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Article 10: Metebolomics and Immunology Cultivation/新陈代谢组学与免疫力培养 Author: Liu Huan (1983-), Master of Science (First Class Honours), The University of Auckland.Published after graduation on 11/01/2016, Revised on 04/02/2021. This article designs a novel method to analyze the isozyme electrophoretograms acrossdifferent isozyme families, targeting the cultivation of environmental adaptiveness. Methods: The same strain of microbes is divided into two samples for the bio-signal simulation: 1. There are two kinds of cultivation conditions simulated in Lab for microbe reproduction process: one is the ‘comfortable’ condition (Sample 1); the other is under UV-B radiation for cultivation (Sample 2). The microbe samples are collected after sufficient reproduction process (Ten generations). 2. After sufficient reproduction process, the UV-B radiation simulation stops. Then both sample 1 and sample 2 are separately transferred into moisture simulation process: different moisture conditions of microbial cultivation are simulated in Lab, and labeled as T1, T2, ..., Tn. 3. Metabolomics tests are conducted after moisture simulation of T1, T2, ..., Tn respectively, resulting in different zymograms as: M1, M2, ..., Mn. The procedure of this test is presented in previous article of this journal. 4. Each isozyme family is labeled as 1, 2, 3..., and E; It is hypothesized that the bands at the same line across different isozyme families are the enzyme species at the same locus, named as enzyme ‘species i’ (i = 1, 2, ..., I), and each isozyme family has the same amount (I) of enzyme species (Please note: this is different from the identification of real enzyme species). Then there is a 3-dimension (I× E × N) matrix presented in this research. I is the total amount of enzyme species within a isozyme family; E is the total amount of isozyme families; N is the total amount of zymograms among different simulated moisture conditions:
X= │Xien │( i = 1, 2, ....I; e = 1, 2, .... E; n= 1, 2, ... N) file:///C:\Users\ADMINI~1\AppData\Local\Temp\ksohtml\wpsA0A9.tmp.pngfile:///C:\Users\ADMINI~1\AppData\Local\Temp\ksohtml\wpsA0AA.tmp.pngXien is the occurrence of enzyme ‘species i’ in the isozyme ‘family e’ during simulated moisture condition Tn. The value of Xien is one or zero.
| X112 ... X11n X212 ... X21n | | X122 ...... X12n ...... X222 ......X22n ....... | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Matrix Se = Xe × (Xe)T Xe = │Xin│( i = 1, 2, ....I; n= 1, 2, ... N); (Xe)T is the transpose of the matrix Xe: file:///C:\Users\ADMINI~1\AppData\Local\Temp\ksohtml\wpsA0AB.tmp.pngfile:///C:\Users\ADMINI~1\AppData\Local\Temp\ksohtml\wpsA0BB.tmp.pngX11 X12 ... X1n X21 X22 ... X2n Xe = ..... ....... ...... The Principal Components Analysis (PCA) method of matrix X is specified [1]. PCA is firstly conducted on the basis of matrix Se, revealing the biochemical dynamics of a isozyme ‘family e’ among different simulated moisture conditions. In matrix Se, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’. S = ΣSe (e = 1, 2, E) PCA is further conducted on the basis of matrix S, revealing the biochemical dynamics among different isozyme families over the whole simulated moisture conditions. In matrix S, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’ across all the isozyme families. The theory of this matrix design has been discussed in the first article of metabolomics in this journal. However, for the comparison between sample 1 and sample 2, this book need to present more procedures for subsequent analysis: in matrix Se, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA in an isozyme family, are selected for comparison between sample 1 and sample 2; in matrix S, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA across all the isozyme families, are selected for comparison between sample 1 and sample 2; the sum dynamics of the first three enzyme species in a isozyme family (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix Se), represents the total variation of a isozyme family over the whole simulated moisture conditions; the sum dynamics of the first three enzyme species across all the isozyme families (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix S), represents the variation of the total zymograms over the whole simulated moisture conditions. Hypotheses: 1. The higher variation in biochemical dynamics of enzyme expression, the better environmental adaptiveness or immunology. It is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of this comparison; 2. Sample 2 leads to higher variation in biochemical dynamics of enzyme expression, which is also revealed by the higher adaptiveness during drought stress or higher immunology. Discussion: The findings of this article further support the theory proposed by other articles of this journal: the memory of cells can be ‘trained’ by the biophysical simulation in site, indicated by the zymograms in metabolomics test. Consequently, the memory of cells, in terms of identifying the bio-signals of a specific environmental factor (can be biotic or abiotic) triggering the gene expression for environmental adaptiveness or immunology, can be trained and strengthened by the biophysical simulation of other environmental factors. The next article (biophysical simulation for blood cell division) further supports above theories (please note: the theory, ‘memory’ of gene expression, is also applicable on cell division in an individual) by assessment of resistance or immunology in host cells. This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” Published in 2016. The ‘chapter’ content mentioned in this article is in previous book. Firstly Revised on 05/01/2021; Secondly Revised on 04/02/2021; Thirdly revised on 25/09/2021. References:[1] 陶玲，任裙 （2004）。进化生态学的数量研究方法。第一章，第六节，第 49 页。 中国林业出版社。 ISBN：7-5038-3735-7
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发表于 2021-2-7 11:03:00
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