Microbial Quantitation Using Synthetic Spike-In Nucleic Acids
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Solution Overview
Problem
Current methods for determining microbial taxa and genes in agricultural soils, such as metagenomics, face challenges in accurately predicting crop yield and disease pressure due to limitations in quantifying absolute microbial abundances from relative abundance data, which can be misleading and fail to account for soil texture and extraction efficiencies.
Innovation Solution
An analytics system that adds synthetic nucleic acids (spike-in) to soil samples for sequencing, using correction factors to normalize sequence reads and account for soil texture, allowing for accurate determination of microbial abundances in terms of genomic mass or cell count per unit soil mass, thereby providing more reliable data for agronomic management decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metagenomics sequencing is used to profile microbial communities, then microbial taxa and genes can be detected, but accurate quantification of absolute microbial abundances cannot be achieved due to reliance on relative abundance data
Solution Approach 1:
The patent introduces synthetic nucleic acids as an intermediary substance added to soil samples before sequencing. These synthetic nucleic acids serve as internal references that allow conversion of relative sequence read abundances into absolute microbial abundances. The synthetic nucleic acids do not interfere with the sequencing process but provide a known quantity baseline for calculation, resolving the contradiction between obtaining microbial profiles and achieving accurate absolute quantification.
Solution Approach 2:
The patent changes the parameter used for quantification from relative abundance (proportion of sequence reads) to absolute abundance (number of organisms per unit soil mass). By adding synthetic nucleic acids with known concentrations, the system transforms sequencing data into absolute quantitative measurements, enabling accurate determination of microbial abundances while maintaining the ability to detect microbial taxa and genes.
2Ease of operation
If relative abundance data is used for microbial enumeration, then sequencing analysis is simplified, but the data becomes misleading when comparing different soil types due to varying soil textures and extraction efficiencies
Solution Approach 1:
Synthetic nucleic acids act as a common reference intermediary across different soil types. Since these synthetic nucleic acids are added in known quantities before extraction and sequencing, they serve as an internal control that normalizes differences caused by varying soil textures, organic matter content, and extraction efficiencies. This allows reliable comparison of microbial abundances across different soil types while maintaining simplified sequencing analysis procedures.
Solution Approach 2:
The synthetic nucleic acids provide feedback about extraction efficiency and sequencing depth for each sample. By measuring the recovery of synthetic nucleic acids through the extraction and sequencing process, the system can calculate correction factors that adjust the sequence read counts to reflect true absolute abundances. This feedback mechanism ensures reliable comparisons while keeping the overall analysis process straightforward.
3Measurement precision
If correction factors are applied to account for soil texture and extraction efficiency, then accurate microbial quantitation is achieved, but the analysis complexity increases
Solution Approach 1:
The synthetic nucleic acids are added to soil samples before DNA extraction and sequencing begins. This preliminary addition allows the correction factors to be calculated based on the known initial quantity of synthetic nucleic acids and their recovery through the entire process. By performing this action beforehand, the system simplifies subsequent data processing, as the correction factors can be applied directly to sequence read counts without requiring complex multi-step analysis.
Solution Approach 2:
The patent transforms the data processing approach by introducing a new parameter - the concentration of synthetic nucleic acids - that serves as a baseline for calculation. This parameter change allows complex corrections for soil texture and extraction efficiency to be incorporated into a unified quantitative framework. The synthetic nucleic acid concentration provides a reference that simplifies the calculation of absolute microbial abundances, achieving precise measurement without proportionally increasing processing complexity.
Data Source
AI summary
In various embodiments of an analytics system, a spike-in including synthetic constructs of nucleic acid is added to soil samples for processing. The analytics system determines sequence reads classified to a microbe in the soil sample. The analytics system determines one or more measures of soil texture of the soil sample, for example, indicating percentages of sand, silt, and clay. The analytics system determines a measure of the microbe as a function of at least the classified sequence reads, the one or more measures of soil texture, and a mass of the spike-in. The analytics system can transmit the measure of the microbe to a client device for display on a user interface. A field where the soil sample was obtained can be treated according to the measure of the microbe.