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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 145 records · Page 8Linked to original sources

bioRxiv2017

Stimulated Raman Scattering Micro-dissection Sequencing (SMD-Seq) for Morphology-specific Genomic Analysis of Oral Squamous Cell Carcinoma

Both the composition of cell types and their spatial distribution in a tissue play a critical role in cellular function, organ development, and disease progression. For example, intratumor heterogeneity and the distribution of transcriptional and genetic events in single cells drive the genesis and development of cancer. However, it can be challenging to fully characterize the molecular profile of cells in a tissue with high spatial resolution because microscopy has limited ability to extract comprehensive genomic information, and the spatial resolution of genomic techniques tends to be limited by dissection. There is a growing need for tools that can be used to explore the relationship between histological features, gene expression patterns, and spatially correlated genomic alterations in healthy and diseased tissue samples. Here, we present a technique that combines label-free histology with spatially resolved multi-omics in un-fixed and unstained tissue sections. This approach leverages stimulated Raman scattering microscopy to provide chemical contrast that reveals histological tissue architecture, allowing for high-resolution in situ laser micro-dissection of regions of interests. These micro-tissue samples are then processed for DNA and RNA sequencing to identify unique genetic profiles that correspond to distinct anatomical regions. We demonstrate the capabilities of this technique by mapping gene expression and copy number alterations to histologically defined regions in human squamous cell carcinoma (OSCC). Our approach provides complementary insights in tumorigenesis and offers an integrative tool for macroscale cancer tissues with spatial multi-omics assessments.

bioengineering↗

bioRxiv2017

Implementation and System Identification of a Phosphorylation-Based Insulator in a Cell-Free Transcription-Translation System

An outstanding challenge in the design of synthetic biocircuits is the development of a robust and efficient strategy for interconnecting functional modules. Recent work demonstrated that a phosphorylation-based insulator (PBI) implementing a dual strategy of high gain and strong negative feedback can be used as a device to attenuate retroactivity. This paper describes the implementation of such a biological circuit in a cell-free transcription-translation system and the structural identifiability of the PBI in the system. We first show that the retroactivity also exists in the cell-free system by testing a simple negative regulation circuit. Then we demonstrate that the PBI circuit helps attenuate the retroactivity significantly compared to the control. We consider a complex model that provides an intricate description of all chemical reactions and leveraging specific physiologically plausible assumptions. We derive a rigorous simplified model that captures the output dynamics of the PBI. We perform standard system identification analysis and determine that the model is globally identifiable with respect to three critical parameters. These three parameters are identifiable under specific experimental conditions and we perform these experiments to estimate the parameters. Our experimental results suggest that the functional form of our simplified model is sufficient to describe the reporter dynamics and enable parameter estimation. In general, this research illustrates the utility of the cell-free expression system as an alternate platform for biocircuit implementation and system identification and it can provide helpful insights into future biological circuit designs.

bioengineering↗

bioRxiv2017

Prototyping And Implementation Of A Novel Feedforward Loop In A Cell-Free Transcription-Translation System And Cells

Building novel synthetic biological devices is a time-consuming task because of the lengthy cell-based testing and optimization processes. Recent progress made in the cell-free field suggests that the utilization of mathematical models and cell-free transcription-translation testing platforms to systematically design and test novel synthetic biocircuits may help streamline some of the processes. Here we present a study of building a novel functional biological network motif from scratch with the aid of the mathematical modeling and the cell-free prototyping. In this work, we demonstrated that we were able to make a 3-promoter feedforward circuit from a concept to a working biocircuit in cells within a month. We started with performing simulations with a cell-free transcription-translation simulation toolbox. After verifying the feasibility of the circuit design, we used a fast assembling method to build the constructs and used the linear DNAs directly in the cell-free system for prototyping. After additional tests and assemblies, we implemented the circuit in plasmid forms in cells and showed that the in vivo results were consistent with the simulations and the outcomes in the cell-free platform. This study showed the usefulness of modeling and prototyping in building synthetic biocircuits and that we can use these tools to help streamline the process of circuit optimizations in future studies.

bioengineering↗

bioRxiv2017

A correlation analysis framework for localization-based super-resolution microscopy

Super-resolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis platform that can extract a quantitative description and biophysical parameters from these images is yet to be established. Here, we propose a conceptual framework for correlation analysis of coordinate-based super-resolution images using distance histograms. We demonstrate the application of this concept in multiple scenarios including image alignment, tracking of diffusing molecules, as well as for quantification of colocalization.\n\nSignificance statementCorrelation analysis is one of the most widely used image processing method. In the quantitative analysis of localization-based super-resolution images, there still lacks a generalized coordinate-based correlation analysis framework to take fully advantage of the super-resolution information. We show a coordinate-based correlation analysis framework for localization-based super-resolution microscopy. This framework is highly general and flexible in that it can be easily extended to model the effect of localization uncertainty, to the time domain and other distance definitions, enabling it to be adapted for a wide range of applications. Our work will greatly benefit the quantitative interpretation of super-resolution images and thus the biological application of super-resolution microscopy.

bioengineering↗

bioRxiv2017

Feature Extraction Through Wavelet Decomposition For Automatic Detection Of Landmarks On Cephalogram Images

Manual cephalogram marking has long way from marking on tracing sheet to availability of commercial software's for cephalometric analysis. With the effort involved in manual marking and time consumption, it becomes imperative for modern science to envisage algorithms which could automatically locate landmarks on the cephalogram images and perform various analysis. In this work, we herby propose a wavelet transform based feature extraction algorithm for detection of landmark on cephalogram images. 15 landmarks were detected on the images using wavelet transform and all landmarks were detected within the acceptable accuracy limits. This algorithm may have a promising approach in detection of further anatomical landmarks automatically and analysis and thus may help orthodontic practioners in better and faster treatment planning.

bioengineering↗

bioRxiv2017

Photoacoustic molecular rulers based on DNA nanostructures

Molecular rulers that rely on the Forster resonance energy transfer (FRET) mechanism are widely used to investigate dynamic molecular processes that occur on the nanometer scale. However, the capabilities of these fluorescence molecular rulers are fundamentally limited to shallow imaging depths by light scattering in biological samples. Photoacoustic tomography (PAT) has recently emerged as a high resolution modality for in vivo imaging, coupling optical excitation with ultrasound detection. In this paper, we report the capability of PAT to probe distance-dependent FRET at centimeter depths. Using DNA nanotechnology we created several nanostructures with precisely positioned fluorophore-quencher pairs over a range of nanoscale separation distances. PAT of the DNA nanostructures showed distance-dependent photoacoustic signal generation and experimentally demonstrated the ability of PAT to reveal the FRET process deep within tissue mimicking phantoms. Further, we experimentally validated these DNA nanostructures as providing a novel and biocompatible strategy to augment the intrinsic photoacoustic signal generation capabilities of small molecule fluorescent dyes.

bioengineering↗

bioRxiv2017

Efficiently Exploring Functional Space In Loop Engineering With Variations In Length And Composition

Insertions and deletions (indels) are known to affect function, biophysical properties and substrate specificity of enzymes, and they play a central role in evolution. Despite such clear significance, this class of mutation remains an underexploited tool in protein engineering with no available platforms capable of systematically generating or analysing libraries of varying sequence composition and length. We present a novel DNA assembly platform (InDel assembly), based on cycles of endonuclease restriction and ligation of standardised dsDNA building blocks, that can generate libraries exploring both composition and sequence length variation. In addition, we developed a framework to analyse the output of selection from InDel-generated libraries, combining next generation sequencing and alignment-free strategies for sequence analysis. We demonstrate the approach by engineering the well-characterized TEM-1 {beta}-lactamase {Omega}-loop, involved in substrate specificity, identifying multiple novel extended spectrum {beta}-lactamases with loops of modified length and composition areas of the sequence space not previously explored. Together, the InDel assembly and analysis platforms provide an efficient route to engineer protein loops or linkers where sequence length and composition are both essential functional parameters.

bioengineering↗

bioRxiv2017

Recent Advancement in Biosensors Technology for Animal and Livestock Health Management

The term biosensors encompasses devices that have the potential to quantify physiological, immunological and behavioural responses of livestock and multiple animal species. Novel biosensing methodologies offer highly specialised monitoring devices for the specific measurement of individual and multiple parameters covering an animals physiology as well as monitoring of an animals environment. These devices are not only highly specific and sensitive for the parameters being analysed, but they are also reliable and easy to use, and can accelerate the monitoring process. Novel biosensors in livestock management provide significant benefits and applications in disease detection and isolation, health monitoring and detection of reproductive cycles, as well as monitoring physiological wellbeing of the animal via analysis of the animals environment. With the development of integrated systems and the Internet of Things, the continuously monitoring devices are expected to become affordable. The data generated from integrated livestock monitoring is anticipated to assist farmers and the agricultural industry to improve animal productivity in the future. The data is expected to reduce the impact of the livestock industry on the environment, while at the same time driving the new wave towards the improvements of viable farming techniques. This review focusses on the emerging technological advancements in monitoring of livestock health for detailed, precise information on productivity, as well as physiology and well-being. Biosensors will contribute to the 4th revolution in agriculture by incorporating innovative technologies into cost-effective diagnostic methods that can mitigate the potentially catastrophic effects of infectious outbreaks in farmed animals

bioengineering↗

bioRxiv2017

Amplified visual immunosensor integrated with nanozyme for ultrasensitive detection of avian influenza virus

Nanomaterial-based artificial enzymes or nanozymes exhibits superior properties such as stability, cost effectiveness and ease of preparation in comparison to conventional enzymes. However, the lower catalytic activity of nanozymes limits their sensitivity and thereby practical applications in the bioanalytical field. To overcome this drawback, herein we propose a very simple but highly sensitive, specific and low-cost dual enhanced colorimetric immunoassay for the detection of avian influenza virus A (H5N1) through facile in situ synthesis of gold nanoparticles and their peroxidase-like enzymatic activity. 3,3,5,5-Tetramethylbenzidine (TMBZ) was used as a reducing agent to produce gold nanoparticles (Au NPs) from a viral target-specific antibody-gold ion complex. The developed blue color from the sensing design was further amplified through catalytic activity of Au NPs in presence of TMBZ-hydrogen peroxide (H2O2) complex. The developed dual enhanced colorimetric immunosensor enables the detection of avian influenza virus A (H5N1) with a limit of detection (LOD) of 1.11 pg/mL. Our results further confirms that the developed assay has superior sensitivity than the conventional ELISA method, plasmonic-based bioassay and commercial flu diagnostic kits.

bioengineering↗

bioRxiv2017

Feature Engineering Coupled Machine Learning Algorithms For Epileptic Seizure Forecasting From Intracranial EEGs

Epilepsy is one of the major neurological disorders affecting nearly 1 percentage of the global population. The major blunt is born by under developed and developing countries due to expensive treatment of epileptic conditions. Further, the lack of proper forecasting methods for an occurrence of epileptic seizures in epileptic-drug resistant patients or patients not amenable for surgery affects their psychological behaviour and restricts their daily activities. The forecasting is usually performed by human experts that leave a wide gap for human-bias and human error. Therefore, in the current work, we have evaluated the efficiency of several machine learning algorithms to automatically identify the preictal patterns corresponding to epileptic seizures from intracranial EEG signals. The robustness of the machine learning algorithms were tested after the data set was pre-processed using carefully chosen feature engineering strategies viz. denoised Fourier transforms as well as cross-correlation across electrodes in time and frequency domain. Extensive experimentations were carried out to determine the best combination of feature engineering techniques and machine learning algorithms. The best combination of feature engineering techniques and machine learning algorithm resulted in 0.7685 AUC (Area under the Receiver Operating Characteristic curve) on the random test samples. The suggested approach was fairly good at prediction of epilepsy in random samples and therefore, it can be used in epileptic seizure forecasting in patients where medication/surgery is ineffective. Eventually, our strategy reveals a robust method for brain disorders forecasting from EEGs.

bioengineering↗

bioRxiv2017

Reading canonical and modified nucleotides in 16S ribosomal RNA using nanopore direct RNA sequencing

The ribosome small subunit is expressed in all living cells. It performs numerous essential functions during translation, including formation of the initiation complex and proofreading of base-pairs between mRNA codons and tRNA anticodons. The core constituent of the small ribosomal subunit is a [~]1.5 kb RNA strand in prokaryotes (16S rRNA) and a homologous [~]1.8 kb RNA strand in eukaryotes (18S rRNA). Traditional sequencing-by-synthesis (SBS) of rRNA genes or rRNA cDNA copies has achieved wide use as a molecular chronometer for phylogenetic studies 1, and as a tool for identifying infectious organisms in the clinic 2. However, epigenetic modifications on rRNA are erased by SBS methods. Here we describe direct MinION nanopore sequencing of individual, full-length 16S rRNA absent reverse transcription or amplification. As little as 5 picograms ([~]10 attomole) of E. coli 16S rRNA was detected in 4.5 micrograms of total human RNA. Nanopore ionic current traces that deviated from canonical patterns revealed conserved 16S rRNA base modifications, and a 7-methylguanosine modification that confers aminoglycoside resistance to some pathological E. coli strains. This direct RNA sequencing technology has promise for rapid identification of microbes in the environment and in patient samples.

bioengineering↗

bioRxiv2017

A Carbon Nanotube Optical Reporter Maps Endolysosomal Lipid Flux

Lipid accumulation within the lumen of endolysosomal vesicles is observed in various pathologies including atherosclerosis, liver disease, neurological disorders, lysosomal storage disorders, and cancer. Current methods cannot measure lipid flux specifically within the lysosomal lumen of live cells. We developed an optical reporter, composed of a photoluminescent carbon nanotube of a single chirality, which responds to lipid accumulation via modulation of the nanotubes optical bandgap. The engineered nanomaterial, composed of short-single stranded DNA and a single nanotube chirality, localizes exclusively to the lumen of endolysosomal organelles without adversely affecting cell viability or proliferation, or organelle morphology, integrity, or function. The emission wavelength of the reporter can be spatially resolved from within the endolysosomal lumen to generate quantitative maps of lipid content in live cells. Endolysosomal lipid accumulation in cell lines, an example of drug-induced phospholipidosis (DIPL), was observed for multiple drugs in macrophages, and measurements of patient-derived Niemann-Pick type C fibroblasts identified lipid accumulation and phenotypic reversal of this lysosomal storage disease. Single-cell measurements using the reporter discerned sub-cellular differences in equilibrium lipid content, illuminating significant intracellular heterogeneity among endolysosomal organelles of differentiating bone marrow-derived monocytes. Single-cell kinetics of lipoprotein-derived cholesterol accumulation within macrophages revealed rates that differed among cells by an order of magnitude. This carbon nanotube optical reporter of endolysosomal lipid content in live cells confers new capabilities for drug development processes and the investigation of lipid-linked diseases.

bioengineering↗

bioRxiv2017

Improved Split Fluorescent Proteins For Endogenous Protein Labeling

Self-complementing split fluorescent proteins (FPs) have been widely used for protein labeling, visualization of subcellular protein localization, and detection of cell-cell contact. To expand this toolset, we have developed a screening strategy for the direct engineering of self-complementing split FPs. Via this strategy, we have generated a yellow-green split-mNeonGreen21-10/11 that improves the ratio of complemented signal to the background of FP1-10-expressing cells compared to the commonly used split-GFP1-10/11, as well as a 10-fold brighter red-colored split-sfCherry21-10/11. Based on split-sfCherry2, we have engineered a photoactivatable variant that enables single-molecule localization-based super-resolution microscopy. We have demonstrated dual-color endogenous protein tagging with sfCherry211 and GFP11, revealing that endoplasmic reticulum translocon complex Sec61B has reduced abundance in certain peripheral tubules. These new split FPs not only offer multiple colors for imaging interaction networks of endogenous proteins, but also hold the potential to provide orthogonal handles for biochemical isolation of native protein complexes.

bioengineering↗

bioRxiv2017

Visualization And Label-Free Quantification Of Microfluidic Mixing Using Quantitative Phase Imaging

Microfluidic mixing plays a key role in various fields, including biomedicine and chemical engineering. To date, although various approaches for imaging microfluidic mixing have been proposed, they provide only quantitative imaging capability and require for exogenous labeling agents. Quantitative phase imaging techniques, however, circumvent these problems and offer label-free quantitative information about concentration maps of microfluidic mixing. We present the quantitative phase imaging of microfluidic mixing in various types of PDMS microfluidic channels with different geometries; the feasibility of the present method was validated by comparing it with the results obtained by theoretical calculation based on Ficks law.

bioengineering↗

bioRxiv2017

Enzyme-Free Nucleic Acid Dynamical Systems

Chemistries exhibiting complex dynamics--from inorganic oscillators to gene regulatory networks--have been long known but either cannot be reprogrammed at will, or rely on the sophisticated chemistry underlying the central dogma. Can simpler molecular mechanisms, designed from scratch, exhibit the same range of behaviors? Abstract coupled chemical reactions have been proposed as a programming language for complex dynamics, along with their systematic implementation using short synthetic DNA molecules. We developed this technology for dynamical systems, identifying critical design principles and codifying them into a compiler automating the design process. Using this approach, we built an oscillator containing only DNA components, establishing that Watson-Crick base pairing interactions alone suffice for arbitrarily complex dynamics. Our results argue that autonomous molecular systems that interact with and control their chemical environment can be designed via molecular programming languages.

bioengineering↗

bioRxiv2017

Light Amplification By Biofilm And Its Polarization Dependence

We report amplified, transmitted light intensity, compared to input, when photosynthetic biofilms were placed in the path of Rayleigh scattered, monochromatic light. Enhancement spectrum shows peak at around 505 nm, which corresponds to the pore wall thickness in biofilm ultra-structure, suggesting role of resonant Mie scattering. Enhancement factors differed when biofilms from different stages of growth were used. Enhancement factors were found to depend on the nature of Rayleigh scattering liquid. Polarizing Rayleigh scattered light by the use of polarizers affected the percentage of enhancement. Amplified output is achievable with constructive interference arising out of coherent forward light scattering, a theoretically predicted outcome of Anderson localization of photons. Possible uses of photosynthetic biofilms in organic material based photonic devices have been discussed.

bioengineering↗

bioRxiv2017

Investigating The Functional Consequence Of White Matter Damage: An Automatic Pipeline To Create Longitudinal Disconnection Tractograms

Neurosurgical resection is one of the few opportunities researchers have to image the human brain both prior to and following focal damage. One of the challenges associated with studying brains undergoing surgical resection is that they often do not fit the brain templates most image-processing methodologies are based on, so manual intervention is required to reconcile the pathology and the most extreme cases must be excluded. Manual intervention requires significant time investment and introduces reproducibility concerns. We propose an automatic longitudinal pipeline based on High Angular Resolution Diffusion Imaging acquisitions to facilitate a Pathway Lesion Symptom Mapping analysis relating focal white matter injury to functional deficits. This two-part approach includes (i) automatic segmentation of focal white matter injury from anisotropic power differences, and (ii) modeling disconnection using tractography on the single-subject level, which specifically identifies the disconnections associated with focal white matter damage. The advantages of this approach stem from (1) objective and automatic lesion segmentation and tractogram generation, (2) objective and precise segmentation of affected tissue likely to be associated with damage to long-range white matter pathways (defined by anisotropic power), (3) good performance even in the cases of anatomical distortions by use of nonlinear tensor-based registration in the patient space, which aligns images using white matter contrast. Mapping a system as variable and complex as the human brain requires sample sizes much larger than the current technology can support. This pipeline can be used to execute large-scale, sufficiently powered analyses by meeting the need for an automatic approach to objectively quantify white matter disconnection.\n\nAbbreviations\n\nFundingThis work was supported by the National Institutes of Health [5R01NS066654-05]; KJ was supported by the Department of Defense (DoD) [National Defense Science & Engineering Graduate Fellowship (NDSEG) Program].

bioengineering↗

bioRxiv2017

Aberration-corrected high-NA open-top selective-plane illumination microscopy for biological imaging

AbstractSelective-plane illumination microscopy (SPIM) provides unparalleled advantages for volumetric imaging of living organisms over extended times. However, the spatial configuration of a SPIM system often limits its compatibility with many widely used biological sample holders such as multi-well chambers and plates. To solve this problem, we developed a high numerical aperture (NA) open-top configuration that places both the excitation and detection objectives on the opposite of the sample coverglass. We carried out a theoretical calculation to analyze the structure of the system-induced aberrations. We then experimentally compensated the system aberrations using adaptive optics combined with static optical components, demonstrating near-diffraction-limited performance in imaging fluorescently labeled cells.\n\n(C) 2017 Optical Society of America\n\nOCIS codes: (080.080) Geometric Optics; (110.0110) Imaging systems; (110.0180) Microscopy.

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