D).

As used herein, the terms "sample" and "biological sample" refer to any sample suitable for the methods provided by the present invention. The sample of cells may be any sample, including, for example, an intestinal or fecal sample obtained by a non-invasive or invasive technique such as a biopsy of the subject. In one embodiment, the term "sample" refers to any preparation of fecal material or intestinal tissue derived from a subject. For example, a sample of cells obtained using the non-invasive methods described herein can be used to isolate nucleic acid molecules or proteins for use in the methods of the invention.

In embodiments, the assay may be any nucleic acid, including DNA, RNA, cDNA, miRNA, mtDNA, single stranded or double stranded. Such nucleic acids may be of any length, as short as about 5bp oligonucleotides, as long as megabases, or even longer. As used herein, the term "nucleic acid molecule" refers to DNA, RNA, single, double, or triple stranded, and any chemical modification thereof. Indeed, any modification of the nucleic acid is contemplated. A "nucleic acid molecule" can have almost any length, from 10, 20, 30, 40, 50, 60, 75, 100, 125, 150, 175, 200, 225, 250, 275, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 150,000, 200,000, 500,000, 1,000,000, 1,500,000, 2,000,000, 5,000,000, or even more bases in length, up to a full-length chromosomal DNA molecule. For methods of analyzing the expression of genes, the nucleic acid isolated from the sample is typically RNA.

Based on the ability of guanine (G) to base pair with cytosine (C) and adenine (a) to base pair with thymine (T) or uridine (U), a single-stranded nucleic acid molecule is "complementary" to another nucleic acid molecule when it can base pair (hybridize) with all or part of another single-stranded nucleic acid molecule to form a double helix (double-stranded nucleic acid molecule). For example, the nucleotide sequence 5 '-TATAC-3' is complementary to the nucleotide sequence 5 '-GTATA-3'.

"hybridization" as used herein refers to the process by which a strand of nucleic acid joins with a complementary strand through base pairing. Hybridization reactions can be sensitive and selective, and thus a particular sequence of interest can be identified even in samples where it is present at low concentrations. In the in vitro case, suitable stringency conditions can be defined by, for example, the concentration of salt or formamide in the prehybridization and hybridization solutions or by the hybridization temperature, and are well known in the art. In particular, stringency can be increased by reducing the salt concentration, increasing the formamide concentration, or increasing the hybridization temperature. For example, hybridization under high stringency conditions can be performed in about 50% formamide at about 37 ℃ to 42 ℃. Hybridization can be performed under reduced stringency conditions in about 35% to 25% formamide at about 30 ℃ to 35 ℃. Specifically, hybridization can be performed under high stringency conditions of 42 ℃ in 50% formamide, 5 XSSPE, 0.3% SDS, and 200mg/ml sheared and denatured salmon sperm DNA. Hybridization can be in the above reduced stringency conditions, but in 35% formamide at 35 degrees C reduced temperature. The temperature range corresponding to a particular stringency level can be further narrowed by calculating the purine to pyrimidine ratio of the nucleic acid of interest and adjusting the temperature accordingly. Variations of the above ranges and conditions are well known in the art.

As used herein, the term "microbiome" refers to microorganisms residing in the gut of a subject, including bacteria, viruses and fungi, archaea, protozoa, amoebae or worms.

As used herein, the term microbial (microbiological), microbial (microbe) or microbial (microbiological) refers to any microorganism (microbiological organism), including prokaryotic or eukaryotic organisms, spores, bacteria, archaebacterium, fungi, viruses or protists, unicellular or multicellular.

The invention is described in part in terms of functional components and various processing steps. Such functional components and process steps may be realized by any number of components, operations, and techniques configured to perform the specified functions and achieve the various results. For example, the present invention may employ various biological samples, biomarkers, elements, materials, computers, data sources, storage systems and media, information collection techniques and processes, data processing standards, statistical analysis, regression analysis, and the like, which may carry out a variety of functions. Moreover, although the present invention is described in the context of medical diagnostics, the present invention may be implemented in connection with any number of applications, environments, and data analysis; the system described herein is only an exemplary application of the present invention.

The method for data analysis according to various aspects of the present invention may be implemented in any suitable way, for example using a computer program running on a computer system. According to various aspects of the present invention, an exemplary analysis system may be implemented in conjunction with a computer system (e.g., a conventional computer system including a processor and random access memory, such as a remotely accessible application server, web server, personal computer, or workstation). The computer system also suitably includes additional storage or information storage systems, such as mass storage systems and user interfaces, e.g., conventional monitors, keyboards, and tracking devices. However, the computer system may comprise any suitable computer system and associated equipment and may be configured in any suitable manner. In one embodiment, the computer system comprises a standalone system. In another embodiment, the computer system is part of a network of computers including servers and databases.

The software required to receive, process and analyze the genetic information may be implemented in a single device or in multiple devices. The software is accessible over a network so that storage and processing of information occurs remotely with respect to the user. The analysis system and its various elements according to various aspects of the present invention provide functions and operations that facilitate microbiome analysis, such as data collection, processing, analysis, reporting, and/or diagnostics. The present analysis system maintains information relating to microbiome and sample and facilitates analysis and/or diagnosis. For example, in the present embodiment, the computer system executes a computer program that can receive, store, search, analyze, and report information related to a microbiome. The computer program may contain a plurality of modules that perform various functions or operations, such as a processing module for processing the raw data and generating the supplemental data, and an analysis module for analyzing the raw data and the supplemental data to generate a model and/or a prediction.

The analysis system may also provide various additional modules and/or separate functions. For example, the analysis system may also include reporting functionality, e.g., to provide information related to processing and analysis functions. The analytics system may also provide various management and administrative functions, such as controlling access and performing other administrative functions.

To the extent necessary to understand or complete the disclosure of the present invention, all publications, patents, and patent applications mentioned herein are expressly incorporated by reference as if each were individually incorporated.

Although the present invention has been described with reference to the above examples, it should be understood that modifications and variations are included within the spirit and scope of the present invention. Accordingly, the invention is not to be restricted except in light of the attached claims.

Claims

1. A method, comprising:

a) mixing the sample with a liquid nitrogen solution;

b) adding a first lysis solution comprising a detergent and a chelating agent; and

c) adding a second lysis solution comprising a chaotropic agent.

2. The method of claim 1, wherein mixing the sample with a liquid nitrogen solution further comprises milling the sample and the liquid nitrogen mixture.

3. The method of claim 1, wherein the first lysis solution further comprises one or more buffers, one or more mild detergents, and/or one or more proteases.

4. The method of claim 1, wherein the detergent of the first lysis solution comprises SDS.

5. The method of claim 4, wherein the concentration of SDS is about 10%.

6. The method of claim 1, wherein the chaotropic agent comprises lithium acetate.

7. The method of claim 6, wherein the mixture of sample, liquid nitrogen, the first lysis solution, and the second lysis solution is further subjected to a thermal shock treatment.

8. The method of claim 1, wherein the sample is subjected to a pretreatment step prior to treatment with the first lysis solution, the pretreatment step inducing germination of any bacterial spores and/or fungal spores present in the sample.

9. The method of claim 8, wherein the pretreating step comprises mixing the sample with tween-80.

10. The method of claim 1, further comprising a mechanical processing step that causes physical lysis, the mechanical processing step comprising sonication, bead mixing, bead milling homogenization, pressurization, microfluidization, or a combination thereof.

11. The method of claim 1, further comprising performing a metagenomics analysis of any extracted genetic material.

12. The method of claim 1, wherein the sample is obtained from the intestinal tract of a subject.

13. The method of claim 11, wherein the metagenomic analysis identifies one or more foods that the subject has consumed.

14. The method of claim 11, wherein the metagenomic analysis identifies one or more macronutrients that the subject has consumed.

15. The method of claim 11, further comprising determining probiotic treatment of the subject based on the metagenomic analysis.

16. The method of claim 11, further comprising determining dietary guidance for the subject based on the metagenomic analysis.

17. A method of determining food consumption of a subject, comprising:

a) extracting genetic material from a stool sample obtained from the subject, the genetic material extracted according to claim 1; and

b) performing a metagenomic analysis of the genetic material extracted from the first sample to determine the food consumption of the subject.

18. The method of claim 17, further comprising treating the subject with a probiotic or a food based on an analysis of food consumption.

19. The method of claim 17, wherein the metagenomic analysis comprises using a database having genomic data of such organisms that can be used to identify the organisms.

20. The method of claim 19, wherein the database can be processed as complete genomes, k-mers of different lengths that are common to higher orders and unique to a particular order, or other means of barcoding genomes to match them to sequencing results.

21. The method of claim 17, wherein metagenomic analysis comprises pre-processing sequencing information selected from the group consisting of removing duplicates, removing adapter sequencing, removing 5 'or 3' sequencing to improve the quality of base calls, including only base calls of a particular quality (i.e., Q20 or higher), filtering human reads, creating paired reads or separating them, and limiting overlap of reads.

22. The method of claim 19, wherein metagenomic analysis comprises aligning sequencing information to the database by using software or systems, wherein the sequencing information can be separated into k-mers of a specific length, used as whole fragments, framed and aligned to a large reference genome, or other methods to create a report of the identified organism, relative abundance of the identified organism, genome size, total fragments aligned, unique fragments aligned in strain, species, genus, family, order, class, phylum, kingdom or domain.

23. The method of claim 17, wherein a microbiome profile enables identification of a disease, disorder, or specific feature indicative of dysbiosis, wherein probiotic and/or dietary supplement therapy may be applied to modulate the microbiome to improve a basal profile.

24. The method of claim 23, wherein groups are created based on demographic, phenotypic, or diagnostic information and barcodes assigned to groups of the profiles.

25. The method of claim 24, wherein statistical analysis is used to determine how closely an individual microbiome profile correlates with a known group in a database.

26. A method of monitoring probiotic treatment in a subject, the method comprising:

a) extracting genetic material from any microorganisms present in a first sample obtained from the subject, the genetic material being extracted according to claim 1;

b) performing a metagenomic analysis of the genetic material extracted from the first sample;

c) treating the subject with a probiotic and then extracting genetic material from any microorganisms present in a second sample obtained from the subject in the same manner as the genetic material is extracted from the first sample;

d) performing a metagenomic analysis of genetic material extracted from the second sample; and

e) comparing the results of the metagenomic analysis of the first sample with the results of the metagenomic analysis of the second sample.

27. The method of claim 26, further comprising modifying the probiotic treatment to obtain a desired population of microorganisms in the subject.

28. The method of claim 26, further comprising analyzing metabolomic markers to determine appropriate probiotic treatment.

29. The method of claim 26, wherein probiotic treatment is performed after use of antibiotics, chemotherapy, drugs, environmental changes, travel, contaminating digestion, intestinal or intestinal infarction, stress, or other effects where disruption of the microbial population may occur.

30. The method of claim 27, wherein the modulation of the microbiome is returning an individual to a previous population of microorganisms when the individual was known to be healthy.

31. The method according to claim 27, wherein the modulation of the microbiome by probiotics and/or prebiotics is to restore the microbiome profile to normal gut already defined internally by the database or externally by the public database.

32. The method of claim 31, wherein normal is defined as a microbiome profile similar to a fecal material reservoir sample used in fecal material transplantation, but used as a probiotic/prebiotic to restore dysbiosis.

33. A computing system, comprising: a memory; and one or more processors coupled to the memory, the one or more processors configured to perform operations to perform the method of claim 17.

34. A computing system, comprising: a memory; and one or more processors coupled to the memory, the one or more processors configured to perform operations to perform the method of claim 26.

35. An automated platform for performing the method of claim 1.