Sondervorst Kaat, Nesporova Kristina, Herdman Matthew, Steemans Bart, Rosseels Joëlle, Govers Sander K
Department of Biology, KU Leuven, Leuven, Flanders, Belgium.
mSystems. 2025 Jul 22;10(7):e0020625. doi: 10.1128/msystems.00206-25. Epub 2025 Jun 10.
Phenotypic outcomes can be heavily affected by environmental factors. In this study, we exploited the previously observed nutrient dependency of cell biological phenotypic features captured by a cross-condition image-based profiling assay of deletion strains to examine this in more detail. We identified several general principles, including the existence of a spectrum of deviating phenotypes across nutrient conditions (i.e., from nutrient- or feature-specific to pleiotropic phenotypic deviations), limited conservation of phenotypic deviations across nutrient conditions (i.e., limited phenotypic robustness), and a subset of nutrient-independent phenotypic deviations (indicative of consistent genetic determinants of specific phenotypic features). In a subsequent step, we used this cross-condition data set to identify five genes of unknown function (, , , , and ), of which the deletion displayed either nutrient-independent phenotypic deviations or phenotypic similarities to genes of known function. These genes showed different levels of phylogenetic conservation, ranging from conserved across the tree of life () to only present in some genera of the Enterobacterales (). Analysis of the structural properties of the proteins encoded by these y-genes, identification of structural similarities to other proteins, and the examination of their subcellular localization yielded new insights into their contribution to cell morphogenesis, cell cycle progression, and cell growth. Together, our approach showcases how bacterial image-based profiling assays and data sets can serve as a gateway to reveal the function of uncharacterized proteins.
Despite unprecedented access to genomic information, predicting phenotypes based on genotypes remains notoriously difficult. One major confounding factor is the environment and its ability to modulate phenotypic outcomes. Another fact is that a large fraction of protein-coding genes in bacterial genomes remain uncharacterized and have no known function. In this work, we use a large-scale cross-condition image-based profiling dataset to characterize nutrient-dependent phenotypic variability of deletion strains and exploit it to provide insight into the cellular role of genes of unknown function. Through our analysis, we identified five genes of unknown function that we subsequently further characterized by examining their phylogenetic conservation, predicted structural properties and similarities, and their intracellular localization. Combined, this approach highlights the potential of cross-condition image-based profiling, which extracts many cell biological phenotypic readouts across multiple conditions, to better understand nutrient-dependent phenotypic variability and uncover protein function.
表型结果会受到环境因素的严重影响。在本研究中,我们利用先前通过基于图像的跨条件分析方法对缺失菌株进行细胞生物学表型特征分析时所观察到的营养依赖性,对这一现象进行了更深入的研究。我们确定了几个一般原则,包括在不同营养条件下存在一系列偏离的表型(即从营养或特征特异性到多效性表型偏差)、不同营养条件下表型偏差的保守性有限(即表型稳健性有限),以及一部分与营养无关的表型偏差(表明特定表型特征存在一致的遗传决定因素)。在后续步骤中,我们利用这个跨条件数据集鉴定了五个功能未知的基因(、、、和),缺失这些基因会表现出与营养无关的表型偏差或与已知功能基因的表型相似性。这些基因显示出不同程度的系统发育保守性,从在整个生命树中保守()到仅存在于肠杆菌科的某些属中()。对这些y基因编码的蛋白质的结构特性进行分析、鉴定与其他蛋白质的结构相似性以及检查它们的亚细胞定位,为它们在细胞形态发生、细胞周期进程和细胞生长中的作用提供了新的见解。总之,我们的方法展示了基于细菌图像的分析方法和数据集如何能够成为揭示未表征蛋白质功能的途径。
尽管获取基因组信息的途径空前,但基于基因型预测表型仍然非常困难。一个主要的混杂因素是环境及其调节表型结果的能力。另一个事实是,细菌基因组中很大一部分蛋白质编码基因仍然未被表征且功能未知。在这项工作中,我们使用一个大规模基于图像的跨条件分析数据集来表征缺失菌株的营养依赖性表型变异性,并利用它来深入了解功能未知基因的细胞作用。通过我们的分析,我们鉴定了五个功能未知的基因,随后通过检查它们系统发育保守性、预测的结构特性和相似性以及它们的细胞内定位对其进行了进一步表征。综合起来,这种方法突出了基于图像的跨条件分析的潜力,该方法可以在多个条件下提取许多细胞生物学表型读数,以更好地理解营养依赖性表型变异性并揭示蛋白质功能。