Label-free Technology Research Articles

Electrical characteristics of cells with electrical impedance spectroscopy

Bioelectrical impedance spectroscopy is a noninvasive, label-free and quantitative detection technology, which has great advantages in the physiological and pathological analysis of biological cells and tissues. In this paper, the relationship between the electrical properties of a single cell and its structure is studied by numerical simulation. Moreover, experiments are conducted to verify the simulation results. For simulation, three single cell models are used to express its structure. Among of the three models, No Shell Model (NS) is proposed in this paper to study the influence of cell membrane on bioelectrical impedance spectroscopy. In addition, the effects of cell type, cell membrane and cell nucleus on its electrical properties are studied by simulation based on Single Shell Model (SS) and Two Shell Model (TS). The simulation results show that: 1) the electrical characteristics of cells can reflect its structure, therefore, the cell type can be accurately distinguished by its electrical characteristics; 2) the high frequency part of the Cole-Cole Plot is caused by ionic polarization of cytoplasm or extracellular fluid, and the low frequency part of the Cole-Cole Plot is caused by interface polarization between cell membrane and the extracellular fluid; 3) the influence of cell nucleus size on impedance measurement is mainly in the low frequency range, which is caused by the polarization of the interface between cell nucleus and intracellular fluid, and when the nucleocytoplasmic ratio is less than 0.25, the effect of nuclear size on impedance analysis could be ignored. Finally, an experiment was conducted on 20% yeasts suspension with different activity to verify the simulation results. It is known that the cell membranes of dead yeasts are destroyed, however, living yeasts have completed cell structures. The structure difference between living and dead yeast is distinguished by electrical impedance spectroscopy through numerical simulation. The experimental results are consistent with the simulation results, which verifies the fact that the high frequency part of the Cole-Cole Plot is caused by ionic polarization of cytoplasm or extracellular fluid, and the low frequency part of the Cole-Cole Plot is caused by interface polarization between cell membrane and the extracellular fluid.

A thin-film interferometry-based label-free immunoassay for the detection of daratumumab interference in serum protein electrophoresis

BackgroundDaratumumab (DARA) is a fully human anti-CD38 IgG1-κ monoclonal antibody drug used in the treatment of multiple myeloma (MM). While serum protein electrophoresis (SPEP) is an important assay for diagnosis and monitoring of patients with MM, DARA can appear in the γ-region as a single band and interfere with the interpretation of SPEP results. An approach to detect the interference is measuring the quantity of DARA in serum samples and assessing its impact on SPEP results. Immunoassays based on label-free technologies, i.e. label-free immunoassays (LFIA’s), can achieve real-time immunometric measurement without attaching a reporter molecule (enzyme, fluorophore, etc.) to the immunocomplex. The recorded time course of the immunocomplex formation allows for quantitation on initial binding rate, which facilitates rapid measurement within a few minutes. Based on the thin-film interferometry (TFI) technology, a rapid LFIA was established for the quantitation of DARA in serum samples. MethodsThe TFI-based LFIA for DARA was validated for imprecision (CV), accuracy, limit of quantitation (LOQ), and analytical measurement range (AMR). Interference to the LFIA was evaluated using a group of protein samples, as well as hemolytic, lipemic, and icteric clinical samples. ResultsThe precision of the TFI-based LFIA’s for DARA ranged from 6.5% to 10.7% (within-run CV), and 7.4% to 11.6% (between-run CV), with a bias of −2.1% to 10.1%. The LOQ was 10 μg/ml (n = 4, CV 9.8%), with an AMR ranging from the LOQ to 1000 μg/ml. The LFIA was used to measure 37 patient samples submitted for SPEP testing. The LFIA results were 100% consistent with the history of DARA use as documented in the medical record. ConclusionsThe TFI-based LFIA was successful at accurately identifying DARA in serum samples and can be used to identify DARA interference in SPEP testing. This work demonstrates the applicability of label-free technologies, particularly the TFI technology, to clinical diagnostic needs. Given the simplicity and the speed of the testing process, the TFI technology provides a unique testing approach for the measurement of proteins in clinical samples.

Ultra-low HIV-1 p24 detection limits with a bioelectronic sensor

Early diagnosis of the infection caused by human immunodeficiency virus type-1 (HIV-1) is vital to achieve efficient therapeutic treatment and limit the disease spreading when the viremia is at its highest level. To this end, a point-of-care HIV-1 detection carried out with label-free, low-cost, and ultra-sensitive screening technologies would be of great relevance. Herein, a label-free single molecule detection of HIV-1 p24 capsid protein with a large (wide-field) single-molecule transistor (SiMoT) sensor is proposed. The system is based on an electrolyte-gated field-effect transistor whose gate is bio-functionalized with the antibody against the HIV-1 p24 capsid protein. The device exhibits a limit of detection of a single protein and a limit of quantification in the 10 molecule range. This study paves the way for a low-cost technology that can quantify, with single-molecule precision, the transition of a biological organism from being “healthy” to being “diseased” by tracking a target biomarker. This can open to the possibility of performing the earliest possible diagnosis.

Abstract A025: Comparative analysis of proteomic/transcriptomic profiles of a panel of GC-PDXs

Abstract Background: Cancers are heterogeneous diseases, requiring individualized treatment approaches and relying on predictive biomarkers. Gastric carcinoma (GC), a common cancer with high fatality, particularly in East Asia, urgently needs effective treatment options, particularly targeted therapy. Patient-derived xenografts (PDXs) are widely accepted as predictive models for translational research, including identifying predictive biomarkers to guide GC-treatment (Zhang et al., 2013). The comprehensive annotation of PDXs pathologically, genomically and proteomically, at baseline and/or upon treatment (pharmacodynamics, or PD), are essential for biomarker discovery and validation. We previously described establishment of a panel of GC-PDX with transcriptome annotation and utilized these models for biomarker discovery predictive of the cetuximab response (Zhang et al., 2013). The present study aims to comparing the genomic and proteomic profiles of the GC-PDX panel and their, usage in translational research. Method. 48 GC-PDX tumor are subjected to transcriptome (RNASeq) sequencing and whole proteomic analysis using high-throughput label-free MS-based technology. We calculate spearman’s correlation coefficient (cc) between relative protein abundance metric (ifot) and mRNA expression metric (FPKM) per proteomic datasets and RNASeq datasets, respectively, to assess their consistent/differential features. We also tested an integrated -omics approach by DIABLO algorithm (Singh et al., 2017) for predictive biomarker discovery using mouse clinical trial data. Results. The correlation between mRNA and protein abundance was moderate (Spearman’s cc~0.55) consistent across all tested PDXs. Genes with high mRNA expression levels have weaker correlations with their corresponding protein abundance. This could be attributed to stronger post-transcriptional control on protein expression for these highly transcribed genes. Gene ontology (GO) over representation analysis were conducted for two subsets of genes: 1) ribosome and cadherin binding related proteins that are highly expressed at both mRNA and protein level, while 2) histones and other DNA binding genes have high protein abundance but low mRNA expression. We also conducted predictive biomarker analysis using the cetuximab (an EGFR inhibitor) GC-PDX trial data, where we previously demonstrated high correlation between EGFR mRNA expression and sensitivity to cetuximab. Although EGFR protein abundance is positively correlated with cetuximab efficacy, the correlation seems weaker than for their mRNA counterpart in this case. We also used the DIABLO algorithm for the integration of both proteomics and transcriptome data, which aims to identify a multi-omics signature that is maximally correlated across data types. A signature including 10-mRNA expression/5-protein abundance has been identified, with high inter data type correlation (0.94)/good discrimination power. Conclusion. The variability of protein abundance can be partially explained by mRNA level, however, post-transcriptional regulation could play important role on protein expression especially for highly transcribed genes. Proteomics data may provide complimentary information to transcriptome data for predictive biomarker analysis. Citation Format: Binchen Mao, Sheng Guo, Bonnie Xiaobo Chen, Davy Xuesong Ouyang, Henry Li. Comparative analysis of proteomic/transcriptomic profiles of a panel of GC-PDXs [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A025. doi:10.1158/1535-7163.TARG-19-A025

Label-free small molecule probe and target discovery of traditional Chinese medicine

Target discovery is the core of elucidating the mechanism of traditional Chinese medicine( TCM),and it is also the key to correlate the chemical composition and pharmacological action of TCM. The traditional target screening methods such as the activitybased probe profiling,affinity chromatography,and protein microarray are commonly used in the past,however,which are limited in TCM due to the complexity of small molecules existed in the herbal medicine. The label-free small molecule probe is a recently well-applied technology in the target discovery of natural products,which is characterized by discovering the small molecule-protein ligation without any structural modification at the ligands,and is therefore suitable to the complex chemical constituents in TCM. Furthermore,this method is conducted on the basis of proteome,which is advanced in the discovery of new or multiple target proteins of TCM. Owing to the potential of label-free probe in the target discovery of TCM,its analytical principle,application status,and general protocol were reviewed in this paper. The label-free probe technology is anticipated to accelerate the mechanism-uncovering of TCM.

Plasma membrane proteome analyses of Arabidopsis thaliana suspension-cultured cells during cold or ABA treatment: Relationship with freezing tolerance and growth phase

Cold acclimation (CA) and abscisic acid (ABA) treatments affected freezing tolerance of Arabidopsis thaliana suspension-cultured cells: cells at the lag and log phases increased their freezing tolerance but cells at the stationery phase rather decreased after the treatments. To further characterize the differential responses of the cells to these treatments depending on growth phase, plasma membrane (PM) proteome were analyzed using label-free protein quantification technology. Abundance of 841 proteins changed during the progression of growth phase, CA and/or ABA treatment. Among them, 392 proteins changed in their abundance in cells during growth phase progression and were categorized into various functional groups, suggesting changes in physiological characteristics of the PM depending on the growth phase. Comparison of CA- and ABA-responsive proteins indicated that ABA is one of the important signals for PM proteome changes in response to CA, but multiple signals are required for the response of PM proteins to CA. Involvement of ABA in the CA process diminished with the progression of growth phase. Taken together, the results suggest that dynamic alterations of the PM proteome with the progression of growth phase influence the PM proteome responses to CA and ABA, which may effect the difference in freezing tolerance capability. SignificanceAfter cold acclimation (CA) or abscisic acid treatment (ABA), Arabidopsis thaliana suspension-cultured cells (T87 line) exhibited freezing tolerance capability dependent on the cell growth phase. However, whether the plasma membrane (PM) proteome profile differs among growth phases and the differences are associated with growth-phase-dependent freezing tolerance have not been elucidated. In the present study, PM proteomics was conducted in association with CA and ABA treatment of Arabidopsis suspension-cultured cells at three growth phases. Characteristics of the PM proteome changed considerably with progression of the growth phase and ABA was indicated to be an important signal for PM protein changes during CA. The results also revealed that multiple signals are required to complete the response of PM proteins to CA. Therefore, dynamic alterations of the PM proteome with the advance of the growth phase influence the responses of PM proteome to CA and ABA, which may result in the differences in freezing tolerance of the cultured cells.

Development and Application of Aptamer-Based Surface-Enhanced Raman Spectroscopy Sensors in Quantitative Analysis and Biotherapy.

Surface-enhanced Raman scattering (SERS) is one of the most special and important Raman techniques. An apparent Raman signal can be observed when the target molecules are absorbed onto the surface of the SERS substrates, especially on the “hot spots” of the substrates. Early research focused on exploring the highly active SERS substrates and their detection applications in label-free SERS technology. However, it is a great challenge to use these label-free SERS sensors for detecting hydrophobic or non-polar molecules, especially in complex systems or at low concentrations. Therefore, antibodies, aptamers, and antimicrobial peptides have been used to effectively improve the target selectivity and meet the analysis requirements. Among these selective elements, aptamers are easy to use for synthesis and modifications, and their stability, affinity and specificity are extremely good; they have been successfully used in a variety of testing areas. The combination of SERS detection technology and aptamer recognition ability not only improved the selection accuracy of target molecules, but also improved the sensitivity of the analysis. Variations of aptamer-based SERS sensors have been developed and have achieved satisfactory results in the analysis of small molecules, pathogenic microorganism, mycotoxins, tumor marker and other functional molecules, as well as in successful photothermal therapy of tumors. Herein, we present the latest advances of the aptamer-based SERS sensors, as well as the assembling sensing platforms and the strategies for signal amplification. Furthermore, the existing problems and potential trends of the aptamer-based SERS sensors are discussed.

Plasmonic Pixel Biosensor Based on Grazing Angle Illumination and Computational Imaging

Surface plasmon resonance (SPR) has been adapted for analyzing biomolecular interactions in real time as a label-free technology. However, SPR instruments, which are usually bulky and expensive, require specialized optical components for exciting surface plasmons and detecting spectral signals, and the technique has yet to evolve into a more affordable and accessible analytic tool. In this paper, we demonstrate a plasmonic sensing device integrated with plasmonic pixels for exciting surface plasmons and displaying spectral information. The plasmonic pixels based on continuous nanostructured metallic thin films establish a direct relationship between nanostructure patterns and plasmon resonances in the visible and near-infrared spectrum range. Steep dispersion of Fano resonances induced by incident light from a grazing angle transduces plasmonic spectral responses into a unique two-dimensional image. Spectral information extracted from the plasmonic pixels exhibits an asymmetric Fano resonance behavior with sharp intensity peaks and the full width half maxima (FWHM) down to 10 nm. The relative brightness of the plasmonic pixels allows naked human eyes to detect the formation of a biomolecule monolayer. Most importantly, subnanometer spectral information can be extracted from the plasmonic pixel images and computed to analyze dynamics of chemical and biomolecular binding events in real time. We envision that these nanostructure plasmonic pixel biosensors can provide a compact and low-cost analytic platform to meet the emerging demands, particularly in portable, mobile, and wearable devices for label-free detection and point-of-care diagnostics.

Sorting by interfacial tension (SIFT): Label-free enzyme sorting using droplet microfluidics

Droplet microfluidics has the ability to greatly increase the throughput of screening and sorting of enzymes by carrying reagents in picoliter droplets flowing in inert oils. It was found with the use of a specific surfactant, the interfacial tension of droplets can be very sensitive to droplet pH. This enables the sorting of droplets of different pH when confined droplets encounter a microfabricated trench. The device can be extended to sort enzymes, as a large number of enzymatic reactions lead to the production of an acidic or basic product and a concurrent change in solution pH. The progress of an enzymatic reaction is tracked from the position of a flowing train of droplets. We demonstrate the sorting of esterase isoenzymes based on their enzymatic activity. This label-free technology, that we dub droplet sorting by interfacial tension (SIFT), requires no active components and would have applications for enzyme sorting in high-throughput applications that include enzyme screening and directed evolution of enzymes.

Accelerated Stimulated Raman Projection Tomography by Sparse Reconstruction From Sparse-View Data.

Stimulated Raman projection tomography (SRPT), a recently developed label-free volumetric chemical imaging technology, has been reported to quantitatively reconstruct the distribution of chemicals in a three-dimensional (3D) complex system. The current image reconstruction scheme used in SRPT is based on a filtered back projection (FBP) algorithm that requires at least 180 angular-dependent projections to rebuild a reasonable SRPT image, resulting in a long total acquisition time. This is a big limitation for longitudinal studies on live systems. We present a sparse-view data-based sparse reconstruction scheme, in which sparsely sampled projections at 180 degrees were used to reconstruct the volumetric information. In the scheme, the simultaneous algebra reconstruction technique (SART), combined with total variation regularization, was used for iterative reconstruction. To better describe the projection process, a pixel vertex driven model (PVDM) was developed to act as projectors, whose performance was compared with those of the distance driven model (DDM). We evaluated our scheme with numerical simulations and validated it for SRPT by mapping lipid contents in adipose cells. Simulation results showed that the PVDM performed better than the DDM in the case of using sparse-view data. Our scheme could maintain the quality of the reconstructed images even when the projection number was reduced to 15. The cell-based experimental results demonstrated that the proposed scheme can improve the imaging speed of the current FBP-based SRPT scheme by a factor of 9-12 without sacrificing discernible imaging details. Our proposed scheme significantly reduces the total acquisition time required for SRPT at a speed of one order of magnitude faster than the currently used scheme. This significant improvement in imaging speed would potentially promote the applicability of SRPT for imaging living organisms.

Label-free time- and space-resolved exometabolite sampling of growing plant roots through nanoporous interfaces

Spatial and temporal profiling of metabolites within and between living systems is vital to understanding how chemical signaling shapes the composition and function of these complex systems. Measurement of metabolites is challenging because they are often not amenable to extrinsic tags, are diverse in nature, and are present with a broad range of concentrations. Moreover, direct imaging by chemically informative tools can significantly compromise viability of the system of interest or lack adequate resolution. Here, we present a nano-enabled and label-free imaging technology using a microfluidic sampling network to track production and distribution of chemical information in the microenvironment of a living organism. We describe the integration of a polyester track-etched (PETE) nanofluidic interface to physically confine the biological sample within the model environment, while allowing fluidic access via an underlying microfluidic network. The nanoporous interface enables sampling of the microenvironment above in a time-dependent and spatially-resolved manner. For demonstration, the diffusional flux through the PETE membrane was characterized to understand membrane performance, and exometabolites from a growing plant root were successfully profiled in a space- and time-resolved manner. This method and device provide a frame-by-frame description of the chemical environment that maps to the physical and biological characteristics of the sample.

Design of ultra-high sensitive biosensor to detect E. Coli in water

Escherichia coli (abbreviated as E. coli) are bacteria found in water, in food. The present work focuses applications of surface plasmon resonance (SPR) based biosensors to detect E. coli. SPR is a label-free technology that is used to detect biological samples. The SPR based biosensor design consists of optical wave guide with different structures of metal–dielectric interfaces and effort has been done to optimize design parameters for improved sensitivity. Metal-dielectric structures considered are Au–Si, Ag–Si, Au–GaAs and Ag–GaAs. Obtained simulation results indicates that the performance of the proposed sensor can be enhanced by varying the thickness and material of metal–dielectric interfaces. The device sensitivity obtained 1071.42 nm/RIU by considering metal-dielectric interface of Gold (thickness 0.074 μm) and Gallium Arsenide (thickness 0.22 μm). This result is significantly higher than sensitivity value of 250 nm/RIU found in published literature for similar type of sensor. From the simulation graph it is clear that for small change in refractive index (RI), value of 0.07 (1.33–1.4), there is significant shift in wavelength. This shows that the sensor is highly sensitive towards the change in RI and can be fabricated as lab-on-chip based biosensor. The optimized sensor was tested for detection for E. coli and sensitivity of 400 nm/RIU obtained. The design is compact and easy to fabricate using optical lithography as compared to the conventional optical component based SPR sensor.

Abstract 2159: Label-free impedance analysis as a versatile tool for dynamic screening of cancer molecular therapeutics

Abstract In vitro monitoring cancer cells response to treatment often involves laborious sample processing and collects single data points that are against the dynamic nature of cancer cells. Here we present the adaptation of an impedance-based methodology to dynamically monitor cancer cell behavior and therapeutic response. The technology detects cell death, proliferation or migration by measuring changes in conductance of microelectrodes embedded in 96 and 384-wells cell culture plates. It avoids sample labeling and processing and allows continuous monitoring of cell response. Our data shows validation with cancer cell lines and primary cells monitored for cell invasion/migration through transwells or after a scratch has been performed with a dedicated device, anticancer drug response and receptor signaling activation, with similar results over end point assays. Easy experiment set up and minimal sample processing make the technology ideal for applications in large screening campaigns, while label-free technology allows less artifacts and further analysis on the same samples through orthogonal assays. Citation Format: Fabio Cerignoli, Biao Xi, Brandon Lamarche, Leyna Zhao, Yama Abassi. Label-free impedance analysis as a versatile tool for dynamic screening of cancer molecular therapeutics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2159.

Abstract 407: Gene expression and mutation profiles of single lung circulating tumor cells

Abstract In the era of personalized medicine, many targeted therapies have been developed against cancer-specific antigens, which have greatly improved patient outcome. The efficacy of targeted therapies was first shown in patients with non-small cell lung cancer (NSCLC) containing activating epidermal growth factor receptor (EGFR) mutations who responded to tyrosine kinase inhibitors (TKIs). To determine if a patient qualifies for targeted therapy, the patient must undergo a tumor biopsy. Usually done at the time of diagnosis, this single time-point examination dictates the treatment plan. Despite strong initial response to TKI therapy, nearly all patients develop resistance, most commonly by acquiring a secondary EGFR mutation. At the time of halted response, an additional biopsy may be necessary to screen for the presence of these secondary, resistance-causing mutations. Circulating tumor cells (CTCs) are cancer cells present in the blood that provide an alternative to an invasive tumor biopsy. Shed from the primary tumor, CTCs circulate throughout the vasculature, and extravasate leading to metastasis. CTCs have been shown to carry tumor-matched characteristics in both genotype and phenotype. Easily accessed through a blood draw, they can be used to serially track patients throughout treatment to detect the early emergence of new tumor clones. One of the biggest hurdles with CTCs being clinical prognostic markers is their low abundance in the blood. We have previously developed a high-throughput, label-free microfluidic technology, the Labyrinth, to isolate CTCs from the blood of breast, lung, and pancreatic cancer patients. This technology allows for quick and efficient isolation of CTCs from the millions of surrounding blood cells. After isolation, the CTCs are used for enumeration or single cell analysis. The single cell gene expression analysis performs a highly multiplexed RT-qPCR of a pre-designed 96 gene panel. Here we report a complementary single cell analysis approach to detect the presence of EGFR point mutations, L858R and T790M, implicated in TKI response using digital PCR (dPCR). dPCR is a highly sensitive approach which enables detection and quantification a single-cell level. dPCR relies on small sample loading and partitions the sample into individual PCR reaction droplets. This single molecule resolution provides the ability to distinguish if a cell is homo- or heterozygous for a mutation as well as their relative expression levels. We have validated this system for single cell analysis using lung cancer cell lines with known L858R and T790M mutation status. We present initial findings of EGFR mutation screening of lung CTCs from patients with known EGFR status based on tissue profiling. By tracking patients over time, comparing the CTC profiles, and correlating it to patient outcomes, we may be able to better identify early treatment resistant clones and adjust their treatment to improve patient outcome. Citation Format: Sarah Owen, Ting-Wen Lo, Shamileh Fouladdel, Ebrahim Azizi, Nithya Ramnath, Sunitha Nagrath. Gene expression and mutation profiles of single lung circulating tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 407.

Rapid Label-free DNA Quantification by Multi-frequency Impedance Sensing on a Chip.

DNA quantification and characterization are of critical importance in disease diagnosis and clinical analysis, while label-free technology greatly simplifies the sensing protocol as it eliminates the extra step for attaching the indicator to DNA strands. In this work, we present a novel label-free DNA detection methodology based on electrical frequency-dependent impedance. The impedance of DNA strands conjunct with streptavidin-coated magnetic beads was measured at 8 different frequencies using an electrical impedance sensor integrated on a chip. Different concentrations of 300 bp double-stranded DNA samples were used to validate our sensor. The minimum DNA amount that could be successfully detected was 0.77 ng (3.9 amol). Detecting DNA fragments using our sensor could be further reduced from currently 20 minutes to under 15 minutes.

Secretome Profiling Reveals Virulence-Associated Proteins of Fusarium proliferatum during Interaction with Banana Fruit.

Secreted proteins are vital for the pathogenicity of many fungi through manipulating their hosts for efficient colonization. Fusarium proliferatum is a phytopathogenic fungus infecting many crops, vegetables, and fruit, including banana fruit. To access the proteins involved in pathogen–host interaction, we used label-free quantitative proteomics technology to comparatively analyze the secretomes of F. proliferatum cultured with and without banana peel in Czapek’s broth medium. By analyzing the secretomes of F. proliferatum, we have identified 105 proteins with 40 exclusively secreted and 65 increased in abundance in response to a banana peel. These proteins were involved in the promotion of invasion of banana fruit, and they were mainly categorized into virulence factors, cell wall degradation, metabolic process, response to stress, regulation, and another unknown biological process. The expressions of corresponding genes confirmed the existence of these secreted proteins in the banana peel. Furthermore, expression pattern suggested variable roles for these genes at different infection stages. This study expanded the current database of F. proliferatum secreted proteins which might be involved in the infection strategy of this fungus. Additionally, this study warranted the further attention of some secreted proteins that might initiate infection of F. proliferatum on banana fruit.

Label-free neuroblastoma cell separation from hematopoietic progenitor cell products using acoustophoresis - towards cell processing of complex biological samples

Processing of complex cell preparations such as blood and peripheral blood progenitor cell (PBPC) transplants using label-free technologies is challenging. Transplant-contaminating neuroblastoma cells (NBCs) can contribute to relapse, and we therefore aimed to provide proof-of-principle evidence that label-free acoustophoretic separation can be applied for diagnostic NBC enrichment and removal (“purging”) from human blood and PBPC products. Neuroblastoma cells spiked into blood and PBPC preparations served as model systems. Acoustophoresis enabled to enrich NBCs from mononuclear peripheral blood cells and PBPC samples with recovery rates of up to 60–97%. When aiming at high purity, NBC purities of up to 90% were realized, however, compromising recovery. Acoustophoretic purging of PBPC products allowed substantial tumour cell depletion of 1.5–2.3 log. PBPC loss under these conditions was considerable (>43%) but could be decreased to less than 10% while still achieving NBC depletion rates of 60–80%. Proliferation of cells was not affected by acoustic separation. These results provide first evidence that NBCs can be acoustically separated from blood and stem cell preparations with high recovery and purity, thus indicating that acoustophoresis is a promising technology for the development of future label-free, non-contact cell processing of complex cell products.

Real-time quality control and functional assessment of mesenchymal stem cells for cellular therapies

Background & Aim One of the biggest hurdles in manufacturing of cellular therapies using mesenchymal stem cells (MSCs) is the lack of quantitative tools that simultaneously assess quality and potency of MSCs, which display big variations among donors and over limited passages. Methods, Results & Conclusion We developed a real-time cell-based assay that generates impedance signals reflecting integrated changes in cell number, attachment, and morphology. We obtained bone marrow derived MSCs from 3 different donors and cultured them under standard conditions using xeno-free media. Multiple real-time quantitative parameters are derived from the assay for quality control, such as proliferation kinetics, doubling time and maximal proliferation signal obtained. These parameters not only provided a measurement of quality of the cells but also provided useful in predicting the differentiation potential of the cells into various lineages including adipocytes, chondrocytes and osteoblasts. This label-free technology can be multiplexed with the measurement of functional biomarkers including receptor activation for a rapid and quantitative assessment of differentiation potential. Using this innovative system, we characterized inter- and intra- donor variability over multiple passages. Our findings suggest that the multi-parametric assay can provide the end-user with a comprehensive assessment for quality control whilst rapidly predicting the extent of functional activity of the cell during the manufacturing process.

Adarza’s Ziva technology platform enables highly multiplexed label-free detection of serum analytes

Abstract New multiplex, label-free methods for the sensitive and quantitative detection of serum proteins are highly desirable, as they have the potential to dramatically accelerate biomedical research in the age of multi-omic, big data driven personalized medicine. We have used Arrayed Imaging Reflectometry (AIR™), a label-free protein microarray technology that relies on the target binding-induced perturbation of an antireflective coating on the surface of a silicon chip, to create a multiplex antibody array for the detection of human serum cytokines and inflammatory markers. The chip is able to provide quantitative information about protein concentrations, with limits of detection in picograms per mL. Provided in a standard 96-well microplate format, the label-free nature of the array will permit rapid expansion in plex size and enable simple, flexible creation of custom panels as there are no secondary antibodies or labels to cross-react. Here we demonstrate validation parameters of sensitivity, precision, and accuracy for inflammatory markers (>20) in a new multiplex technology suitable for analyzing trends across cytokine and inflammatory marker profiles comparable to traditional ELISAs. With array capabilities from low to hundreds of plex combined with a hands-free, automation-friendly workflow enabled by the Ziva instrument, the technology has been designed for the ultimate user-experience.

Clinical protein science in translational medicine targeting malignant melanoma

Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry–based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular functions underlying disease progression. In parallel to a streamlined, patient-centric, clinical proteomic pipeline, mass spectrometry–based imaging can aid in interrogating the spatial distribution of drugs and drug metabolites within tissues at single-cell resolution. These developments are an important advancement in studying drug action and efficacy in vivo and will aid in the development of more effective and safer strategies for the treatment of melanoma. A collaborative effort of gargantuan proportions between academia and healthcare professionals has led to the initiation, establishment and development of a cutting-edge cancer research centre with a specialisation in melanoma and lung cancer. The primary research focus of the European Cancer Moonshot Lund Center is to understand the impact that drugs have on cancer at an individualised and personalised level. Simultaneously, the centre increases awareness of the relentless battle against cancer and attracts global interest in the exceptional research performed at the centre.