Characterizing and identifying cells in multicellular in vitro models remain a substantial challenge. Here, we utilize hyperspectral confocal Raman microscopy and principal component analysis coupled with linear discriminant analysis to form a label-free, noninvasive approach for classifying bone cells and osteosarcoma cells. Through the development of a library of hyperspectral Raman images of the K7M2-wt osteosarcoma cell lines, 7F2 osteoblast cell lines, RAW 264.7 macrophage cell line, and osteoclasts induced from RAW 264.7 macrophages, we built a linear discriminant model capable of correctly identifying each of these cell types. The model was cross-validated using a k-fold cross validation scheme. The results show a minimum of 72% accuracy in predicting cell type. We also utilize the model to reconstruct the spectra of K7M2 and 7F2 to determine whether osteosarcoma cancer cells and normal osteoblasts have any prominent differences that can be captured by Raman. We find that the main differences between these two cell types are the prominence of the β-sheet protein secondary structure in K7M2 versus the α-helix protein secondary structure in 7F2. Additionally, differences in the CH2 deformation Raman feature highlight that the membrane lipid structure is different between these cells, which may affect the overall signaling and functional contrasts. Overall, we show that hyperspectral confocal Raman microscopy can serve as an effective tool for label-free, nondestructive cellular classification and that the spectral reconstructions can be used to gain deeper insight into the differences that drive different functional outcomes of different cells.
Remote assessment of physiological parameters has enabled patient diagnostics without the need for a medical professional to become exposed to potential communicable diseases. In particular, early detection of oxygen saturation, abnormal body temperature, heart rate, and/or blood pressure could affect treatment protocols. The modeling effort in this work uses an adding-doubling radiative transfer model of a seven-layer human skin structure to describe absorption and reflection of incident light within each layer. The model was validated using both abiotic and biotic systems to understand light interactions associated with surfaces consisting of complex topography as well as multiple illumination sources. Using literature-based property values for human skin thickness, absorption, and scattering, an average deviation of 7.7% between model prediction and experimental reflectivity was observed in the wavelength range of 500-1000 nm.
To address challenges in early detection of pond pests, we have extended a spectroradiometric monitoring method, initially demonstrated for measurement of pigment optical activity and biomass, to the detection of algal competitors and grazers. The method relies upon measurement and interpretation of pond reflectance spectra spanning from the visible into the near-infrared. Reflectance spectra are acquired every 5 min with a multi-channel, fiber-coupled spectroradiometer, providing monitoring of algal pond conditions with high temporal frequency. The spectra are interpreted via numerical inversion of a reflectance model, in which the above-water reflectance is expressed in terms of the absorption and backscatter coefficients of the cultured species, with additional terms accounting for the pigment fluorescence features and for the water-surface reflection of sunlight and skylight. With this method we demonstrate detection of diatoms and the predator Poteriochromonas in outdoor cultures of Nannochloropsis oceanica and Chlorella vulgaris, respectively. The relative strength of these signatures is compared to microscopy and sequencing analysis. Spectroradiometric detection of diatoms is then further assessed on beaker-contained mixtures of Microchloropsis salina with Phaeodactylum tricornutum, Thalassiosira weissflogii, and Thalassiosira pseudonana, respectively, providing an initial evaluation of the sensitivity and specificity of detecting pond competitors.
Autophagy is a natural, regulated cellular process that "cleans up" cellular debris by degrading and recycling dysfunctional proteins. There is a high potential impact of exploiting the benefits of autophagy to complement existing treatments, but little has been done to date on bacterial pathogens of defense concern such as Burkholderia pseudomallei, a highly virulent Select Agent pathogen that is intrinsically resistant to most classes of antibiotics. Assessment of autophagy in the context of infection typically requires use of multiple technologies in combination (e.g., Western analysis paired with microscopy or flow cytometry) as applied to heterogeneous populations of cells. To address this, we have developed a dual target reporter cell line (RAW264.7 LC3-BFP:mPlum, GFP-RelA) that enables concurrent visualization of infection and autophagy induction. We assessed the effect of clinically approved small molecule inducers of autophagy on infection by Burkholderia thailendensis, a closely related but less virulent surrogate for B. pseudomallei. The reporter cells were first infected with a B. thailendensis strain that constitutively expresses GFP, then treated with one of four known autophagy inducers (rapamycin, niclosamide, bromhexine HC1, or flubendazole) for 4 hours. Confocal fluorescence imaging was used to quantify autophagy stimulation at the single cell level. Autophagy maturation was observed as a decrease in BFP LC3 puncta with a concurrent increase in mPlum LC3 puncta. B. thailendensis infection was assessed by monitoring translocation of GFP-RelA (an NFkB subunit) into the nucleus and through quantitating the intracellular bacterial presence in single cells. Preliminary results indicate that bromhexine HC1 and niclosamide may hinder B. thailendensis' ability to replicate intracellularly and reduce overall bacterial survival.
Genome editing technologies, particularly those based on zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and CRISPR (clustered regularly interspaced short palindromic repeat DNA sequences)/Cas9 are rapidly progressing into clinical trials. Most clinical use of CRISPR to date has focused on ex vivo gene editing of cells followed by their re-introduction back into the patient. The ex vivo editing approach is highly effective for many disease states, including cancers and sickle cell disease, but ideally genome editing would also be applied to diseases which require cell modification in vivo. However, in vivo use of CRISPR technologies can be confounded by problems such as off-target editing, inefficient or off-target delivery, and stimulation of counterproductive immune responses. Current research addressing these issues may provide new opportunities for use of CRISPR in the clinical space. In this review, we examine the current status and scientific basis of clinical trials featuring ZFNs, TALENs, and CRISPR-based genome editing, the known limitations of CRISPR use in humans, and the rapidly developing CRISPR engineering space that should lay the groundwork for further translation to clinical application.
The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) ribonucleoprotein (RNP) complex is an RNA-guided DNA-nuclease that is part of the bacterial adaptive immune system. CRISPR/Cas9 RNP has been adapted for targeted genome editing within cells and whole organisms with new applications vastly outpacing detection and quantification of gene-editing reagents. Detection of the CRISPR/Cas9 RNP within biological samples is critical for assessing gene-editing reagent delivery efficiency, retention, persistence, and distribution within living organisms. Conventional detection methods are effective, yet the expense and lack of scalability for antibody-based affinity reagents limit these techniques for clinical and/or field settings. This necessitates the development of low cost, scalable CRISPR/Cas9 RNP affinity reagents as alternatives or augments to antibodies. Herein, we report the development of the Streptococcus pyogenes anti-CRISPR/Cas9 protein, AcrIIA4, as a novel affinity reagent. An engineered cysteine linker enables covalent immobilization of AcrIIA4 onto glassy carbon electrodes functionalized via aryl diazonium chemistry for detection of CRISPR/Cas9 RNP by electrochemical, fluorescent, and colorimetric methods. Electrochemical measurements achieve a detection of 280 pM RNP in reaction buffer and 8 nM RNP in biologically representative conditions. Our results demonstrate the ability of anti-CRISPR proteins to serve as robust, specific, flexible, and economical recognition elements in biosensing/quantification devices for CRISPR/Cas9 RNP.