Chemical methods allow indirect measurement of biofilm components, through the use of dyes or fluorochromes that can adsorb or bind to cells or matrix components, or assessment of the cellular physiology of biofilms. For example, resazurin (93) and XTT [2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide inner salt] (94) have been used to determine the effect of phages against biofilms. Despite the widespread use of these methods, there is a lack of reproducibility associated with them. In addition, the fact that a standard protocol is not available makes the comparison of results among different studies difficult.
化学方法可通过使用可吸附或结合细胞或基质成分的染料或荧光染料来间接测量生物膜成分，或评估生物膜的细胞生理学。例如，Resazurin（93）和 XTT [2,3-双-（2-甲氧基-4-硝基-5-磺酸苯基）-2H-四氮唑-5-甲酰苯胺内盐] （94）已被用于确定噬菌体对生物膜的影响。尽管这些方法被广泛使用，但它们缺乏可重复性。此外，由于没有标准方案，因此很难比较不同研究的结果。
3.2.5. Microscopy methods.
3.2.5.显微镜方法。
Numerous microscopy-based imaging modalities are available to analyze biofilms; their pros and cons have been widely discussed elsewhere (72). Several of these approaches have already been used to examine phage-biofilm interactions, namely epifluorescence microscopy, CLSM (95), scanning electron microscopy (SEM) (96), field emission SEM (90), and atomic force microscopy (97). An optical system that allows simultaneous imaging of individual bacterial cells over a 36-mm2 field of view was recently developed (98). With this system, E. coli biofilms were observed in a detail never seen before, and new intracolony channels with an approximately 10-μm diameter were discovered (98).
有许多基于显微镜的成像模式可用于分析生物膜；它们的优缺点已在其他地方得到广泛讨论 ( 72)。其中几种方法已被用于研究噬菌体与生物膜的相互作用，即外荧光显微镜、CLSM（95）、扫描电子显微镜（SEM）（96）、场发射扫描电子显微镜（90）和原子力显微镜（97）。最近开发出一种光学系统，可在 36 毫米 2 视场内对单个细菌细胞同时成像（98）。利用该系统，可以观察到大肠杆菌生物膜前所未有的细节，并发现了直径约为 10 微米的新菌落内通道（98）。
For fluorescence microscopy, biofilm elements need to be marked with fluorescence probes. Microbial cells are usually stained with DAPI or LIVE/DEAD for viability. Components of the biofilm matrix can be marked with fluorescence-labeled lectins such as wheat germ agglutinin conjugated with different fluorophores. Recently, different fluorescence-based approaches were designed to study phage-biofilm interactions. For instance, Akturk et al. (99) designed bacteria-specific fluorescent probes based on phage proteins to discriminate between S. aureus and P. aeruginosa on dual-species biofilms. Another elegant approach is based on the use of fluorescence in situ hybridization (FISH). Although phageFISH was designed to detect Pseudoalteromonas using polynucleotide probes (100), more recent techniques using locked nucleic acid probes as an alternative to DNA probes proved to be very successful when applied on biofilms. These probes allow the discrimination of phage-infected cells and the visualization of their spatial distribution within single-species (20) or multi-species biofilms (36).
在荧光显微镜下，需要用荧光探针标记生物膜元件。微生物细胞通常用 DAPI 或 LIVE/DEAD 染色，以显示其活力。生物膜基质的成分可以用荧光标记凝集素（如与不同荧光团共轭的小麦胚芽凝集素）来标记。最近，人们设计了不同的基于荧光的方法来研究噬菌体与生物膜之间的相互作用。例如，Akturk 等人（99 年）设计了基于噬菌体蛋白的细菌特异性荧光探针，用于区分双物种生物膜上的金黄色葡萄球菌和铜绿假单胞菌。另一种优雅的方法是使用荧光原位杂交（FISH）。虽然噬菌体荧光原位杂交（FISH）是使用多核苷酸探针检测假单胞菌（100），但最近使用锁定核酸探针替代 DNA 探针的技术被证明在生物膜上应用非常成功。这些探针可以区分受噬菌体感染的细胞，并观察它们在单种（20）或多 种生物膜（36）中的空间分布。
3.2.6. Computational and mathematical models.
3.2.6.计算和数学模型。
Mathematical models hold great potential for the quantitative description of the population dynamics in a biofilm following phage predation. For example, Heilmann et al. (101) used stochastic spatial models to study the degree of bacterial susceptibility to phage predation. The authors showed that bacterial density or biofilm formation can produce refuges and edges in a self-organized manner (101). Laboratory experiments performed by Li et al. (102) demonstrated that, when phages find motile hosts, a well-delimited lysis zone is formed; when the authors applied a mathematical model, they observed that the lysis pattern was a consequence of local nutrient depletions and inhibition of bacterial and phage motility. In a similar approach, Ping et al. (103) showed that phage mobility requires virus particles to hitchhike with moving bacteria, which can simulate what happens on biofilms.
数学模型在定量描述噬菌体捕食后生物膜中的种群动态方面具有很大的潜力。例如，Heilmann 等人（101）利用随机空间模型研究了细菌易受噬菌体捕食的程度。作者的研究表明，细菌密度或生物膜的形成能以自组织的方式产生避难所和边缘（101）。Li 等人的实验室实验（102）表明，当噬菌体发现运动宿主时，就会形成一个界限分明的溶解区；当作者应用数学模型时，他们观察到溶解模式是局部营养耗竭以及细菌和噬菌体运动受抑制的结果。Ping 等人（103）用类似的方法表明，噬菌体的移动需要病毒颗粒搭上移动细菌的便车，这可以模拟生物膜上发生的情况。
A mathematical model developed by Eriksen et al. (104) predicted that biofilm microcolonies formed only by phage-sensitive bacteria have the ability to survive due to the bacterial growth throughout the microcolony, which can exceed the rate at which the cells are being killed by phage action. Using mathematical models and a computational framework, Simmons et al. (105) developed simulations that led to the conclusion that the equilibrium state of interaction between phages and biofilms is largely affected by the nutrient availability of biofilm cells, the infection likelihood per encounter, and the capacity of phages to diffuse through the biofilms. The authors also concluded that the biofilm matrix has a role in controlling these interactions by governing the extent to which prey and predator can coexist in the environment (105). In another study, a computer simulation of phage-host dynamics during biofilm development was applied based on experimental data obtained using S. aureus and the virulent phage phiIPLA-RODI (106). The results demonstrated that even small differences on pH evolution can dramatically affect the course of biofilm infection, suggesting that phage-host interactions can be tightly coordinated by different environmental signals (106). Very recently, Hartmann et al. (107) developed BiofilmQ, which is an innovative image cytometry software tool that allows automated and high-throughput quantification, analysis, and visualization of numerous biofilm properties. This tool is able to provide quantitative data from data analysis by scientists without programming skills to study biofilms and will provide new insights into phage-biofilm interaction.
Eriksen 等人 ( 104) 建立的数学模型预测，只有对噬菌体敏感的细菌形成的生物膜微菌落才有生存能力，因为整个微菌落的细菌生长速度可能超过噬菌体杀死细胞的速度。Simmons 等人（105）利用数学模型和计算框架进行了模拟，得出的结论是：噬菌体与生物膜之间相互作用的平衡状态在很大程度上受生物膜细胞的营养供应、每次相遇的感染可能性以及噬菌体在生物膜中的扩散能力的影响。作者还得出结论，生物膜基质通过调节猎物和捕食者在环境中共存的程度，在控制这些相互作用方面发挥作用（105）。在另一项研究中，根据使用金黄色葡萄球菌和毒性噬菌体 phiIPLA-RODI 获得的实验数据，对生物膜发展过程中的噬菌体-宿主动力学进行了计算机模拟 ( 106)。结果表明，即使是 pH 值演化的微小差异也会极大地影响生物膜感染的过程，这表明噬菌体与宿主的相互作用可以通过不同的环境信号紧密协调（106）。最近，Hartmann 等人（107）开发了 BiofilmQ，这是一种创新的图像细胞计量软件工具，可对生物膜的多种特性进行自动化、高通量量化、分析和可视化。没有编程技能的科学家也能利用该工具通过数据分析提供定量数据，从而研究生物膜，并为噬菌体与生物膜的相互作用提供新的见解。