Understanding hyphal branching in Fusarium venenatum to design improved strains

这项合作提案旨在描述丝状真菌的分枝模式，以便对基因网络的功能和调控提供见解。这不仅将导致对许多丝状真菌菌丝分枝的分子机制的基本见解，还将帮助我们的工业合作伙伴提高工艺效率，确保Quorn继续成为市场上最可持续的非植物性肉类替代品之一。在20世纪50年代，S，在“绿色革命”之前，人们严重关注是否有足够的蛋白质来养活日益增长的全球人口。RANK Hovis McDouga(RHM)开始了一项寻找单细胞蛋白质来源的过程，该来源可以用小麦淀粉(或衍生的葡萄糖单体)发酵。这导致了一种镰刀菌的发现，这种镰刀菌具有正确的生长特性，能够继续加工。这种丝状真菌后来被归类为毒腐镰刀菌，小麦病原菌的姊妹种，这种丝状真菌在与鸡蛋蛋白混合、形成、烹饪和受控冷冻后，以一种具有良好感官特性的方式生长，使真菌蛋白细丝排列成纤维-凝胶复合体，赋予肉类般的质地。在真菌蛋白的产生过程中，发酵过程中会产生自发变异，分支速度更快，最终在发酵过程中上升到较高水平。从食品质构的角度来看，这些都是不可取的，因为它们会导致质地松脆，而不是肉质，因此发酵必须及早终止，导致生产效率较低，如果没有这些殖民地变体(也称为c-变体)是可能的。我们之前的工作已经对19个独立发酵的c-变异菌株的基因组进行了测序，并揭示了一组共同的基因集，这些基因在不同组合的c-变异菌株之间发生突变。我们现在希望验证这些基因中的哪些(以及在什么组合中)是导致c-变异表型的。这将帮助我们了解哪些基因负责控制菌丝生长和分枝，目前在大多数丝状真菌中是一个“未知的”。我们将使用机器学习方法的组合来验证我们关于哪些变异是重要的假设，这将使我们能够有效地对c变异分离株进行分组，以帮助基因识别。我们将研究每个突变分离株的基因表达扰动，结合“主动学习”方法，使我们能够确定基因表达网络的调控顺序。然后，我们将与Marlow Foods合作，了解发酵过程中突变事件的顺序，并结合超深种群水平基因组测序和数字液滴PCR技术跟踪商业发酵过程中个体突变的动态。我们还会问这种突变轨迹是否取决于选择用于发酵的菌株，因为它可能是目前的生产菌株比其他菌株更容易受到超分支变体的影响。最后，我们将把形态生长模型和基因表达网络联系起来，模拟不同基因扰动对生长和分枝过程的影响。这一点，与其他分析一起，将使我们能够观察基因调控网络的稳健性，并确定是否有机会通过增强对菌丝生长和分支系统如何运作和调节的机械洞察来提高菌株的稳健性。综上所述，这项工作将允许合理设计新的真菌蛋白菌株，提高生产效率，并确保可持续生产可扩展的肉类替代品。

This collaborative proposal aims to characterise branching patterns in filamentous fungi in order to provide insights into gene network function and regulation. This will not only lead to fundamental insights into the molecular mechanism of hyphal branching across many species of filamentous fungi, but will help our industrial partners improve process efficiencies, ensuring that Quorn continues to be one of the most sustainable, non-plant-based, meat alternatives on the market. In the 1950's, prior to the 'green revolution' there was serious concern about the availability of sufficient protein to feed a growing global population. Rank Hovis McDougal (RHM) began a process of searching for a single celled protein source that could be fermented using wheat starch (or derived glucose monomers). This led to the discovery of a Fusarium species, that has the correct growth properties that enabled onward processing. Later classified as Fusarium venenatum (Fv), a sister species to the wheat pathogen Fusarium graminearum, this filamentous fungus grew in a manner that had good organoleptic properties following mixture with egg albumen, forming, cooking and controlled freezing, which cause mycoprotein filaments to align as a fibre-gel composite conferring a meat-like texture .During the production of mycoprotein, spontaneous variants arise in the fermentation which branch more quickly and eventually rise to high levels in the fermentation process. These are undesirable from a food texture perspective as they lead to a crumbly, rather than a meaty texture and therefore fermentations must be terminated early, leading to less efficient production that would be possible without these colonial variants (also known as c-variants). Our previous work has sequenced 'c-variant' genomes from 19 independent fermentations and revealed a common set of genes that are mutated across c-variant isolates in different combinations. We now wish to verify which of these genes (and in what combination) are responsible for the c-variant phenotype. This will help us to understand which genes are responsible for controlling hyphal growth and branching, currently an 'unknown' in most filamentous fungi. We will validate our hypotheses about which variants are important by using a combination of machine-learning approaches which will allow us to effectively group c-variant isolates to aid with gene identification. We will look at gene expression perturbations across each mutant isolate, which in combination with 'active learning' approaches, allow us to identify the regulatory order of the gene expression network. We will, in collaboration with Marlow Foods then look to understand the order of mutational events within the fermentation process and with a combination of ultra-deep population-level genome sequencing and digital droplet PCR techniques track the dynamics of individual mutations within the commercial fermentation process. We will also ask if this mutational trajectory is dependent upon the strain which is chosen for fermentation, as it may be that the current production strain is more susceptible to hyper-branching variants than other strains. Finally, we will link together morphological growth models with gene expression networks to model the effects of different gene perturbations on the growth and branching process. This, along with other analyses will allow us to look at the robustness of the gene regulatory network and identify whether there are opportunities to improve the robustness of strains through enhanced mechanistic insight into how the hyphal growth and branching system functions and is regulated. Taken together this work will allow the rational design of new strains of mycoprotein, enhance production efficiency and ensure that scalable alternatives to meat can be sustainably produced.