Liquid-Liquid Phase Separation in Single Suspended Aerosol Microdroplets.

Liquid-liquid phase separation (LLPS) is ubiquitous in ambient aerosols. This specific morphology exerts substantial impacts on the physicochemical properties and atmospheric processes of aerosols, particularly on the gas-particle mass transfer, the interfacial heterogeneous reaction, and the surface albedo. Although there are many studies on the LLPS of aerosols, a clear picture of LLPS in individual aerosols is scarce due to the experimental difficulties of trapping a single particle and mimicking the suspended state of real aerosols. Here, we investigate the phase separation in individual contactless microdroplets by a self-constructed laser tweezer/Raman spectroscopy system. The dynamic transformation of the morphology of optically trapped droplets over the course of humidity cycles is detected by the time-resolved cavity-enhanced Raman spectra. The impacts of pH and inorganic components on LLPS in aerosols are discussed. The results show that the increasing acidity can enhance the miscibility between the hydrophilic and hydrophobic phases and decrease the separation relative humidity of aerosols. Moreover, the inorganic components also have various impacts on the aerosol phase state, whose influence depends on their different salting-out capabilities. It brings possible implications on the morphology of actual atmospheric particles, particularly for those dominated by internal mixtures of inorganic and organic components.

Sub-Cellular Dynamic Analysis of BGC823 Cells after Treatment with the Multi-Component Drug CKI Using Raman Spectroscopy.

Multi-component drugs (MCDs) can induce various cellular changes covering multiple levels, from molecular and subcellular structure to cell morphology. A "non-invasive" method for comprehensively detecting the dynamic changes of cellular fine structure and chemical components on the subcellular level is highly desirable for MCD studies. In this study, the subcellular dynamic processes of gastric cancer BGC823 cells after treatment with a multi-component drug, Compound Kushen Injection (CKI), were investigated using a homemade, high-resolution, confocal Raman spectroscopy (RS) device combined with bright-field imaging. The Raman spectra of the nucleus, cytoplasm and intracellular vesicles (0.4-1 µm) were collected simultaneously for each cell treated with CKI at different times and doses. The RS measurements showed that CKI decreased the DNA signatures, which the drug is known to inhibit. Meanwhile, the CKI-induced subcellular dynamic changes in the appearance of numerous intracellular vesicles and the deconstruction of cytoplasm components were observed and discussed. The results demonstrated that high-resolution subcellular micro-Raman spectroscopy has potential for detecting fine cellular dynamic variation induced by drugs and the screening of MCDs in cancer therapy.

Measurement of atmospheric nanoparticles: Bridging the gap between gas-phase molecules and larger particles.

Atmospheric nanoparticles are crucial components contributing to fine particulate matter (PM2.5), and therefore have significant effects on visibility, climate, and human health. Due to the unique role of atmospheric nanoparticles during the evolution process from gas-phase molecules to larger particles, a number of sophisticated experimental techniques have been developed and employed for online monitoring and characterization of the physical and chemical properties of atmospheric nanoparticles, helping us to better understand the formation and growth of new particles. In this paper, we firstly review these state-of-the-art techniques for investigating the formation and growth of atmospheric nanoparticles (e.g., the gas-phase precursor species, molecular clusters, physicochemical properties, and chemical composition). Secondly, we present findings from recent field studies on the formation and growth of atmospheric nanoparticles, utilizing several advanced techniques. Furthermore, perspectives are proposed for technique development and improvements in measuring atmospheric nanoparticles.

Correction: Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy.

Correction for 'Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy' by Teng Fang et al., Analyst, 2022, https://doi.org/10.1039/D2AN00024E.

Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy.

Nucleated red blood cells (NRBCs) as a type of rare cell present in an adult's peripheral blood is a concern in hematology, intensive care medicine and prenatal diagnostics. However, it is labor-intensive to screen such rare cells from real complex cell mixtures especially in a label-free way. Herein, we report a new label-free method that incorporates image recognition and Raman spectroscopy for fast recognition of the rare cells in blood. First, we identified unlabeled NRBCs based on both Raman signals of hemoglobin and nucleated morphology, and recorded their microscopic image characteristics which were different enough from other blood cells in unlabeled morphology. Then, two deep-learning algorithms of visual object detection, Faster RCNN and YOLOv3, were investigated for cell morphological recognition on a low-cost computer configuration, and YOLOv3 was demonstrated to be more competent for real-time detection despite slightly lower precision. Finally, several NRBCs were successfully found in maternal blood using this method, which verified the methodological feasibility. Thus, we believe such a labor-saving approach might inspire a new idea for detecting rare cells from complex cell mixtures in a label-free and computer-assisted way.

The relative humidity-dependent viscosity of single quasi aerosol particles and possible implications for atmospheric aerosol chemistry.

Viscosity is a fundamental physicochemical property of aerosol particles that influences chemical evolution, mass transfer rates, particle formation, etc. and also changes with ambient relative humidity (RH). However, the viscosity of real individual aerosol particles still remains less understood. Here, we developed a novel optical system based on dual optical tweezers to measure the viscosity of single suspending aerosol droplets under different RH conditions. In our experiment, a pair of quasi atmospheric aerosol droplets composed of organic and inorganic chemical substances were trapped and levitated by dual laser beams, respectively, and then collided and coalesced. The backscattering light signals and bright-field images of the dynamic coalescence process were recorded to infer the morphological relaxation time and the diameter of the composited droplet. Then, the viscosity of the droplet was calculated based on these measured values. The ambient RH of the aerosol droplets was controlled by varying the relative flow rates of dry and humidified nitrogen gas in a self-developed aerosol chamber. The viscosities of single aqueous droplets nebulized with solutes of sucrose, various sulfates and nitrates, and organic/inorganic mixtures were measured over the atmospheric RH range. Besides, the viscosities of the proxies of actual ambient aerosols in Beijing were investigated, which reasonably interpreted the aerosol chemistry transforming from sulfate dominating to nitrate dominating at the PM10 (particulate matter with an aerodynamic diameter of less than 10 µm) level in the last decade in Beijing. Furthermore, the hygroscopicity of droplets with a solute of organic/inorganic mixtures was researched to obtain a deep insight into the relationship between the viscosity and mass transfer process. Hence, we provide a robust approach for investigating the viscosity and hygroscopicity of the actual individual liquid PM10 aerosols.

Single-Cell Multimodal Analytical Approach by Integrating Raman Optical Tweezers and RNA Sequencing.

Single-cell analysis has become a state-of-art approach to heterogeneity profiling in tumor cells. Herein, we realize a kind of single-cell multimodal analytical approach by combining single-cell RNA sequencing (scRNA-seq) with Raman optical tweezers (ROT), a label-free single-cell identification and isolation technique, and apply it to investigate drug sensitivity. The drug sensitivity of human BGC823 gastric cancer cells toward different drugs, paclitaxel and sodium dichloroacetate, was distinguished in the conjoint analytical way including morphology monitoring, Raman identification, and transcriptomic profiling. Each individual BGC823 cancer cell was measured by Raman spectroscopy, then nondestructively isolated out by ROT, and finally RNA-sequenced. Our results demonstrate each analytical mode can reflect cell response to the drugs from different perspectives and is consistent and complementary with each other. Therefore, we believe the multimodal analytical approach offers an access to comprehensive characterizations of the unicellular complexity, which especially makes sense for studying tumor heterogeneity or a desired special cell from a mixture cell sample such as whole blood.

Rapid and accurate identification of marine microbes with single-cell Raman spectroscopy.

Rapid and accurate identification of individual microorganisms, such as pathogenic or unculturable microbes, is significant in microbiology. In this work, rapid identification of marine microorganisms by single-cell Raman spectroscopy (scRS) using one-dimensional convolutional neural networks (1DCNN) was explored. Here, single-cell Raman spectra of ten species of marine actinomycetes, two species of non-marine actinomycetes and E. coli (as a reference) were individually collected. Several common classification algorithms in chemometrics, including linear discriminant analysis with principal component analysis and a support vector machine, were applied to evaluate the 1DCNN performance based on the raw and pre-processed Raman spectra. 1DCNN showed superior performance on the raw data in terms of its accuracy and recall rate compared with other classification algorithms. Our investigation demonstrated that the scRS-integrating advanced 1DCNN classification algorithm provided a rapid and accurate approach for identifying individual microorganisms without time-consuming cell culture and sophisticated or specific techniques, which could be a useful methodology for discriminating the microbes that cannot be cultured under normal conditions, especially for 'biological risk'-related emergencies.

Nondestructive Identification and Accurate Isolation of Single Cells through a Chip with Raman Optical Tweezers.

Raman optical tweezers (ROT) as a label-free technique plays an important role in single-cell study such as heterogeneity of tumor and microbial cells. Herein we designed a chip utilizing ROT to isolate a specific single cell. The chip was made from a polydimethylsiloxane (PDMS) slab and formed into a gourd-shaped reservoir with a connected channel on a cover glass. On the chip an individual cell could be isolated from a cell crowd and then extracted with ∼0.5 µL of phosphate-buffered saline (PBS) via pipet immediately after Raman spectral measurements of the same cell. As verification, we separated four different type of cells including BGC823 gastric cancer cells, erythrocytes, lymphocytes, and E. coli cells and quantifiably characterized the heterogeneity of the cancer cells, leukocyte subtype, and erythrocyte status, respectively. The average time of identifying and isolating a specific cell was 3 min. Cell morphology comparison and viability tests showed that the successful rate of single-cell isolation was about 90%. Thus, we believe our platform could further couple other single-cell techniques such as single-cell sequencing and become a multiperspective analytical approach at the level of a single cell.

Laser trapping of Ag nanoparticles to enhance Raman spectroscopy in aqueous media.

Laser trapping (LT) of metallic nanoparticles (NPs) is an approach that has the potential to enhance Raman spectroscopy in aqueous media. In this paper, we report the LT of multiple 60-nm Ag NPs using a tightly focused 1064-nm Gaussian laser beam. The dynamic process (trapping and escaping) of the individual Ag NPs were recorded using a charge coupled device (CCD) camera in backscattering illumination mode. We found that up to four Ag NPs could be simultaneously trapped; however, they were unstable in the laser trap due to Brownian motion and NP-NP interactions. However, after mixing Ag NPs with Bacillus subtilis, more of the Ag NPs could be trapped together with the bacteria. Furthermore, a 532-nm solid-state laser beam was used to activate Raman scattering of the Ag NPs + Bacillus subtilis sample. Based on repetitive measurements, the Raman spectra of the Ag NPs + Bacillus subtilis sample were enhanced and the results were consistent. Our work suggests that LT of metallic NPs can be used to enhance Raman spectroscopy in aqueous media. We believe that the enhanced Raman spectroscopy will be useful for real-time biological assays.

Anti-Cancer Drug Sensitivity Assay with Quantitative Heterogeneity Testing Using Single-Cell Raman Spectroscopy.

A novel anti-cancer drug sensitivity testing (DST) approach was developed based on in vitro single-cell Raman spectrum intensity (RSI). Generally, the intensity of Raman spectra (RS) for a single living cell treated with drugs positively relates to the sensitivity of the cells to the drugs. In this study, five cancer cell lines (BGC 823, SGC 7901, MGC 803, AGS, and NCI-N87) were exposed to three cytotoxic compounds or to combinations of these compounds, and then they were evaluated for their responses with RSI. The results of RSI were consistent with conventional DST methods. The parametric correlation coefficient for the RSI and Methylthiazolyl tetrazolium assay (MTT) was 0.8558 ± 0.0850, and the coefficient of determination was calculated as R² = 0.9529 ± 0.0355 for fitting the dose⁻response curve. Moreover, RSI data for NCI-N87 cells treated by trastuzumab, everolimus (cytostatic), and these drugs in combination demonstrated that the RSI method was suitable for testing the sensitivity of cytostatic drugs. Furthermore, a heterogeneity coefficient H was introduced for quantitative characterization of the heterogeneity of cancer cells treated by drugs. The largest possible variance between RSs of cancer cells were quantitatively obtained using eigenvalues of principal component analysis (PCA). The ratio of H between resistant cells and sensitive cells was greater than 1.5, which suggested the H-value was effective to describe the heterogeneity of cancer cells. Briefly, the RSI method might be a powerful tool for simple and rapid detection of the sensitivity of tumor cells to anti-cancer drugs and the heterogeneity of their responses to these drugs.

Piconewton-Scale Analysis of Ras-BRaf Signal Transduction with Single-Molecule Force Spectroscopy.

Intermolecular interactions dominate the behavior of signal transduction in various physiological and pathological cell processes, yet assessing these interactions remains a challenging task. Here, this study reports a single-molecule force spectroscopic method that enables functional delineation of two interaction sites (≈35 pN and ≈90 pN) between signaling effectors Ras and BRaf in the canonical mitogen-activated protein kinase (MAPK) pathway. This analysis reveals mutations on BRaf at Q257 and A246, two sites frequently linked to cardio-faciocutaneous syndrome, result in ≈10-30 pN alterations in RasBRaf intermolecular binding force. The magnitude of changes in RasBRaf binding force correlates with the size of alterations in protein affinity and in α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-sensitive glutamate receptor (-R)-mediated synaptic transmission in neurons expressing replacement BRaf mutants, and predicts the extent of learning impairments in animals expressing replacement BRaf mutants. These results establish single-molecule force spectroscopy as an effective platform for evaluating the piconewton-level interaction of signaling molecules and predicting the behavior outcome of signal transduction.

Dynamic characterization of drug resistance and heterogeneity of the gastric cancer cell BGC823 using single-cell Raman spectroscopy.

Drug resistance and heterogeneous characteristics of human gastric carcinoma cells (BGC823) under the treatment of paclitaxel (PTX) were investigated using single-cell Raman spectroscopy (RS). RS of normal and drug-resistant BGC823 cells (DR-BGC823) were collected and analyzed using arithmetic, statistic and individual spectrum analysis. The dynamic effects of paclitaxel (PTX) in normal and DR-BGC823 cells were evaluated dynamically. The RS intensity changed with PTX over time and produced distinct different results for the two types of cells. The average RS intensities of the normal BGC823 cells initially decreased and then increased under PTX treatment after 24 hours. In contrast, upon exposure to PTX, the average intensity of the DR-BGC823 cells initially increased within 12 hours and then gradually decreased and approached a steady state. The temporal variation of the typical component in the cells was analyzed by comparing the ratios between Raman bands. More importantly, the heterogeneous characteristics of the BGC823 cells under PTX treatment were quantified and clustered using hierarchical trees combined with RS intensity changes. The 'outlier' cells related to drug resistance were discriminated. The heterogeneity of the normal BGC823 cells under drug treatment gradually appeared over time, and was evaluated with the eigenvalues of principal component analysis (PCA). Our study indicates that single-cell RS may be useful in systematically and dynamically characterizing the drug response of cancer cells at the single-cell level.

Myosin light chain kinase (MLCK) regulates cell migration in a myosin regulatory light chain phosphorylation-independent mechanism.

Myosin light chain kinase (MLCK) has long been implicated in the myosin phosphorylation and force generation required for cell migration. Here, we surprisingly found that the deletion of MLCK resulted in fast cell migration, enhanced protrusion formation, and no alteration of myosin light chain phosphorylation. The mutant cells showed reduced membrane tether force and fewer membrane F-actin filaments. This phenotype was rescued by either kinase-dead MLCK or five-DFRXXL motif, a MLCK fragment with potent F-actin-binding activity. Pull-down and co-immunoprecipitation assays showed that the absence of MLCK led to attenuated formation of transmembrane complexes, including myosin II, integrins and fibronectin. We suggest that MLCK is not required for myosin phosphorylation in a migrating cell. A critical role of MLCK in cell migration involves regulating the cell membrane tension and protrusion necessary for migration, thereby stabilizing the membrane skeleton through F-actin-binding activity. This finding sheds light on a novel regulatory mechanism of protrusion during cell migration.

RamanNet: a lightweight convolutional neural network for bacterial identification based on Raman spectra.

Raman spectroscopy combined convolutional neural network (CNN) enables rapid and accurate identification of the species of bacteria. However, the existing CNN requires a complex hyperparameters model design. Herein, we propose a new simple network architecture with less hyperparameter design and low computation cost, RamanNet, for rapid and accurate identifying of bacteria at the species level based on its Raman spectra. We verified that compared with the previous CNN methods, the RamanNet reached comparable results on the Bacteria-ID Raman spectral dataset and PKU-bacterial Raman spectral datasets, but using only about 1/45 and 1/297 network parameters, respectively. RamanNet achieved an average isolate-level accuracy of 84.7 ± 0.3%, antibiotic treatment identification accuracy of 97.1 ± 0.3%, and distinguished accuracy of 81.6 ± 0.9% for methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA) on the Bacteria-ID dataset, respectively. Moreover, it achieved an average accuracy of 96.04% on the PKU-bacterial dataset. The RamanNet model benefited from fewer model parameters that can be quickly trained even using CPU. Therefore, our method has the potential to rapidly and accurately identify bacterial species based on their Raman spectra and can be easily extended to other classification tasks based on Raman spectra.

Rapid and accurate identification of pathogenic bacteria at the single-cell level using laser tweezers Raman spectroscopy and deep learning.

We report a new method for the rapid identification of pathogenic bacterial species at the single-cell level that combines laser tweezers Raman spectroscopy (LTRS) with deep learning (DL). LTRS can accurately measure single-cell Raman spectra (scRS) without destroying and labeling cells. Based on the scRS data, DL rapidly and accurately identifies pathogenic bacteria. We measured scRS of 15 species bacteria using homemade LTRS. For each species, approximately, 160 cells from three different patients were measured, one patient's data were used as test set, and the rest after being augmented was used as training set. A residual network (ResNet) model, trained on the augmented training set, achieved an accuracy of 94.53% on the test set. Moreover, we applied gradient-weighted class activation mapping to visualize the proposed model. Finally, we demonstrated the advantages of ResNet over traditional machine-learning algorithms.

Erratum: Single-molecule force measurement via optical tweezers reveals different kinetic features of two BRaf mutants responsible for cardio-facial-cutaneous (CFC) syndrome: errata.

We correct the omission of the construct and protein purification method in our recent paper [Biomed. Opt. Express 4(12), 2835-2845 (2013)].[This corrects the article on p. 2835 in vol. 4, PMID: 24409384.].

Single-molecule force measurement via optical tweezers reveals different kinetic features of two BRaf mutants responsible for cardio-facial-cutaneous (CFC) syndrome.

BRaf (B- Rapid Accelerated Fibrosarcoma) protein is an important serine/threonine-protein kinase. Two domains on BRaf can independently bind its upstream kinase, Ras (Rat Sarcoma) protein. These are the Ras binding domain (RBD) and cysteine-rich-domain (CRD). Herein we use customized optical tweezers to compare the Ras binding process in two pathological mutants of BRaf responsible for CFC syndrome, abbreviated BRaf (A246P) and BRaf (Q257R). The two mutants differ in their kinetics of Ras-binding, though both bind Ras with similar increased overall affinity. BRaf (A246P) exhibits a slightly higher Ras/CRD unbinding force and a significantly higher Ras/RBD unbinding force versus the wild type. The contrary phenomenon is observed in the Q257R mutation. Simulations of the unstressed-off rate, koff (0), yield results in accordance with the changes revealed by the mean unbinding force. Our approach can be applied to rapidly assess other mutated proteins to deduce the effects of mutation on their kinetics compared to wild type proteins and to each other.

Mechanical property analysis of stored red blood cell using optical tweezers.

The deformation of human red blood cells subjected to direct stretching by optical tweezers was analyzed. The maximum force exerted by optical tweezers on the cell via a polystyrene microbead 5microm in diameter was 315pN. Digital image correlation (DIC) method was introduced to calculate the force and the deformation of the cell for the first time. Force-extension relation curves of the biconcave cell were quantitatively assessed when erythrocytes were stored in Alsever's Solution for 2 days, 5 days, 7 days and 14 days respectively. Experiment results demonstrated that the deformability of red blood cells was impaired with the stored time.