2D In Vitro Disease Modeling with FluidFM


Explore how 2D In Vitro disease modeling can benefit from the FluidFM technology.

Current challenges in In Vitro disease modeling

In vitro disease models are one of the starting points in both biological and medical research. With disease modeling, scientists can gain greater insight into mechanisms of a range of human diseases and develop new and improved therapies or diagnostics. Disease models can be produced via traditional 2D in vitro cultures based on animal cells or via in vivo-like 3D cell culture models, such as organoids, spheroids, or tissue models to mimic disease in a more physiologically relevant environment. [1]

Ideally, an in vitro disease model would be established from human diseased tissue that can demonstrate relevant degenerative mechanisms, but the access to such tissues remains a challenge for many researchers. Consequently, at the present time, for many infectious human diseases, medical research predominantly relies on having appropriate animal model systems to study disease states and to develop therapies.

Applications of In Vitro Disease Modeling

In vitro models have been employed widely to investigate many parts of the human organism, for blood-brain barrier [2], the study of osteoarthritis [3], myocardial tissue [4], myocardial ischemic injury [5], paroxysmal supraventricular tachycardia [6], Murine middle ear epithelium [7], Alzheimer's disease [8], thrombosis [9], vascular inflammation [10], and for different kinds of cancer [11].

Despite the great advances achieved in the development of in vitro disease models in animals, many of these models fail to faithfully describe the human body. Additionally, the identification of critical cellular and molecular contributors to disease remains a challenge. Lastly, with whole-animal models, there are limited ways to vary independently cellular and molecular contributors. [12] With those limitations, researchers proposed different ways to generate reliable and robust disease models. 

Cutting-edge solutions for a better representation of the human body.

A first step towards achieving a better representation of the human body in 2D in vitro cell culture, came with the use of single-cell analysis methods compared to batch analysis methods to gain a greater representation of cellular heterogeneity. Batch cell analysis methods operating on pooled cells provide a vast amount of biological information, but the averaging employed in the pooling process does not give a sufficiently detailed evaluation of the single cell. Information such as cell-to-cell differences and cellular heterogeneity can be completely missed. Thereby, with the improvement of single-cell manipulation platforms and technologies, new milestones could be achieved in various applications of in vitro disease modeling.

For instance, the development of cell transfection methods towards non-destructive delivery methods directly into the nucleus of an individual cell, and performed with the FluidFM technology, allowed researchers to significantly improve cell viability and therefore, experimental throughput and efficiency.  Oppositely, the ability to extract intracellular content directly from the cytoplasm or nucleus, without disrupting the cell viability - the single-cell biopsy approach, opened new doors in single-cell multi-omics. This innovation brought the temporal dimension to transcriptomics with sequential profiling of a single cell’s transcriptome.


The second measure taken by scientists to compensate the lack of resemblance to human body, originated from the creation of 3D in vitro disease models.  More specifically, stem cells-derived 3D organoid systems provide a unique way to examine mechanisms ranging from organ development to homeostasis and disease. Because organoids develop according to intrinsic developmental programs, the resultant tissue morphology recapitulates organ architecture with remarkable fidelity. Furthermore, the fact that these tissues can be derived from human progenitors allows for the study of uniquely human processes and disorders. [13] 

In the organoids research, scientists have exploited the potential of Induced Pluripotent Stem Cells (iPSCs) to produce such systems. However, differentiating iPSCs to generate stage-specific and homogeneous cell types that are relevant to the disease, is still a challenge. [14] A significant aspect of that relies on the development of in vitro assays to study the cellular function.  In vitro assays require custom and stable cell lines. An effective and reproducible cell line development relies on the use of cell transfection methods that can reliably and efficiently bring gene editing tools such as CRISPR Cas9 complexes, directly into the nucleus without killing the cell. 

Among current cell transfection methods, the delivery of soluble compounds directly into the nucleus by nano-injection, presents many advantages for precision genome engineering. As an example, the direct intra-nuclear injection capability of the FluidFM OMNIUM, provides a very gentle and efficient transfection method. As the insertion of a FluidFM probe does not compromise cell viability, it can even be used for injecting plasmids, gRNAs or CRISPR-complexes directly into the nucleus of many hard-to-transfect cells with exceptional viability, including stem cells, primary cells and neurons. 

Altogether, the FluidFM technology could bring important benefits to tackle the current limitations of in vitro disease modeling.

Benefits of FluidFM for In Vitro Disease Modeling

Gentle vector-free cell transfection 

through direct intra-nuclear delivery of RNP complexes for high HDR efficiency and reduced off-targets.

Gentle Cytoplasmic Biopsy Extraction 

for further downstream analysis to obtain a more refined understanding of the complex mechanism underlining tissue homeostasis, stem cell identity, and the pathophysiology of diseases. 

Related Resources

References

[1] Nikolic, Milica, Tijana Sustersic, and Nenad Filipovic. "In vitro models and on-chip systems: Biomaterial interaction studies with tissues generated using lung epithelial and liver metabolic cell lines." Frontiers in bioengineering and biotechnology 6 (2018): 120.

[2] Ogunshola, O. O. (2011). In vitro modeling of the blood-brain barrier: simplicity versus complexity. Curr. Pharmaceut. Design 17, 2755–2761. doi: 10.2174/138161211797440159

[3] Johnson, C. I., Argyle, D. J., and Clements, D. N. (2016). In vitro models for the study of osteoarthritis. Vet. J. 209, 40–49. doi: 10.1016/j.tvjl.2015.07.011

[4] Vunjak Novakovic, G., Eschenhagen, T., and Mummery, C. (2014). Myocardial tissue enginreeing: in vitro models. Cold Spring Harb. Perspect. Med. 4:a014076. doi: 10.1101/cshperspect.a014076

[5] Tumiati, L. C., Mickle, D. A. G., Weisel, R. D., Williams, W. G., and Li, R.K. (1994). An in vitro model to study myocardial ischemic injury. J. Tissue Cult. Methods 16, 1–9. doi: 10.1007/BF01404830

[6] Wit, A. L., Bruce, N. G., and Damato, A. N. (1971). An in vitro model of paroxymal supraventricular tachycardia. Circulation 43, 862–875. doi: 10.1161/01.CIR.43.6.862

[7] Mulay, A., Akram, K. M., Williams, D., Armes, H., Russell, C., Hood, D., et al. (2016). An in vitro model of murine middle ear epithelium. Dis. Models Mech. 9, 1405–1417. doi: 10.1242/dmm.026658

[8] Stoppelkamp, S., Bell, H. S., Palacios-Filardo, J., Shewan, D. A., Riedel, G., and Platt, B. (2011). In vitro modelling of Alzheimer's disease: degeneration and cell death induced by viral delivery of amyloid and tau. Exp. Neurol. 229, 226–237. doi: 10.1016/j.expneurol.2011.01.018

[9] Zhang, Y. S., Oklu, R., and Albadawi, H. (2017). Bioengineered in vitro models of thrombosis: methods and techniques. Cardiovasc. Diagn. Ther. 7:3. doi: 10.21037/cdt.2017.08.08

[10] Ahluwalia, A., Misto, A., Vozzi, F., Magliaro, C., Mattei, G., Marescotti, M. C., et al. (2018). Systemic and vascular inflammation in an in-vitro model of central obesity. PLoS ONE. 13:e0192824. doi: 10.1371/journal.pone.0192824

[11] Katt, M. E., Placone, A. L., Wong, A. D., Xu, Z. S., and Searson, P. C. (2016). In vitro tumor models: advantages, disadvantages, variables, and selecting the right platform. Front. Bioeng. Biotechnol. 4:12. doi: 10.3389/fbioe.2016.00012

[12] Benam, Kambez H., et al. "Engineered in vitro disease models." Annual Review of Pathology: Mechanisms of Disease 10 (2015): 195-262.

[13] Lancaster, Madeline A., and Meritxell Huch. "Disease modelling in human organoids." Disease models & mechanisms 12.7 (2019): dmm039347.

[14] Dutta, Devanjali, Inha Heo, and Hans Clevers. "Disease modeling in stem cell-derived 3D organoid systems." Trends in molecular medicine 23.5 (2017): 393-410.