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High-throughput biochemical fingerprinting of Saccharomyces cerevisiae by Fourier transform infrared spectroscopy

Journal article
Authors A. Kohler
U. Böcker
V. Shapaval
Annabelle Forsmark
Mats X. Andersson
Jonas Warringer
H. Martens
S. W. Omholt
Anders Blomberg
Published in PLoS ONE
Volume 10
Issue 2
ISSN 1932-6203
Publication year 2015
Published at Department of Biological and Environmental Sciences
Department of Chemistry and Molecular Biology
Language en
Links dx.doi.org/10.1371/journal.pone.011...
Subject categories Biochemistry

Abstract

Single-channel optical density measurements of population growth are the dominant large scale phenotyping methodology for bridging the gene-function gap in yeast. However, a substantial amount of the genetic variation induced by single allele, single gene or double gene knock-out technologies fail to manifest in detectable growth phenotypes under conditions readily testable in the laboratory. Thus, new high-throughput phenotyping technologies capable of providing information about molecular level consequences of genetic variation are sorely needed. Here we report a protocol for high-throughput Fourier transform infrared spectroscopy (FTIR) measuring biochemical fingerprints of yeast strains. It includes high-throughput cultivation for FTIR spectroscopy, FTIR measurements and spectral pretreatment to increase measurement accuracy.We demonstrate its capacity to distinguish not only yeast genera, species and populations, but also strains that differ only by a single gene, its excellent signal-to-noise ratio and its relative robustness to measurement bias. Finally, we illustrated its applicability by determining the FTIR signatures of all viable Saccharomyces cerevisiae single gene knock-outs corresponding to lipid biosynthesis genes. Many of the examined knock-out strains showed distinct, highly reproducible FTIR phenotypes despite having no detectable growth phenotype. These phenotypes were confirmed by conventional lipid analysis and could be linked to specific changes in lipid composition. We conclude that the introduced protocol is robust to noise and bias, possible to apply on a very large scale, and capable of generating biologically meaningful biochemical fingerprints that are strain specific, even when strains lack detectable growth phenotypes. Thus, it has a substantial potential for application in the molecular functionalization of the yeast genome.

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