High-throughput lipidomic profiles sampled with electroporation-based biopsy differentiate healthy skin, cutaneous squamous cell carcinoma, and basal cell carcinoma.

BACKGROUND: The incidence rates of cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) skin cancers are rising, while the current diagnostic process is time-consuming. We describe the development of a novel approach to high-throughput sampling of tissue lipids using electroporation-based biopsy, termed e-biopsy. We report on the ability of the e-biopsy technique to harvest large amounts of lipids from human skin samples. MATERIALS AND METHODS: Here, 168 lipids were reliably identified from 12 patients providing a total of 13 samples. The extracted lipids were profiled with ultra-performance liquid chromatography and tandem mass spectrometry (UPLC-MS-MS) providing cSCC, BCC, and healthy skin lipidomic profiles. RESULTS: Comparative analysis identified 27 differentially expressed lipids (p < 0.05). The general profile trend is low diglycerides in both cSCC and BCC, high phospholipids in BCC, and high lyso-phospholipids in cSCC compared to healthy skin tissue samples. CONCLUSION: The results contribute to the growing body of knowledge that can potentially lead to novel insights into these skin cancers and demonstrate the potential of the e-biopsy technique for the analysis of lipidomic profiles of human skin tissues.

Electroporation-Based Biopsy Treatment Planning with Numerical Models and Tissue Phantoms.

Molecular sampling with vacuum-assisted tissue electroporation is a novel, minimally invasive method for molecular profiling of solid lesions. In this paper, we report on the design of the battery-powered pulsed electric field generator and electrode configuration for an electroporation-based molecular sampling device for skin cancer diagnostics. Using numerical models of skin electroporation corroborated by the potato tissue phantom model, we show that the electroporated tissue volume, which is the maximum volume for biomarker sampling, strongly depends on the electrode's geometry, needle electrode skin penetration depths, and the applied pulsed electric field protocol. In addition, using excised human basal cell carcinoma (BCC) tissues, we show that diffusion of proteins out of human BCC tissues into water strongly depends on the strength of the applied electric field and on the time after the field application. The developed numerical simulations, confirmed by experiments in potato tissue phantoms and excised human cancer lesions, provide essential tools for the development of electroporation-based molecular markers sampling devices for personalized skin cancer diagnostics.

Exploring multisite heterogeneity of human basal cell carcinoma proteome and transcriptome.

Basal cell carcinoma (BCC) is the most common type of skin cancer. Due to multiple, potential underlying molecular tumor aberrations, clinical treatment protocols are not well-defined. This study presents multisite molecular heterogeneity profiles of human BCC based on RNA and proteome profiling. Three areas from lesions excised from 9 patients were analyzed. The focus was gene expression profiles based on proteome and RNA measurements of intra-tumor heterogeneity from the same patient and inter-tumor heterogeneity in nodular, infiltrative, and superficial BCC tumor subtypes from different patients. We observed significant overlap in intra- and inter-tumor variability of proteome and RNA expression profiles, showing significant multisite heterogeneity of protein expression in the BCC tumors. Inter-subtype analysis has also identified unique proteins for each BCC subtype. This profiling leads to a deeper understanding of BCC molecular heterogeneity and potentially contributes to developing new sampling tools for personalized diagnostics therapeutic approaches to BCC.

In vivo detection of bile duct pre-cancer with endoscopic light scattering spectroscopy.

Bile duct cancer is the second most common primary liver cancer, with most diagnoses occurring in the advanced stages. This leads to a poor survival rate, which means a technique capable of reliably detecting pre-cancer in the bile duct is urgently required. Unfortunately, radiological imaging lacks adequate accuracy for distinguishing dysplastic and benign biliary ducts, while endoscopic techniques, which can directly assess the bile duct lining, often suffer from insufficient sampling. Here, we report an endoscopic optical light scattering technique for clinical evaluation of the malignant potential of the bile duct. This technique employs an ultraminiature spatial gating fiber optic probe compatible with cholangioscopes and endoscopic retrograde cholangiopancreatography (ERCP) catheters. The probe allowed us to investigate the internal cellular composition of the bile duct epithelium with light scattering spectroscopy (LSS) and phenotypic properties of the underlying connective tissue with diffuse reflectance spectroscopy (DRS). In a pilot in vivo double-blind prospective study involving 29 patients undergoing routine ERCP procedures, the technique detected malignant transformation with 97% accuracy, showing that biliary duct pre-cancer can be reliably identified in vivo non-invasively.

Nondestructive protein sampling with electroporation facilitates profiling of spatial differential protein expression in breast tumors in vivo.

Excision tissue biopsy, while central to cancer treatment and precision medicine, presents risks to the patient and does not provide a sufficiently broad and faithful representation of the heterogeneity of solid tumors. Here we introduce e-biopsy-a novel concept for molecular profiling of solid tumors using molecular sampling with electroporation. As e-biopsy provides access to the molecular composition of a solid tumor by permeabilization of the cell membrane, it facilitates tumor diagnostics without tissue resection. Furthermore, thanks to its non tissue destructive characteristics, e-biopsy enables probing the solid tumor multiple times in several distinct locations in the same procedure, thereby enabling the spatial profiling of tumor molecular heterogeneity.We demonstrate e-biopsy in vivo, using the 4T1 breast cancer model in mice to assess its performance, as well as the inferred spatial differential protein expression. In particular, we show that proteomic profiles obtained via e-biopsy in vivo distinguish the tumors from healthy breast tissue and reflect spatial tumor differential protein expression. E-biopsy provides a completely new molecular sampling modality for solid tumors molecular cartography, providing information that potentially enables more rapid and sensitive detection at lesser risk, as well as more precise personalized medicine.

Electroporation-based proteome sampling ex vivo enables the detection of brain melanoma protein signatures in a location proximate to visible tumor margins.

A major concern in tissue biopsies with a needle is missing the most lethal clone of a tumor, leading to a false negative result. This concern is well justified, since needle-based biopsies gather tissue information limited to needle size. In this work, we show that molecular harvesting with electroporation, e-biopsy, could increase the sampled tissue volume in comparison to tissue sampling by a needle alone. Suggested by numerical models of electric fields distribution, the increased sampled volume is achieved by electroporation-driven permeabilization of cellular membranes in the tissue around the sampling needle. We show that proteomic profiles, sampled by e-biopsy from the brain tissue, ex vivo, at 0.5mm distance outside the visible margins of mice brain melanoma metastasis, have protein patterns similar to melanoma tumor center and different from the healthy brain tissue. In addition, we show that e-biopsy probed proteome signature differentiates between melanoma tumor center and healthy brain in mice. This study suggests that e-biopsy could provide a novel tool for a minimally invasive sampling of molecules in tissue in larger volumes than achieved with traditional needle biopsies.

Rapid detection and identification of bacteria directly from whole blood with light scattering spectroscopy based biosensor.

Bacterial infections are one of the major causes of death worldwide. The identification of a bacterial species that is the source of an infection generally takes a long time, and often exceeds the treatment window for seriously ill patients. Many of these deaths are preventable if the bacterial species can be identified quickly. Here we present an optical spectroscopic method for rapid detection and identification of bacteria directly from whole blood using a light scattering spectroscopy technique. This technique was originally developed to detect pre-cancerous changes in epithelial tissues, characterize changes in tissue on the cellular scale, and characterize biological structures comparable to or smaller than a single wavelength. We demonstrate here that not only can an inexpensive light scattering spectroscopy-based biosensor rapidly detect and identify four bacteria species in the blood, responsible for the majority of death causing infections, but that species-level identification can potentially be made based on approximately one thousand bacterial cells per milliliter of blood. Observing entire colonies or performing susceptibility testing is therefore not required.

Coherent confocal light scattering spectroscopic microscopy evaluates cancer progression and aggressiveness in live cells and tissue.

The observation of biological structures in live cells beyond the diffraction limit with super-resolution fluorescence microscopy is limited by the ability of fluorescence probes to permeate live cells and the effect of these probes, which are often toxic, on cellular behavior. Here we present a coherent confocal light scattering and absorption spectroscopic microscopy that for the first time enables the use of large numerical aperture optics to characterize structures in live cells down to 10 nm spatial scales, well beyond the diffraction limit. Not only does this new capability allow high resolution microscopy with light scattering contrast, but it can also be used with almost any light scattering spectroscopic application which employs lenses. We demonstrate that the coherent light scattering contrast based technique allows continuous temporal tracking of the transition from non-cancerous to an early cancerous state in live cells, without exogenous markers. We also use the technique to sense differences in the aggressiveness of cancer in live cells and for label free identification of different grades of cancer in resected tumor tissues.

Spectroscopic label-free microscopy of changes in live cell chromatin and biochemical composition in transplantable organoids.

Organoids formed from human induced pluripotent stem cells (hiPSCs) could be a limitless source of functional tissue for transplantations in many organs. Unfortunately, fine-tuning differentiation protocols to form large quantities of hiPSC organoids in a controlled, scalable, and reproducible manner is quite difficult and often takes a very long time. Recently, we introduced a new approach of rapid organoid formation from dissociated hiPSCs and endothelial cells using microfabricated cell-repellent microwell arrays. This approach, when combined with real-time label-free Raman spectroscopy of biochemical composition changes and confocal light scattering spectroscopic microscopy of chromatin transition, allows for monitoring live differentiating organoids without the need to sacrifice a sample, substantially shortening the time of protocol fine-tuning. We used this approach to both culture and monitor homogeneous liver organoids that have the main functional features of the human liver and which could be used for cell transplantation liver therapy in humans.

Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.

Intelligent biorefinery design that addresses both the composition of the biomass feedstock as well as fermentation microorganisms could benefit from dedicated tools for computational simulation and computer-assisted optimization. Here we present the BioLego Vn2.0 framework, based on Microsoft Azure Cloud, which supports large-scale simulations of biomass serial fermentation processes by two different organisms. BioLego enables the simultaneous analysis of multiple fermentation scenarios and the comparison of fermentation potential of multiple feedstock compositions. Thanks to the effective use of cloud computing it further allows resource intensive analysis and exploration of media and organism modifications. We use BioLego to obtain biological and validation results, including (1) exploratory search for the optimal utilization of corn biomasses-corn cobs, corn fiber and corn stover-in fermentation biorefineries; (2) analysis of the possible effects of changes in the composition of K. alvarezi biomass on the ethanol production yield in an anaerobic two-step process (S. cerevisiae followed by E. coli); (3) analysis of the impact, on the estimated ethanol production yield, of knocking out single organism reactions either in one or in both organisms in an anaerobic two-step fermentation process of Ulva sp. into ethanol (S. cerevisiae followed by E. coli); and (4) comparison of several experimentally measured ethanol fermentation rates with the predictions of BioLego.

Design and Analysis of Offshore Macroalgae Biorefineries.

Displacing fossil fuels and their derivatives with renewables, and increasing sustainable food production are among the major challenges facing the world in the coming decades. A possible, sustainable direction for addressing this challenge is the production of biomass and the conversion of this biomass to the required products through a complex system coined biorefinery. Terrestrial biomass and microalgae are possible sources; however, concerns over net energy balance, potable water use, environmental hazards, and uncertainty in the processing technologies raise questions regarding their actual potential to meet the anticipated food, feed, and energy challenges in a sustainable way. Alternative sustainable sources for biorefineries are macroalgae grown and processed offshore. However, implementation of the offshore biorefineries requires detailed analysis of their technological, economic, and environmental performance. In this chapter, the basic principles of marine biorefineries design are shown. The methods to integrate thermodynamic efficiency, investment, and environmental aspects are discussed. The performance improvement by development of new cultivation methods that fit macroalgae physiology and development of new fermentation methods that address macroalgae unique chemical composition is shown.

Energy efficient dewatering of far offshore grown green macroalgae Ulva sp. biomass with pulsed electric fields and mechanical press.

Offshore macroalgae biomass production is a promising, yet challenging, pathway to provide feedstock for biorefineries. In this work, a device and a process for dewatering offshore grown biomass of the green macroalgae Ulva sp. using high-voltage pulsed electric fields (PEF) was developed. Ulva sp. was cultivated attached to fish cages 15 km offshore. Increasing the applied voltage from 250 V to 500 V and invested PEF energy from 9.3 ±â€¯0.4 J g-1 FW to 54.6 ±â€¯0.2Jg-1 FW increased the extracted water from 0.033 ±â€¯0.006 g Water g-1  FW to 0.150 ±â€¯0.031 g Water g-1 FW. The energy consumption to achieve similar moisture content with air convection drying was lower by 78.73 ±â€¯10.41 (JgFW-1) for 250 V and 339.31 ±â€¯48.01 (JgFW-1) for 500 V, pulse duration 50 µs, pulse number 50, pulse repetition frequency 3 Hz. PEF leads to biomass compression of 8.45 ±â€¯1.72% for 250 V protocol and 25.66 ±â€¯2.53% for 500 V protocol. In addition, PEF leads to the reduction of water diffusivity of 18-19% in the treated biomass, reducing air drying kinetics.

Multispectral Endoscopy with Light Gating for Early Cancer Detection.

This paper reports the application of endoscopic light scattering spectroscopy (LSS) with light gating to detect malignancies in the biliary and pancreatic ducts, and also reviews the application of endoscopic LSS for differentiating cystic neoplasms in the pancreas and detecting invisible dysplasia in Barrett's esophagus. Information about tissue structure within the superficial epithelium where malignancy starts is present within the spectra of reflected light. Fortunately, this component of the reflected light is not yet randomized. However multiple scattering randomizes the signal from the underlying connective tissue which obscures the desired signal. In order to extract diagnostic information from the reflected signal the multiple scattering component related to connective tissue scattering and absorption must be removed. This is accomplished using described here spatial or polarization gating implemented with endoscopically compatible fiber optic probes.

Genome-wide analysis of fitness data and its application to improve metabolic models.

BACKGROUND: Synthetic biology and related techniques enable genome scale high-throughput investigation of the effect on organism fitness of different gene knock-downs/outs and of other modifications of genomic sequence. RESULTS: We develop statistical and computational pipelines and frameworks for analyzing high throughput fitness data over a genome scale set of sequence variants. Analyzing data from a high-throughput knock-down/knock-out bacterial study, we investigate differences and determinants of the effect on fitness in different conditions. Comparing fitness vectors of genes, across tens of conditions, we observe that fitness consequences strongly depend on genomic location and more weakly depend on gene sequence similarity and on functional relationships. In analyzing promoter sequences, we identified motifs associated with conditions studied in bacterial media such as Casaminos, D-glucose, Sucrose, and other sugars and amino-acid sources. We also use fitness data to infer genes associated with orphan metabolic reactions in the iJO1366 E. coli metabolic model. To do this, we developed a new computational method that integrates gene fitness and gene expression profiles within a given reaction network neighborhood to associate this reaction with a set of genes that potentially encode the catalyzing proteins. We then apply this approach to predict candidate genes for 107 orphan reactions in iJO1366. Furthermore - we validate our methodology with known reactions using a leave-one-out approach. Specifically, using top-20 candidates selected based on combined fitness and expression datasets, we correctly reconstruct 39.7% of the reactions, as compared to 33% based on fitness and to 26% based on expression separately, and to 4.02% as a random baseline. Our model improvement results include a novel association of a gene to an orphan cytosine nucleosidation reaction. CONCLUSION: Our pipeline for metabolic modeling shows a clear benefit of using fitness data for predicting genes of orphan reactions. Along with the analysis pipelines we developed, it can be used to analyze similar high-throughput data.

Picoanalysis of Drugs in Biofluids with Quantitative Label-Free Surface-Enhanced Raman Spectroscopy.

The enormous increase of Raman signal in the vicinity of metal nanoparticles allows surface-enhanced Raman spectroscopy (SERS) to be employed for label-free detection of substances at extremely low concentrations. However, the ultimate potential of label-free SERS to identify pharmaceutical compounds at low concentrations, especially in relation to biofluid sensing, is far from being fully realized. Opioids are a particular challenge for rapid clinical identification because their molecular structural similarities prevent their differentiation with immunolabeling approaches. In this paper, a new method called quantitative label-free SERS (QLF-SERS) which involves the formation of halide-conjugated gold nanoclusters trapping the analyte of interest near the SERS hot spots is reported, and it is demonstrated that it yields a 105 fold improvement in the detection limit over previously reported results for the entire class of clinically relevant opioids and their metabolites. Measurements of opioid concentrations in multicomponent mixtures are also demonstrated. QLF-SERS has comparable detection limits as currently existing laboratory urine drug testing techniques but is significantly faster and inexpensive and, therefore, can be easily adapted as part of a rapid clinical laboratory routine.

Multispectral light scattering endoscopic imaging of esophageal precancer.

Esophageal adenocarcinoma is the most rapidly growing cancer in America. Although the prognosis after diagnosis is unfavorable, the chance of a successful outcome increases tremendously if detected early while the lesion is still dysplastic. Unfortunately, the present standard-of-care, endoscopic surveillance, has major limitations, since dysplasia is invisible, often focal, and systematic biopsies typically sample less than one percent of the esophageal lining and therefore easily miss malignancies. To solve this problem we developed a multispectral light scattering endoscopic imaging system. It surveys the entire esophageal lining and accurately detects subcellular dysplastic changes. The system combines light scattering spectroscopy, which detects and identifies invisible dysplastic sites by analyzing light scattered from epithelial cells, with rapid scanning of the entire esophageal lining using a collimated broadband light beam delivered by an endoscopically compatible fiber optic probe. Here we report the results of the first comprehensive multispectral imaging study, conducted as part of routine endoscopic procedures performed on patients with suspected dysplasia. In a double-blind study that characterized the system's ability to serve as a screening tool, 55 out of 57 patients were diagnosed correctly. In addition, a smaller double-blind comparison of the multispectral data in 24 patients with subsequent pathology at locations where 411 biopsies were collected yielded an accuracy of 90% in detecting individual locations of dysplasia, demonstrating the capability of this method to serve as a guide for biopsy.

Light scattering spectroscopy identifies the malignant potential of pancreatic cysts during endoscopy.

Pancreatic cancers are usually detected at an advanced stage and have poor prognosis. About one fifth of these arise from pancreatic cystic lesions. Yet not all lesions are precancerous, and imaging tools lack adequate accuracy for distinguishing precancerous from benign cysts. Therefore, decisions on surgical resection usually rely on endoscopic ultrasound-guided fine needle aspiration (EUS-FNA). Unfortunately, cyst fluid often contains few cells, and fluid chemical analysis lacks accuracy, resulting in dire consequences, including unnecessary pancreatic surgery for benign cysts and the development of cancer. Here, we report an optical spectroscopic technique, based on a spatial gating fibre-optic probe, that predicts the malignant potential of pancreatic cystic lesions during routine diagnostic EUS-FNA procedures. In a double-blind prospective study in 25 patients, with 14 cysts measured in vivo and 13 postoperatively, the technique achieved an overall accuracy of 95%, with a 95%confidence interval of 78-99%, in cysts with definitive diagnosis.

Thermochemical hydrolysis of macroalgae Ulva for biorefinery: Taguchi robust design method.

Understanding the impact of all process parameters on the efficiency of biomass hydrolysis and on the final yield of products is critical to biorefinery design. Using Taguchi orthogonal arrays experimental design and Partial Least Square Regression, we investigated the impact of change and the comparative significance of thermochemical process temperature, treatment time, %Acid and %Solid load on carbohydrates release from green macroalgae from Ulva genus, a promising biorefinery feedstock. The average density of hydrolysate was determined using a new microelectromechanical optical resonator mass sensor. In addition, using Flux Balance Analysis techniques, we compared the potential fermentation yields of these hydrolysate products using metabolic models of Escherichia coli, Saccharomyces cerevisiae wild type, Saccharomyces cerevisiae RN1016 with xylose isomerase and Clostridium acetobutylicum. We found that %Acid plays the most significant role and treatment time the least significant role in affecting the monosaccharaides released from Ulva biomass. We also found that within the tested range of parameters, hydrolysis with 121 °C, 30 min 2% Acid, 15% Solids could lead to the highest yields of conversion: 54.134-57.500 gr ethanol kg(-1) Ulva dry weight by S. cerevisiae RN1016 with xylose isomerase. Our results support optimized marine algae utilization process design and will enable smart energy harvesting by thermochemical hydrolysis.

Cancer exosomes perform cell-independent microRNA biogenesis and promote tumorigenesis.

Exosomes are secreted by all cell types and contain proteins and nucleic acids. Here, we report that breast cancer associated exosomes contain microRNAs (miRNAs) associated with the RISC-Loading Complex (RLC) and display cell-independent capacity to process precursor microRNAs (pre-miRNAs) into mature miRNAs. Pre-miRNAs, along with Dicer, AGO2, and TRBP, are present in exosomes of cancer cells. CD43 mediates the accumulation of Dicer specifically in cancer exosomes. Cancer exosomes mediate an efficient and rapid silencing of mRNAs to reprogram the target cell transcriptome. Exosomes derived from cells and sera of patients with breast cancer instigate nontumorigenic epithelial cells to form tumors in a Dicer-dependent manner. These findings offer opportunities for the development of exosomes based biomarkers and therapies.

Peer group normalization and urine to blood context in steroid metabolomics: the case of CAH and obesity.

Traditional interpretation of GC-MS output involved the semi-quantitative estimation of outstanding low or high specific metabolites and the ratio between metabolites. Here, we utilize a systems biology approach to steroid metabolomics of a complex steroid-related disorder, using an all-inclusive analysis of the steroidal pathway in the form of a subject steroidal fingerprint and disease signature, providing novel methods of normalization and visualization. The study compares 324 normal children to pure enzymatic deficiency in 27 untreated 21-hydroxylase CAH patients and to complex disease in 70 children with obesity. Steroid profiles were created by quantitative data generated by GC-MS analyses. A novel peer-group normalization method defined each individual subject's control group in a multi-dimensional space of metadata parameters. Classical steroid pathway visualization was enhanced by adding urinary end-product sub-nodes and by color coding of semi-quantitative metabolic concentrations and enzymatic activities. Unbiased automated data analysis confirmed the common knowledge for CAH - the inferred 17-hydroxyprogesterone was up-regulated and the inferred 21-hydroxylase enzyme activity was down-regulated. In childhood obesity, we observe a general decrease of both glucocorticoid and mineralocorticoid metabolites, increased androgens, up-regulation of 17,20-lyase, 17-OHase and 11ß-HSD1 activity and down-regulation of 21-OHase enzymatic activity. Our study proved novel normalization and visualization techniques are to be useful in identifying subject fingerprint and disease signature in enzymatic deficiency and insufficiency, while demonstrating hypothesis generation in a complex disease such as childhood obesity.