Pismennõi Dmitri, Kattel Anna, Belouah Isma, Nahku Ranno, Vilu Raivo, Kobrin Eeva-Gerda
Center of Food and Fermentation Technologies (TFTAK), Mäealuse 2/4, 12618 Tallinn, Estonia.
Department of Chemistry and Biotechnology, Tallinn University of Technology, Akadeemia Tee 15, 12618 Tallinn, Estonia.
Microorganisms. 2023 Aug 23;11(9):2134. doi: 10.3390/microorganisms11092134.
The high throughput in genome sequencing and metabolic model (MM) reconstruction has democratised bioinformatics approaches such as flux balance analysis. Fluxes' prediction accuracy greatly relates to the deepness of the MM curation for a specific organism starting from the cell composition. One component is the cell wall, which is a functional barrier (cell shape, exchanges) with the environment. The bacterial cell wall (BCW), including its thickness, structure, and composition, has been extensively studied in but poorly described for other organisms. The peptidoglycan (PG) layer composing the BCW is usually thinner in Gram- bacteria than in Gram+ bacteria. In both bacteria groups, PG is a polymeric mesh-like structure of amino acids and sugars, including N-acetylglucosamine, N-acetylmuramic acid, and amino acids. In this study, we propose a high-throughput method to characterise and quantify PG in Gram-positive and Gram-negative bacteria using acidic hydrolysis and hydrophilic interaction liquid chromatography coupled with mass spectrometry (HILIC-MS). The method showed a relatively short time frame (11 min analytical run), low inter- and intraday variability (3.2% and 4%, respectively), and high sensitivity and selectivity (limits of quantification in the sub mg/L range). The method was successfully applied on two Gram-negative bacteria ( K12 MG1655, DSM 2079) and one Gram-positive bacterium ( ssp. DSM20259). The PG concentration ranged from 1.6% / to 14% / of the dry cell weight. The results were in good correlation with previously published results. With further development, the PG concentration provided by this newly developed method could reinforce the curation of MM.
基因组测序和代谢模型（MM）重建的高通量技术使通量平衡分析等生物信息学方法得以普及。通量预测的准确性与从细胞组成开始对特定生物体的MM管理深度密切相关。其中一个组成部分是细胞壁，它是与环境的功能屏障（细胞形状、物质交换）。细菌细胞壁（BCW），包括其厚度、结构和组成，已得到广泛研究，但对其他生物体的描述却很少。构成BCW的肽聚糖（PG）层在革兰氏阴性菌中通常比在革兰氏阳性菌中更薄。在这两类细菌中，PG都是由氨基酸和糖类组成的聚合物网状结构，包括N-乙酰葡糖胺、N-乙酰胞壁酸和氨基酸。在本研究中，我们提出了一种高通量方法，使用酸性水解和亲水相互作用液相色谱-质谱联用（HILIC-MS）来表征和定量革兰氏阳性菌和革兰氏阴性菌中的PG。该方法显示出相对较短的分析时间（11分钟分析运行）、较低的日内和日间变异性（分别为3.2%和4%）以及高灵敏度和选择性（定量限在亚毫克/升范围内）。该方法成功应用于两种革兰氏阴性菌（K12 MG1655、DSM 2079）和一种革兰氏阳性菌（ssp. DSM20259）。PG浓度范围为干细胞重量的1.6%/至14%/。结果与先前发表的结果具有良好的相关性。随着进一步发展，这种新开发方法提供的PG浓度可以加强MM的管理。
