Real-Time Monitoring of Wound Healing by Using Label-free Multiphoton Microscopy and the 3D Printed Live-cell Imaging Chamber

Session

Live and Functional Imaging Technologies Part 2

Authors

Haijiang Zhang (1), Che-Wei Chang (1), Rafael Camacho (1), Julia Fernandez-Rodriguez (1)

Affiliations

1. Centre of Cellular Imaging, Core Facilities, the Sahlgrenska Academy, University of Gothenburg, Sweden

Keywords

Multiphoton, second harmonic generation, SHG, collagen, wound healing, skin, autofluorescence, microfluidics

Abstract text

Abstract:

Current skin research typically relies on classical histopathological examination, either by studying the abnormality of the surface or vertical sections across the tissue. The drawbacks of this type of end-point experiment for studying wound healing are its destructive nature and that the outcome can only be rationalized retrospectively. To reliably observe the skin biology directly, the optimal experiment would require monitoring live tissue in real-time with an imaging system capable of recording cellular responses a few hundred mm under the skin surface. One-photon microscopy, although capable of achieving sub-micron resolution, generally can only image the surface of the skin tissue, due to the nature of the one-photon absorption/emission, and more importantly, the imaging limitations caused by the tightly packed keratinocyte cells. This study demonstrates that multiphoton laser scanning microscopy is a good imaging technique for monitoring wound healing in ex vivo skin models while using a 3D printed microfluidics chamber for keeping the tissue viable. Multiphoton microscopy is capable of deep tissue imaging down to ~300 μm and is able to monitor the cellular proliferation and collagen regeneration without adding external fluorescent markers, which could potentially interfere with native cellular functions. Further, the 3D printed microfluidics chamber we designed can be integrated into commercial microscopy incubation systems to create an artificial growth mini-environment for keeping tissue alive for prolonged periods of time. In this study, real-time monitoring of wound healing was achieved at the depth of ~300 μm during 3-7 days. 

Summary:

Skin is the largest human organ and acts as the primary defense barrier to the outside environment. However, it is far from being simply an inert shield; rather, it is a highly complex and well-structured integumentary system upholding homeostasis and immunologic defense responses. Any damage to the skin will possibly affect the whole organism if the healing process does not progress in a timely manner. Aside from the regular mechanical injury to the skin in daily life, fundamental questions surrounding wound healing, and how age or diseases such as diabetes affect wound healings need to be addressed with more advanced monitoring protocols. The focus on creating better treatments and medicine for repairing wounds more efficiently has accelerated in the past decade thanks to advancements in cellular imaging tools, in which the sub-micron resolution can now be easily achieved in most commercial light microscopes. Nevertheless, the real-time monitoring for wound healing has been challenging due to the reasons below: 

(1) Real-time monitoring is not easily achieved. In histopathological imaging techniques, the tissue needs to be fixed, sectioned, and then stained before visualization. This means that important morphological information might be lost in this destructive sample preparatory phase. Furthermore, in order to fully understand how cell motility and multiplication occur, it is necessary to monitor regenerative processes over time.

(2) Conventional one-photon imaging tools are not adequate for two main reasons: (A) Conventional light microscopy typically relies on external fluorescent labels to visualize specific cellular components. The main drawback is that these labels could potentially interfere with the wound healing process and mislead the conclusions. (B) Typically, one-photon microscopes can only image up to ~ 30 μm under the skin surface. Moreover, skin is mainly composed of an outermost epidermis that is tightly packed with several layers of keratinocytes, melanocytes, Langerhans cells, and immediately under that a deeper dermis that contains tough connective tissue, hair follicles, and sweat glands. Since the thickness of the epidermis is already at the range of ~ 100 μm, one-photon microscopy is not able to record how re-epithelization in deep dermis layers occurs.    

(3) Keeping skin tissue viable is challenging. While some ex vivo methods have been developed to understand how cell motility and proliferation occur, the main challenge is still to keep the tissue alive and fully functional over a long period of time. 

 This study overcomes all three main challenges by utilizing multiphoton microscopy for deep tissue imaging and a 3D-printed microfluidics chamber. Multiphoton microscopy proved two major advantages: label-free and deep-tissue imaging. Since light with a longer wavelength is able to penetrate deeper into the tissue, multiphoton microscopy uses a pulsed laser at the range of 800-1100 nm as the excitation source. In skin tissue, live cells and connecting tissue such as collagen and elastin generate autofluorescence. More importantly, collagen is also a strong second harmonic generation (SHG) emitter and therefore makes it possible to record how cells regenerate skin tissues in real-time without adding any exogenous fluorescence labels.   In order to observe wound healing, a wound with a 3 mm diameter and close to 400 mm depth was created on the 1 cm x 1 cm x ~ 0.8 cm skin tissue sample. The tissue was then placed in the live cell imaging microfluidics chamber and then imaged by an upright multiphoton microscope. Several Regions-of-Interest (450 x 450 μm²  with a 350 μm Z-stack) were recorded close to the wound and imaged every hour over the periods of 3-7 days. The time series of each Z-stack was then segmented into different cellular components by using machine learning algorithms. With this protocol, we are able to distinguish between epidermal keratinocytes, living keratinocytes, collagen, and elastin.