PATENT CLAIM ANALYSIS

Application Number: 15923555
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-08
Patent Classification: ["439", "069000"]

Abstract:
The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

Claim (Index 1):
A method for rehabilitating and improving the phenotypic performance of a production microbial strain, which does not require prior knowledge regarding the underlying function of a given genetic variation, the method comprising the steps of:\n a. providing a parental lineage microbial strain and a production microbial strain derived therefrom, wherein the production microbial strain comprises a plurality of identified genetic variations selected from single nucleotide polymorphisms, DNA insertions, and DNA deletions, not present in the parental lineage microbial strain; b. perturbing the genome of either the parental lineage microbial strain, or the production microbial strain, to create an initial library of microbial strains, wherein each strain in the initial library comprises a genetic variation that is unique from amongst the plurality of identified genetic variations between the parental lineage microbial strain and the production microbial strain; c. screening and selecting individual strains of the initial library for phenotypic performance improvements over a reference microbial strain, thereby identifying genetic variations that confer phenotypic performance improvements; d. providing a subsequent plurality of microbes that each comprise a combination of genetic variations from the genetic variations present in at least two individual microbial strains screened in the preceding step, to thereby create a subsequent library of microbial strains; e. screening and selecting individual strains of the subsequent library for phenotypic performance improvements over the reference microbial strain, thereby identifying combinations of genetic variation that confer additional phenotypic performance improvements; and f. repeating steps d)-e) one or more times, in a linear or non-linear fashion, until a microbial strain exhibits a desired level of improved phenotypic performance compared to the phenotypic performance of the production microbial strain, wherein each subsequent iteration creates a new library of microbial strains, where each strain in the new library comprises genetic variations that are a combination of genetic variations selected from amongst at least two individual microbial strains of a preceding library; and wherein the method enables analyzing genome-wide combinatorial effects of genetic variations across multiple disparate genomic regions, including genes of no known function.

Metadata:
- Claim Count in Document: 40.0
- Percentile: 90.0
- Lexical Diversity: 1.45588
- Patent Class: 439.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15396230', '15923527', '15923543', '16313613', '16313612']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.8024233999801439
- 35 USC 102 Novelty (BERT): 0.7333158375196536
- Combined Prediction Score: 0.7955126437340949
- Mean Citation Score: 528.1129080000002
- Max Citation Score: 814.24243
- Similarity Product: 747.4783223078049

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test