Nitrogen and sulfur for phosphorus: Lipidome adaptation for anaerobic sulfate-reducing bacteria in phosphorus-deprived conditions

Abstract Understanding how microbial lipidomes adapt to environmental and nutrient stress is crucial for comprehending microbial survival and functionality. Certain anaerobic bacteria can synthesize glycerolipids with ether/ester bonds, yet the complexities of their lipidome remodeling under varying environmental and nutritional conditions remain largely unexplored. In this study, we thoroughly examined the lipidome adaptations of Desulfatibacillum alkenivorans strain PF2803T, a mesophilic anaerobic sulfate-reducing bacterium known for its n-alkene degradation capability, under various cultivation conditions including temperature, pH, salinity, and ammonium and phosphorous concentrations. Employing an extensive analytical and computational lipidomic methodology, we identified nearly 400 distinct lipids for the first time, including a range of glycerol ether/ester lipids and various polar head groups. Information theory-based analysis revealed that temperature fluctuations and phosphate scarcity profoundly influenced the lipidome's composition, leading to enhanced diversity and specificity of novel lipids. Notably, phosphorous limitation led to the creation of novel glucuronosylglycerols and sulfur-containing aminolipids, termed butyramide cysteine glycerols, featuring various ether/ester bonds. This suggests a novel adaptive strategy for anaerobic heterotrophs to thrive in phosphorus-depleted areas of the oceans, characterized by a diverse array of nitrogen- and sulfur-containing polar head groups, moving beyond a reliance on conventional non-phospholipid types. Repository Contents 1_SRB_lipidome.zip: includes all source data and code scripts used for figures in this study. Files are organized as follows and are associated with the corresponding parts of the manuscript: Figure 2A-F, Figure 4A-E, Figure 5A-B, Figure 6A-E, Supplementary Figures 7. Figure 2. The impact of culturing conditions on lipidomic variability. A) The number of intact polar lipid species in different lipid classes putatively identified in this study. B) Principal Component Analysis (PCA) based on peak intensity of intact polar lipid species, showcasing the variation in general lipidomic features across individual experimental conditions. C) Information theory analysis showing lipidome diversity and specificity based on the Shannon entropy of the lipidomic frequency distribution. D) Lipid species specificity across the various culturing conditions. E) Hierarchical clustering heatmap depicting the distribution of major lipid classes across all the culturing conditions. F) Cumulative variability of all intact polar lipid species within each range of growth conditions, calculated as the difference in mean abundance between the standard growth condition and the variable conditions. The variability analysis excludes phosphate 0.015 mM as it is under phosphorous-sufficient condition, which showed a similar lipidome composition as the standard growth condition. Each condition analysis is based on three biological replicates. Abbreviations: Polar head groups –phosphatidylethanolamines (PE), phosphatidylglycerols (PG), cardiolipins (CL), novel N-butyramide cysteine (BACys), glucuronosyl (GlcA); Core lipids – diacylglycerols (DAGs), acyl/ether glycerols (AEGs), dietherglycerols (DEGs), tetraetherglycerols (TetraEGs), triether/monoacyl glycerols (TriEGs), diether/diacyl glycerol (DiEGs), monoether/triacyl glycerol (MonoEGs), and tetraacylglycerols (TetraAGs), demethylmenaquinone (DMK). Figure 4. Variability of major lipid classes across different culturing conditions. A) PG with different ether/ester bond core lipids. B) PE with different ether/ester bond core lipids. C) CL with different ether/ester bond core lipids. D) GlcA with different ether/ester bond core lipids. E) Novel BACys with different ether/ester bond core lipids. Asterisks indicate significant differences between the last condition and the current condition (Student's t tests on pairwise differences, *P < 0.05, **P < 0.01 and ***P < 0.001). The numbers of treatments on the x-axis represent the parameters associated with each condition, ranging from low to high. These parameters include temperature (25°C, 30°C, 40°C), pH levels (6.4, 6.8, 7.8), NaCl concentration (3 g/L, 10 g/L, 25 g/L, 60 g/L), phosphate concentration (0.0005 mM, 0.0015 mM, 0.015 mM, 1.5 mM), and ammonium concentration (0.003 g/L, 0.03g/L, 0.3 g/L). Figure 5. Distribution of the relative abundance of major lipid classes and number of lipid species across different culturing conditions. A) Relative abundance of major lipid classes. B) Number of lipid species with an abundance exceeding 0.5% of the total lipids. The numbers of treatments on the x-axis represent the parameters associated with each condition, ranging from low to high. These parameters include temperature (25°C, 30°C, 40°C), pH levels (6.4, 6.8, 7.8), NaCl concentration (3 g/L, 10 g/L, 25 g/L, 60 g/L), phosphate concentration (0.0005 mM, 0.0015 mM, 0.015 mM, 1.5 mM), and ammonium concentration (0.003 g/L, 0.03g/L, 0.3 g/L). Figure 6. Adaptation of ether/ester bond lipids, polar headgroups, the averaged carbon chain length and double bond equivalents (DB) of the studied sulfur-reducing bacterial lipidome across different culturing conditions. A) The ratio of phospholipids with dialkyl chains and tetraalkyl chains, or the ratio of (PE+PG)/CL, calculated as the summed core lipids within each class. B) The logarithmic ratio of phospholipids/non-phospholipids, phospholipids included both diglyceride phospholipids (PG and PE) and CL. C) The ratio of ether/ester bond lipids. The abundance of ethers in lipids with DEGs is calculated based on their inherent intensity, while the abundance of ethers in lipids containing both ether and ester chains is determined using the ratio of ether% multiplied by the intensity. For instance, in CL-TriEG, which has three ether-bond chains and one ester-bond chain, the abundance of the ether chain is calculated as 0.75 multiplied by the intensity. D) The average DBs of total lipids across different culturing conditions. E) The average chain length of two-chain lipids across different culturing conditions. Asterisks indicate significant differences between the last condition and the current condition (Student’s t tests on pairwise differences, *P < 0.05, **P < 0.01 and ***P < 0.001). These parameters include temperature (25°C, 30°C, 40°C), pH levels (6.4, 6.8, 7.8), NaCl concentration (3 g/L, 10 g/L, 25 g/L, 60 g/L), phosphate concentration (0.0005 mM, 0.0015 mM, 0.015 mM, 1.5 mM), and ammonium concentration (0.003 g/L, 0.03g/L, 0.3 g/L). Fig. S7. The fractional abundance of lipids with (A) different DBs (0-4) and (B) different carbon chain lengths (26-37, 56-68). The numbers from 26 to 37 represent the summed two-chain carbon atoms, while the numbers from 56 to 68 represent the summed four-chain carbon atoms (from CL). The numbers of treatments with different colors represent the parameters associated with each condition, ranging from low to high.# 摘要 解析微生物脂质组（lipidome）如何响应环境与营养胁迫，对于理解微生物的生存与功能至关重要。部分厌氧细菌可合成含醚/酯键的甘油脂，但目前对于这类微生物在不同环境与营养条件下的脂质组重塑机制仍知之甚少。 本研究针对一株以降解正烯烃见长的嗜温厌氧硫酸盐还原菌（sulfate-reducing bacterium）*Desulfatibacillum alkenivorans* PF2803^T，系统探究了其在温度、pH、盐度以及铵盐、磷浓度等不同培养条件下的脂质组适应性变化。本研究采用全面的分析与计算脂质组学方法，首次鉴定出近400种不同脂质，涵盖多类醚/酯键甘油脂与多种极性头部基团。 基于信息论的分析表明，温度波动与磷限制会显著影响脂质组组成，促使新型脂质的多样性与特异性提升。值得注意的是，磷限制条件下会产生新型的葡萄糖醛酸甘油脂与含硫氨基脂，这类被命名为丁酰胺半胱氨酸甘油脂（butyramide cysteine glycerols）的脂质具有多种醚/酯键结构。该发现揭示了厌氧异养微生物在海洋磷匮乏区域存活的全新适应性策略：这类微生物不再依赖传统的非磷脂类型，而是通过多样化的含氮与含硫极性头部基团来适应环境。 # 仓库内容 1_SRB_lipidome.zip：包含本研究所有用于生成图表的原始数据与代码脚本。文件组织形式如下，并与论文的对应章节关联：图2A-F、图4A-E、图5A-B、图6A-E以及补充图7。 ## 图2 培养条件对脂质组变异的影响 A）本研究推定鉴定的不同脂质类别中完整极性脂质物种的数量。B）基于完整极性脂质物种峰强度的主成分分析（Principal Component Analysis, PCA），展示了各实验条件下整体脂质组特征的差异。C）基于脂质组频率分布的香农熵（Shannon entropy）开展的信息论分析，用于呈现脂质组的多样性与特异性。D）不同培养条件下脂质物种的特异性分布。E）层级聚类热图，用于描述主要脂质类别在所有培养条件下的分布情况。F）各生长条件范围内所有完整极性脂质物种的累积变异度，该变异度通过标准生长条件与可变条件下的平均丰度差值计算得到。本变异度分析剔除了0.015 mM磷浓度组，因其处于磷充足条件下，脂质组组成与标准生长条件相似。所有条件的分析均基于3次生物学重复。 缩写说明：极性头部基团——磷脂酰乙醇胺（phosphatidylethanolamines, PE）、磷脂酰甘油（phosphatidylglycerols, PG）、心磷脂（cardiolipins, CL）、新型N-丁酰胺半胱氨酸（N-butyramide cysteine, BACys）、葡萄糖醛酸基（glucuronosyl, GlcA）；核心脂质——二酰甘油（diacylglycerols, DAGs）、酰基/醚甘油（acyl/ether glycerols, AEGs）、二醚甘油（dietherglycerols, DEGs）、四醚甘油（tetraetherglycerols, TetraEGs）、三醚/单酰甘油（triether/monoacyl glycerols, TriEGs）、二醚/二酰甘油（diether/diacyl glycerol, DiEGs）、单醚/三酰甘油（monoether/triacyl glycerol, MonoEGs）以及四酰甘油（tetraacylglycerols, TetraAGs）、去甲基甲基萘醌（demethylmenaquinone, DMK）。 ## 图4 不同培养条件下主要脂质类别的变异情况 A）携带不同醚/酯键核心结构的PG脂质。B）携带不同醚/酯键核心结构的PE脂质。C）携带不同醚/酯键核心结构的CL脂质。D）携带不同醚/酯键核心结构的GlcA脂质。E）携带不同醚/酯键核心结构的新型BACys脂质。星号表示当前条件与前一条件间的显著性差异（成对差异的Student t检验：*P < 0.05，**P < 0.01，***P < 0.001）。 横轴上的处理序号代表对应条件的参数，由低到高排列，这些参数包括：温度（25℃、30℃、40℃）、pH值（6.4、6.8、7.8）、NaCl浓度（3 g/L、10 g/L、25 g/L、60 g/L）、磷浓度（0.0005 mM、0.0015 mM、0.015 mM、1.5 mM）以及铵浓度（0.003 g/L、0.03 g/L、0.3 g/L）。 ## 图5 不同培养条件下主要脂质类别的相对丰度与脂质物种数量分布 A）主要脂质类别的相对丰度。B）丰度占总脂质0.5%以上的脂质物种数量。 横轴上的处理序号代表对应条件的参数，由低到高排列，这些参数包括：温度（25℃、30℃、40℃）、pH值（6.4、6.8、7.8）、NaCl浓度（3 g/L、10 g/L、25 g/L、60 g/L）、磷浓度（0.0005 mM、0.0015 mM、0.015 mM、1.5 mM）以及铵浓度（0.003 g/L、0.03 g/L、0.3 g/L）。 ## 图6 不同培养条件下所研究硫酸盐还原菌脂质组的醚/酯键脂质、极性头部基团、平均碳链长度与双键当量（double bond equivalents, DB）的适应性变化 A）二烷基链磷脂与四烷基链磷脂的比值，或(PE+PG)/CL比值，该比值通过每一类别的核心脂质总和计算得到。B）磷脂/非磷脂的对数比值，其中磷脂包含二甘油脂磷脂（PG与PE）以及CL。C）醚/酯键脂质的占比。携带DEGs的脂质中醚键的丰度基于其固有强度计算；而同时含醚键与酯键的脂质中醚键的丰度则通过醚键占比乘以强度的比值确定。例如，在CL-TriEG中，该脂质含有3条醚键链与1条酯键链，其醚链的丰度计算为0.75乘以其强度。D）不同培养条件下总脂质的平均DB值。E）不同培养条件下双链脂质的平均链长度。 星号表示当前条件与前一条件间的显著性差异（成对差异的Student t检验：*P < 0.05，**P < 0.01，***P < 0.001）。这些参数包括：温度（25℃、30℃、40℃）、pH值（6.4、6.8、7.8）、NaCl浓度（3 g/L、10 g/L、25 g/L、60 g/L）、磷浓度（0.0005 mM、0.0015 mM、0.015 mM、1.5 mM）以及铵浓度（0.003 g/L、0.03 g/L、0.3 g/L）。 ## 补充图S7 不同DB值（0-4）（A）与不同碳链长度（26-37、56-68）（B）的脂质的分数丰度。26至37的数值代表双链脂质的总碳原子数，56至68的数值则代表四链脂质（来自CL）的总碳原子数。不同颜色的处理序号代表对应条件的参数，由低到高排列。