High-throughput Mapping Research Articles

Neuroscience Research using Small Animals on a Chip: From Nematodes to Zebrafish Larvae

Implementation of microfluidic technology to study small animal models such as Caenorhabditis elegans worms (soil-dwelling nematodes), Drosophila melanogaster (fruit fly) and larvae of Danio rerio (zebrafish) provides great opportunities for in vivo quantification of neuronal activities and behavioral responses. By controlling the internal environment, microfluidic devices can manipulate animal models with precision and cause minimal damage to the specimen. Due to these advantages, microfluidic devices have been applied to high-throughput drug screening, high-throughput brain-wide activity mapping, analyzing animals’ neuronal and behavioral responses to different external stimuli, microinjection, and neuronal regeneration. In this paper, we review different microfluidic devices and techniques that allow the manipulation of small animal models to study brain functions and behavioral responses. Furthermore, biomedical applications of microfluidic systems, technical challenges, and future directions in the whole brain and animal research on a chip will be discussed.

Comprehensive epitope mapping using polyclonally expanded human CD8 T cells and a two-step ELISpot assay for testing large peptide libraries

The genetic diversity of circulating HIV-1 strains poses a major barrier to the design, development and evaluation of HIV-1 vaccines. The assessment of both vaccine- and natural infection-elicited T cell responses is commonly done with multivalent peptides that are designed to maximally capture the diversity of potential T cell epitopes (PTEs) observed in natural circulating sequences. However, depending on the sequence diversity of viral subtypes and number of the HIV immunogens under investigation, PTE estimates, including HLA-guided computational methods, can easily generate enormous peptide libraries. Evaluation of T cell epitope specificity using such extensive peptide libraries is usually limited by sample availability, even for high-throughput and robust epitope mapping techniques like ELISpot assays. Here we describe a novel, two-step protocol for in-vitro polyclonal expansion of CD8 T cells from a single vial of frozen PBMC, which facilitated the screening 441 HIV-1 Gag peptides for immune responses among 32 HIV-1 positive subjects and 40 HIV-1 negative subjects for peptide qualification. Using a pooled-peptide mapping strategy, epitopes were mapped in two sequential ELISpot assays; the first ELISpot screened 33 large peptide pools using CD8 T cells expanded for 7 days, while the second step tested pool-matrix peptides to identify individual peptides using CD8 T cells expanded for 10 days. This comprehensive epitope screening established the breadth and magnitude of HIV-1 Gag-specific CD8 T cells and further revealed the extent of immune responses to variable/polymorphic epitopes.

Rapid, low-cost, and in-situ analysis of per- and polyfluoroalkyl substances in soils and sediments by ambient 3D-printed cone spray ionization mass spectrometry

A rapid method to empirically determine the presence of trace per- and polyfluoroalkyl substances (PFAS) in solid media, such as soils, sands, and sediments, without any sample preparation, through ambient ionization mass spectrometry (MS), is described. 3D-printed cone spray ionization (3D-PCSI) is an ambient ionization technique that employs a 3D-printed conductive plastic cone to perform both sampling and ionization. The 3D-PCSI sources are fabricated in the shape of a hollowed square pyramid to hold bulk matrices, and consist of rigid walls to aid in the uniformity and consistency of sampling and ionization. Solid samples are placed within the hollowed pyramid and a solvent is added to perform an in-situ extraction, followed by spray-based ionization when a voltage is applied. The low cost of 3D-printing, its reproducibility at scale, and lack of sample preparation, enables 3D-PCSI-MS to rapidly and efficiently screen for trace PFAS, in-situ, in bulk samples. Demonstrated here is the detection of trace PFAS that were doped into six different soil and sediment matrices, by 3D-PCSI-MS, to validate the universality of the method, irrespective of matrix composition. All PFAS were identified by their indicative MS3 spectra and ranged in detection limits from 100 ppt to 10 ppb depending on the compound and soil classification. Legacy aqueous film forming foams (AFFF) were analyzed in soil by 3D-PCSI-MS, as were soil samples collected around an AFFF testing facility. The sampling rate for 3D-PCSI-MS was less than 2 min per sample, demonstrating the applicability to high-throughput mapping of a contaminated area.

High-throughput whole-brain mapping of rhesus monkey at micron resolution

High-throughput whole-brain mapping of rhesus monkey at micron resolution

Transcriptome-wide high-throughput mapping of protein\u2013RNA occupancy profiles using POP-seq

Interaction between proteins and RNA is critical for post-transcriptional regulatory processes. Existing high throughput methods based on crosslinking of the protein–RNA complexes and poly-A pull down are reported to contribute to biases and are not readily amenable for identifying interaction sites on non poly-A RNAs. We present Protein Occupancy Profile-Sequencing (POP-seq), a phase separation based method in three versions, one of which does not require crosslinking, thus providing unbiased protein occupancy profiles on whole cell transcriptome without the requirement of poly-A pulldown. Our study demonstrates that ~ 68% of the total POP-seq peaks exhibited an overlap with publicly available protein–RNA interaction profiles of 97 RNA binding proteins (RBPs) in K562 cells. We show that POP-seq variants consistently capture protein–RNA interaction sites across a broad range of genes including on transcripts encoding for transcription factors (TFs), RNA-Binding Proteins (RBPs) and long non-coding RNAs (lncRNAs). POP-seq identified peaks exhibited a significant enrichment (p value < 2.2e−16) for GWAS SNPs, phenotypic, clinically relevant germline as well as somatic variants reported in cancer genomes, suggesting the prevalence of uncharacterized genomic variation in protein occupied sites on RNA. We demonstrate that the abundance of POP-seq peaks increases with an increase in expression of lncRNAs, suggesting that highly expressed lncRNA are likely to act as sponges for RBPs, contributing to the rewiring of protein–RNA interaction network in cancer cells. Overall, our data supports POP-seq as a robust and cost-effective method that could be applied to primary tissues for mapping global protein occupancies.

Organ-specific, multimodal, wireless optoelectronics for high-throughput phenotyping of peripheral neural pathways

The vagus nerve supports diverse autonomic functions and behaviors important for health and survival. To understand how specific components of the vagus contribute to behaviors and long-term physiological effects, it is critical to modulate their activity with anatomical specificity in awake, freely behaving conditions using reliable methods. Here, we introduce an organ-specific scalable, multimodal, wireless optoelectronic device for precise and chronic optogenetic manipulations in vivo. When combined with an advanced, coil-antenna system and a multiplexing strategy for powering 8 individual homecages using a single RF transmitter, the proposed wireless telemetry enables low cost, high-throughput, and precise functional mapping of peripheral neural circuits, including long-term behavioral and physiological measurements. Deployment of these technologies reveals an unexpected role for stomach, non-stretch vagal sensory fibers in suppressing appetite and demonstrates the durability of the miniature wireless device inside harsh gastric conditions.

Antibody Binding Epitope Mapping (AbMap) of Hundred Antibodies in a Single Run

Antibodies play essential roles in both diagnostics and therapeutics. Epitope mapping is essential to understand how an antibody works and to protect intellectual property. Given the millions of antibodies for which epitope information is lacking, there is a need for high-throughput epitope mapping. To address this, we developed a strategy, Antibody binding epitope Mapping (AbMap), by combining a phage displayed peptide library with next-generation sequencing. Using AbMap, profiles of the peptides bound by 202 antibodies were determined in a single test, and linear epitopes were identified for >50% of the antibodies. Using spike protein (S1 and S2)-enriched antibodies from the convalescent serum of one COVID-19 patient as the input, both linear and potentially conformational epitopes of spike protein specific antibodies were identified. We defined peptide-binding profile of an antibody as the binding capacity (BiC). Conceptually, the BiC could serve as a systematic and functional descriptor of any antibody. Requiring at least one order of magnitude less time and money to map linear epitopes than traditional technologies, AbMap allows for high-throughput epitope mapping and creates many possibilities.

Quantitative Genetic Screens for Mapping Bacterial Pathways and Functional Networks.

Escherichia coli synthetic genetic array (eSGA) screening procedure enables high-throughput systematic mapping of pairwise genetic interactions in E. coli. The eSGA method exploits E. coli's rapid growth, its ease of genetic manipulation, and efficient genetic exchange via conjugation. Replica pinning is used to grow and mate arrayed sets of single gene mutant strains as well as to select double mutants en masse. Strain fitness, which is the eSGA readout, is determined by the digital imaging of the plates and subsequent colony size measurements. Comparing single and double mutant colony sizes then allows for identifying interacting genes. Using eSGA on a global or a smaller process-centric scale can help reveal gene functions and reconstruct genetic interaction networks with known and novel connections between genes and pathways.

Silver nanoparticle on zinc oxide array for label-free detection of opioids through surface-enhanced raman spectroscopy.

Opioid abuse is a significant public health problem. Over two million Americans have some form of addiction to opioids; however, despite governmental programs established to treat overdoses and restrict opioid distribution, there are still few screening tools that are quantitative, portable and easy to use for high-throughput mapping and monitoring this ongoing crisis. In this paper, we demonstrated a plasmonic zinc oxide (ZnO) arrays-on-silicon sensor for the label-free detection of opioids through surface-enhanced Raman spectroscopy (SERS), and evaluated the chips' opioid sensing performance. Specifically, we tested our device with oxycodone, a potent and commonly abused opioid, dissolved in methanol and blood serum as a proof-of-concept study. Ag particles were in situ patterned onto the ZnO array to form the completed sensing platform. The resulting Ag@ZnO arrays were characterized using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Analysis (EDS), and element mapping. In addition, the enhanced electric field induced by the localized surface plasmonic resonance at the Ag particle decorated ZnO is simulated using COMSOL. Opioid-containing samples at varying concentrations, from 900 μg mL−1 to 90 ng mL−1 were tested using SERS to characterize the chip's accuracy and sensitivity. We demonstrated that the sensor can reliably detect opioid concentrations as low as 90 ng mL−1 with great accuracy and sensitivity even spiked into blood serum. The chips could provide a cost-effective, high-throughput method for detecting opiate oxycodone, thereby providing a powerful tool to monitor and control the emerging public health threats.

In Vivo Tracking of Hematopoietic Stem and Progenitor Cell Ontogeny by Cellular Barcoding.

Cellular barcoding is a powerful technique that allows for high-throughput mapping of the fate of single cells, notably hematopoietic stem and progenitor cells (HSPCs) after transplantation. Unique artificial DNA fragments, termed barcodes, are stably inserted into HSPCs using lentiviral transduction, making sure that each individual cell receives a single unique barcode. Barcoded HSPCs are transplanted into sublethally irradiated mice where they reconstitute the hematopoietic system through proliferation and differentiation. During this process, the barcode of each HSPC is inherited by all of its daughter cells and their subsequent mature hematopoietic cell progeny. After sorting mature hematopoietic cell subsets, their barcodes can be retrieved from genomic DNA through nested PCR and sequencing. Analysis of barcode sequencing results allows for determination of clonal relationships between the mature cells, that is, which cell types were produced by a single barcoded HSPC, as well as the heterogeneity of the initial HSPC population. Here, we give a detailed protocol of a complete HSPC cellular barcoding experiment, starting with barcode lentivirus production, isolation, transduction, and transplantation of HSPCs, isolation of target cells followed by PCR amplification and sequencing of DNA barcodes. Finally, we describe the basic filtering and analysis steps of barcode sequencing data to ensure high-quality results.

Mreža protein-protein interakcija i protein-ligand doking - trenutno stanje i perspektive

Traditional research means, such as in vitro and in vivo models, have consistently been used by scientists to test hypotheses in biochemistry. Computational (in silico) methods have been increasingly devised and applied to testing and hypothesis development in biochemistry over the last decade. The aim of in silico methods is to analyze the quantitative aspects of scientific (big) data, whether these are stored in databases for large data or generated with the use of sophisticated modeling and simulation tools; to gain a fundamental understanding of numerous biochemical processes related, in particular, to large biological macromolecules by applying computational means to big biological data sets, and by computing biological system behavior. Computational methods used in biochemistry studies include proteomics-based bioinformatics, genome-wide mapping of protein-DNA interaction, as well as high-throughput mapping of the protein-protein interaction networks. Some of the vastly used molecular modeling and simulation techniques are Monte Carlo and Langevin (stochastic, Brownian) dynamics, statistical thermodynamics, molecular dynamics, continuum electrostatics, protein-ligand docking, protein-ligand affinity calculations, protein modeling techniques, and the protein folding process and enzyme action computer simulation. This paper presents a short review of two important methods used in the studies of biochemistry - protein-ligand docking and the prediction of protein-protein interaction networks.

Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types.

We developed a high-throughput mapping workflow, which centers on deep learning (DL) convolutional neural network (CNN) algorithms on high-performance distributed computing resources, to automatically characterize ice-wedge polygons (IWPs) from sub-meter resolution commercial satellite imagery. We applied a region-based CNN object instance segmentation algorithm, namely the Mask R-CNN, to automatically detect and classify IWPs in North Slope of Alaska. The central goal of our study was to systematically expound the DLCNN model interoperability across varying tundra types (sedge, tussock sedge, and non-tussock sedge) and image scene complexities to refine the understanding of opportunities and challenges for regional-scale mapping applications. We corroborated quantitative error statistics along with detailed visual inspections to gauge the IWP detection accuracies. We found promising model performances (detection accuracies: 89% to 96% and classification accuracies: 94% to 97%) for all candidate image scenes with varying tundra types. The mapping workflow discerned the IWPs by exhibiting low absolute mean relative error (AMRE) values (0.17–0.23). Results further suggest the importance of increasing the variability of training samples when practicing transfer-learning strategy to map IWPs across heterogeneous tundra cover types. Overall, our findings demonstrate the robust performances of IWPs mapping workflow in multiple tundra landscapes.

Deep learning networks reflect cytoarchitectonic features used in brain mapping

The distribution of neurons in the cortex (cytoarchitecture) differs between cortical areas and constitutes the basis for structural maps of the human brain. Deep learning approaches provide a promising alternative to overcome throughput limitations of currently used cytoarchitectonic mapping methods, but typically lack insight as to what extent they follow cytoarchitectonic principles. We therefore investigated in how far the internal structure of deep convolutional neural networks trained for cytoarchitectonic brain mapping reflect traditional cytoarchitectonic features, and compared them to features of the current grey level index (GLI) profile approach. The networks consisted of a 10-block deep convolutional architecture trained to segment the primary and secondary visual cortex. Filter activations of the networks served to analyse resemblances to traditional cytoarchitectonic features and comparisons to the GLI profile approach. Our analysis revealed resemblances to cellular, laminar- as well as cortical area related cytoarchitectonic features. The networks learned filter activations that reflect the distinct cytoarchitecture of the segmented cortical areas with special regard to their laminar organization and compared well to statistical criteria of the GLI profile approach. These results confirm an incorporation of relevant cytoarchitectonic features in the deep convolutional neural networks and mark them as a valid support for high-throughput cytoarchitectonic mapping workflows.

Needle in a Haystack: The Naïve Repertoire as a Source of T Cell Receptors for Adoptive Therapy with Engineered T Cells.

T cell engineering with antigen-specific T cell receptors (TCRs) has allowed the generation of increasingly specific, reliable, and versatile T cell products with near-physiological features. However, a broad applicability of TCR-based therapies in cancer is still limited by the restricted number of TCRs, often also of suboptimal potency, available for clinical use. In addition, targeting of tumor neoantigens with TCR-engineered T cell therapy moves the field towards a highly personalized treatment, as tumor neoantigens derive from somatic mutations and are extremely patient-specific. Therefore, relevant TCRs have to be de novo identified for each patient and within a narrow time window. The naïve repertoire of healthy donors would represent a reliable source due to its huge diverse TCR repertoire, which theoretically entails T cells for any antigen specificity, including tumor neoantigens. As a challenge, antigen-specific naïve T cells are of extremely low frequency and mostly of low functionality, making the identification of highly functional TCRs finding a “needle in a haystack.” In this review, we present the technological advancements achieved in high-throughput mapping of patient-specific neoantigens and corresponding cognate TCRs and how these platforms can be used to interrogate the naïve repertoire for a fast and efficient identification of rare but therapeutically valuable TCRs for personalized adoptive T cell therapy.

High-throughput mapping method for mechanical properties, oxidation resistance, and phase stability in Ni-based superalloys using composition-graded unidirectional solidified alloys

We propose a new approach for the high-throughput experimental evaluation of the phase stability, mechanical and oxidation properties of a Ni-based superalloy. The Bridgman method is used to introduce the gradation of nine elements in a long distance (∼24 mm) and a wide range of microstructural features with η, μ and γ’ phase volume fractions in one sample. Nanoindentation and microstructural observations are utilized to extract the elastic modulus/hardness of a γ-γ’ two-phase structure and evaluate the oxidation layers in an oxidized sample. Our approach makes it possible to obtain huge number of datasets linked to the composition and microstructure of the superalloys.

Pacific Biosciences assembly with Hi-C mapping generates an improved, chromosome-level goose genome.

ABSTRACTBackgroundThe domestic goose is an economically important and scientifically valuable waterfowl; however, a lack of high-quality genomic data has hindered research concerning its genome, genetics, and breeding. As domestic geese breeds derive from both the swan goose (Anser cygnoides) and the graylag goose (Anser anser), we selected a female Tianfu goose for genome sequencing. We generated a chromosome-level goose genome assembly by adopting a hybrid de novo assembly approach that combined Pacific Biosciences single-molecule real-time sequencing, high-throughput chromatin conformation capture mapping, and Illumina short-read sequencing.FindingsWe generated a 1.11-Gb goose genome with contig and scaffold N50 values of 1.85 and 33.12 Mb, respectively. The assembly contains 39 pseudo-chromosomes (2n = 78) accounting for ∼88.36% of the goose genome. Compared with previous goose assemblies, our assembly has more continuity, completeness, and accuracy; the annotation of core eukaryotic genes and universal single-copy orthologs has also been improved. We have identified 17,568 protein-coding genes and a repeat content of 8.67% (96.57 Mb) in this genome assembly. We also explored the spatial organization of chromatin and gene expression in the goose liver tissues, in terms of inter-pseudo-chromosomal interaction patterns, compartments, topologically associating domains, and promoter-enhancer interactions.ConclusionsWe present the first chromosome-level assembly of the goose genome. This will be a valuable resource for future genetic and genomic studies on geese.

High-throughput mapping of the phage resistance landscape in E. coli.

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage-specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

Atomic-Scale Studies of Overlapping Grain Boundaries between Parallel and Quasi-Parallel Grains in Low-Symmetry Monolayer ReS2

Summary Grain boundaries (GBs) are significant microstructures that dominate properties of polycrystalline two-dimensional (2D) materials. Low-symmetry rhenium disulfide monolayers provide an ideal platform to investigate diverse configurations of GBs and their orientation-dependent characteristics. Here, we utilize the preferential deposition of platinum-based nanoparticles on grain edges to rapidly locate nanoscale-wide overlapping GBs during microscopic-scale observation. Atomic-resolution investigations by aberration-corrected annular dark-field scanning transmission electron microscopy reveal diverse overlapping GBs constructed by parallel grains with transversal displacement. They prefer to align along several primary lattice directions with different interlayer atomic registries. Calculations show that the electronic band structures of overlapping GBs are strongly direction dependent, suggesting their potential in tunable electronic and photonic devices. Incommensurate overlapping GBs formed by quasi-parallel grains with ultrasmall twist angles are also observed. These results unveil the rich polymorphism of GBs and new opportunities to tailor properties of anisotropic 2D materials via GB engineering.

13C tracer deposition in EAST D and He plasmas investigated by high-throughput deuteron nuclear reaction analysis mapping

Abstract Rare isotope tracer injection represents an established way for following particle transport in fusion research, but a tracer experiment is only as good as the tracer can be followed and separated from the common isotope. Physical models for transport analysis such as ERO2.0 require accurate total amounts of deposition with high spatial resolution. This work describes an extended high throughput NRA post analysis approach together with the surface analysis results of 2 technically rough graphite-tiles of 150x150 mm2 surface area exposed to D and He plasmas in EAST. The applied 1.43 MeV deuteron beam NRA offers percent range accuracy for layer thicknesses ranging from few 10 nm to 20 µm. Optimisation of the beam line and beam optics enables operation with ≤20 nA without reaching critical radiation levels, resulting in a measurement time of 5–10 s per spot. This enabled acquiring in total 3070 NRA points on the central 46 × 46 mm2 cut-outs of each sample and an adjacent part of equal size within 12 h of analysis time. The layers contained 50–60% D, ~2% 12C, and ~3% O. The central 20 mm radius around the injection hole contains 98% of the total 13C deposition. NRA finds up to 5.8 ± 0.9 × 1022 13C/m2 close to the hole with an e-folding fall-off length of about 3–10 mm in every radial direction. In the D discharge 24 ± 2% and 16 ± 2% in He of the injected 13C are found on the tiles with triangle shaped deposition profiles following ExB. The comparison to colour fringe analysis and SIMS reveals the particular strength of D-NRA regarding roughness, thick layers, and the separation of 12C and 13C deposits, but in compatible regions all methods agree. Compared to these, the NRA yields additional information indicating depositing species and physical processes.

Phage-DMS: A Comprehensive Method for Fine Mapping of Antibody Epitopes.

SummaryUnderstanding the antibody response is critical to developing vaccine and antibody-based therapies and has inspired the recent development of new methods to isolate antibodies. Methods to define the antibody-antigen interactions that determine specificity or allow escape have not kept pace. We developed Phage-DMS, a method that combines two powerful approaches—immunoprecipitation of phage peptide libraries and deep mutational scanning (DMS)—to enable high-throughput fine mapping of antibody epitopes. As an example, we designed sequences encoding all possible amino acid variants of HIV Envelope to create phage libraries. Using Phage-DMS, we identified sites of escape predicted using other approaches for four well-characterized HIV monoclonal antibodies with known linear epitopes. In some cases, the results of Phage-DMS refined the epitope beyond what was determined in previous studies. This method has the potential to rapidly and comprehensively screen many antibodies in a single experiment to define sites essential for binding interactions.