Methods, apparatus and Systems for Analysis of complex communities of Microorganisms strains HETEROGu00c9NEAS, Predicting and identifying Functional relationships and Interactions of these sets, and select and synthesize microbial based on these

摘要

Described are methods, apparatus and Systems for SIFT, analyze and select microorganisms Complex heterogeneous Communities, Predicting and identifying Functional relationships and Interactions of these sets and synthesize these microbial function.It also describes methods to identify and determine the absolute count of cell types and Strains of Microorganisms, and also to identify the relationships between network active microorganisms and Environmental parameters.Claim 1: a method, comprising: obtaining at least two samples that share at least one Common characteristic and have at least one feature for each Sample, different;Detect the presence of one or more types of Microorganisms in each sample; determining the quantity of each kind of microorganism detected one or more types of Microorganisms in each sample; Measuring a First number of unique markers in each Sample, and the number of these,When every single Marker is a marker of a Strain of microorganism; integrate the number of each type of Micro organism and the number of the first Markers to provide Absolute CELL COUNTING of each Strain of Microorganisms present in each sample to Measure at least one Second; Unique marker for each Strain of Microorganisms in a specific function to determine a thresholdLevel of activity to the strain of microorganism in each sample; Filter the absolute cell count for the given activity to provide a list of active strains of microorganisms and their respective Absolute cell counts for each of at least two samples; to compare the cont EOS Absolute Cell filtrates of strains of Microorganisms are active for each of at least twoSamples with at least one metadata or additional Active microorganisms measured Strain for each of at least two samples and categorize the Strains of Microorganisms active in at least two groups according to the function and / or chemical methods; selecting at least one Strain of Microorganisms at least Combining the two groups and at least one Strain of Microorganisms selected at least two groups of PAForming a group of Microorganisms that is configured to change a property of said at least one metadata.Claim 82: a method implemented by Processor, which comprises: receiving data shows at least two samples that share at least one Common characteristic and have at least one feature for each Sample, different;Determining the presence of one or more types of Microorganisms in each sample; determine the number of each kind of microorganism detected one or more types of Microorganisms in each sample; determining a First number of unique markers in each Sample, and the number of these, where CAD The first unique Marker is a marker of a Strain of microorganism; integrate, through a Processor,The number of each type of Micro organism and the number of the first Cell Markers to obtain the absolute count of each Strain of Microorganisms present in each sample to determine a level of activity for each Strain of Microorganisms in each Sample on the basis of a measurement of the M A second US single marker for each Strain of Microorganisms that exceeds a specific Threshold.Where a Strain of Microorganisms were identified as active if the Measurement of at least one Second unique marker for the strain exceeds the corresponding Threshold; Filtering the cell count of each Strain of Microorganisms for the particular activity to provide a list of strains Active microorganisms and their respective Absolute cell counts for each of at least two muFlower; to carry out an analysis of network Processor, using at least one of the absolute cell counts filtrates of strains of Microorganisms are active for each of at least two samples with at least one metadata or additional Active microorganisms measured Strain for each of at least do S samples,Network Analysis includes determining maximal coefficient scores of information between every strain and every Strain of microorganism Active microorganisms and Activated by determining the scores of maximal Strain coefficient of information between each of the active microorganisms and me We measured respective metadata or additional Active Strain of Microorganisms; categorize strainsActive microorganisms according to predicted function and / or Chemistry; identifying a Plurality of active strains of Microorganisms on the basis of the categorization, and produce the Plurality of identified Active strains of microorganisms.