Quantitative phase imaging (QPI) has emerged as a valuable method for investigating cells and tissues. QPI operates on unlabelled specimens and, as such, is complementary to established fluorescence microscopy, exhibiting lower phototoxicity and no photobleaching. As the images represent quantitative maps of optical path length delays introduced by the specimen, QPI provides an objective measure of morphology and dynamics, free of variability due to contrast agents. Owing to the tremendous progress witnessed especially in the past 10–15 years, a number of technologies have become sufficiently reliable and translated to biomedical laboratories. Commercialization efforts are under way and, as a result, the QPI field is now transitioning from a technology-development-driven to an application-focused field. In this Review, we aim to provide a critical and objective overview of this dynamic research field by presenting the scientific context, main principles of operation and current biomedical applications. Over the past 10–15 years, quantitative phase imaging has moved from a research-driven to an application-focused field. This Review presents the main principles of operation and representative basic and clinical science applications.

Quantitative phase imaging in biomedicine

A system and methods for quantitative optical phase imaging of a sample. First second replica field of an image field are generated, characterized by a respective optical phase, cross-polarized and shifted in a shift direction transverse to a normal to the surface of the sample. The replica fields are Fourier transformed, the second replica field is retarded by four successive phase shifts, and, after inverse Fourier transforming, the first and second replica fields pass through an analyzer polarizer and superposing the first and second replica fields on a detector array to create four successive detector signals. The four successive detector signals are solved to derive a gradient of the optical phase of the image field, which may be integrated to obtain a quantitative phase image.

Gradient Light Interference Microscopy for 3D Imaging of Unlabeled Specimens

Digital holography (DH) has emerged as one of the most effective coherent imaging technologies. The technological developments of digital sensors and optical elements have made DH the primary approach in several research fields, from quantitative phase imaging to optical metrology and 3D display technologies, to name a few. Like many other digital imaging techniques, DH must cope with the issue of speckle artifacts, due to the coherent nature of the required light sources. Despite the complexity of the recently proposed de-speckling methods, many have not yet attained the required level of effectiveness. That is, a universal denoising strategy for completely suppressing holographic noise has not yet been established. Thus the removal of speckle noise from holographic images represents a bottleneck for the entire optics and photonics scientific community. This review article provides a broad discussion about the noise issue in DH, with the aim of covering the best-performing noise reduction approaches that have been proposed so far. Quantitative comparisons among these approaches will be presented.

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Strategies for reducing speckle noise in digital holography

Quantitative phase imaging (QPI) with its high-contrast images of optical phase delay (OPD) maps is often used for label-free single-cell analysis. Contrary to other imaging methods, sensitivity improvement has not been intensively explored because conventional QPI is sensitive enough to observe the surface roughness of a substrate that restricts the minimum measurable OPD. However, emerging QPI techniques that utilize, for example, differential image analysis of consecutive temporal frames, such as mid-infrared photothermal QPI, mitigate the minimum OPD limit by decoupling the static OPD contribution and allow measurement of much smaller OPDs. Here, we propose and demonstrate supersensitive QPI with an expanded dynamic range. It is enabled by adaptive dynamic range shift through a combination of wavefront shaping and dark-field QPI techniques. As a proof-of-concept demonstration, we show dynamic range expansion (sensitivity improvement) of QPI by a factor of 6.6 and its utility in improving the sensitivity of mid-infrared photothermal QPI. This technique can also be applied for wide-field scattering imaging of dynamically changing nanoscale objects inside and outside a biological cell without losing global cellular morphological image information.

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Adaptive dynamic range shift (ADRIFT) quantitative phase imaging.

Recent advances in deep learning have given rise to a new paradigm of holographic image reconstruction and phase recovery techniques with real-time performance. Through data-driven approaches, these emerging techniques have overcome some of the challenges associated with existing holographic image reconstruction methods while also minimizing the hardware requirements of holography. These recent advances open up a myriad of new opportunities for the use of coherent imaging systems in biomedical and engineering research and related applications.

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Deep learning in holography and coherent imaging.

High-throughput single-cell analysis is a challenging task. Label-free tomographic phase microscopy is an excellent candidate to perform this task. However, in-line tomography is very difficult to implement in practice because it requires a complex set-up for rotating the sample and examining the cell along several directions. We demonstrate that by exploiting the random rolling of cells while they are flowing along a microfluidic channel, it is possible to obtain in-line phase-contrast tomography, if smart strategies for wavefront analysis are adopted. In fact, surprisingly, a priori knowledge of the three-dimensional position and orientation of rotating cells is no longer needed because this information can be completely retrieved through digital holography wavefront numerical analysis. This approach makes continuous-flow cytotomography suitable for practical operation in real-world, single-cell analysis and with a substantial simplification of the optical system; that is, no mechanical scanning or multi-direction probing is required. A demonstration is given for two completely different classes of biosamples: red blood cells and diatom algae. An accurate characterization of both types of cells is reported, despite their very different nature and material content, thus showing that the proposed method can be extended by adopting two alternate strategies of wavefront analysis to many classes of cells.

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Tomographic flow cytometry by digital holography.

Diatoms are an ecologically relevant group of microalgae that are not commonly considered for bio-oil production even if they are responsible for massive blooms at sea. Seventeen diatom species were screened for their capacity to produce biomass and lipids, in relation to their growth rate. Triglyceride levels were also assessed as a preferential source of biofuels. Using statistical analysis, two centric diatoms, Thalassiosira weissflogii and Cyclotella cryptica, were selected as good candidates for oil production. Lipid levels significantly increased when the two diatoms were cultivated in a two-stage process under nitrogen limitation. The effect was less pronounced in cultures where silicon was reduced to 20% of the standard supply. Nitrogen limitation did not affect growth rates but led to lipid remodeling and de novo synthesis of triacylglycerols. Triacylglycerols in T. weissflogii and C. cryptica can account for up to 82% and 88% of total glycerolipids, thereby suggesting that the two species are promising candidates for large-scale experimentation for biofuel production.

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Potential of lipid metabolism in marine diatoms for biofuel production

The persistence of heavy metals (HMs) in the environment causes adverse effects to all living organisms; HMs accumulate along the food chain affecting different levels of biological organizations, from cells to tissues. HMs enter cells through transporter proteins and can bind to enzymes and nucleic acids interfering with their functioning. Strategies used by microalgae to minimize HM toxicity include the biosynthesis of metal-binding peptides that chelate metal cations inhibiting their activity. Metal-binding peptides include genetically encoded metallothioneins (MTs) and enzymatically produced phytochelatins (PCs). A number of techniques, including genetic engineering, focus on increasing the biosynthesis of MTs and PCs in microalgae. The present review reports the current knowledge on microalgal MTs and PCs and describes the state of art of their use for HM bioremediation and other putative biotechnological applications, also emphasizing on techniques aimed at increasing the cellular concentrations of MTs and PCs. In spite of the broad metabolic and chemical diversity of microalgae that are currently receiving increasing attention by biotechnological research, knowledge on MTs and PCs from these organisms is still limited to date.

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Microalgal Metallothioneins and Phytochelatins and Their Potential Use in Bioremediation.

Cell mortality is a key mechanism that shapes phytoplankton blooms and species dynamics in aquatic environments. Here we show that sterol sulfates (StS) are regulatory molecules of a cell death program in Skeletonema marinoi, a marine diatom-blooming species in temperate coastal waters. The molecules trigger an oxidative burst and production of nitric oxide in a dose-dependent manner. The intracellular level of StS increases with cell ageing and ultimately leads to a mechanism of apoptosis-like death. Disrupting StS biosynthesis by inhibition of the sulfonation step significantly delays the onset of this fatal process and maintains steady growth in algal cells for several days. The autoinhibitory activity of StS demonstrates the functional significance of small metabolites in diatoms. The StS pathway provides another view on cell regulation during bloom dynamics in marine habitats and opens new opportunities for the biochemical control of mass-cultivation of microalgae.

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Autoinhibitory sterol sulfates mediate programmed cell death in a bloom-forming marine diatom.

Accurate characterization of biomass constituents is a crucial aspect of research in the biotechnological application of natural products. Here we report an efficient, fast and reproducible method for the identification and quantitation of fatty acids and complex lipids (triacylglycerols, glycolipids, phospholipids) in microalgae under investigation for the development of functional health products (probiotics, food ingredients, drugs, etc.) or third generation biofuels. The procedure consists of extraction of the biological matrix by modified Folch method and direct analysis of the resulting material by proton nuclear magnetic resonance (1H NMR). The protocol uses a reference electronic signal as external standard (ERETIC method) and allows assessment of total lipid content, saturation degree and class distribution in both high throughput screening of algal collection and metabolic analysis during genetic or culturing studies. As proof of concept, the methodology was applied to the analysis of three microalgal species (Thalassiosira weissflogii, Cyclotella cryptica and Nannochloropsis salina) which drastically differ for the qualitative and quantitative composition of their fatty acid-based lipids.

Angela Sardo

Papers

Tomographic flow cytometry by digital holography.

Potential of lipid metabolism in marine diatoms for biofuel production

Microalgal Metallothioneins and Phytochelatins and Their Potential Use in Bioremediation.

Autoinhibitory sterol sulfates mediate programmed cell death in a bloom-forming marine diatom.

Composition and Quantitation of Microalgal Lipids by ERETIC 1H NMR Method