Low-throughput Approaches Research Articles

Proteomics of prostate cancer serum and plasma using low and high throughput approaches

Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.

Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript.

Translation is a key determinant of gene expression and an important biotechnological engineering target. In bacteria, 5'-untranslated region (5'-UTR) and coding sequence (CDS) are well-known mRNA parts controlling translation and thus cellular protein levels. However, the complex interaction of 5'-UTR and CDS has so far only been studied for few sequences leading to non-generalisable and partly contradictory conclusions. Herein, we systematically assess the dynamic translation from over 1.2 million 5'-UTR-CDS pairs in Escherichia coli to investigate their collective effect using a new method for ultradeep sequence-function mapping. This allows us to disentangle and precisely quantify effects of various sequence determinants of translation. We find that 5'-UTR and CDS individually account for 53% and 20% of variance in translation, respectively, and show conclusively that, contrary to a common hypothesis, tRNA abundance does not explain expression changes between CDSs with different synonymous codons. Moreover, the obtained large-scale data provide clear experimental evidence for a base-pairing interaction between initiator tRNA and mRNA beyond the anticodon-codon interaction, an effect that is often masked for individual sequences and therefore inaccessible to low-throughput approaches. Our study highlights the indispensability of ultradeep sequence-function mapping to accurately determine the contribution of parts and phenomena involved in gene regulation.

BaM-seq and TBaM-seq, highly multiplexed and targeted RNA-seq protocols for rapid, low-cost library generation from bacterial samples.

The ability to profile transcriptomes and characterize global gene expression changes has been greatly enabled by the development of RNA sequencing technologies (RNA-seq). However, the process of generating sequencing-compatible cDNA libraries from RNA samples can be time-consuming and expensive, especially for bacterial mRNAswhich lack poly(A)-tails that are often used to streamline this process for eukaryotic samples. Compared to the increasing throughput and decreasing cost of sequencing, library preparation has had limited advances. Here, we describe bacterial-multiplexed-seq (BaM-seq), an approach that enables simple barcoding of many bacterial RNA samples that decreases the time and cost of library preparation. We also present targeted-bacterial-multiplexed-seq (TBaM-seq) that allows for differential expression analysis of specific gene panels with over 100-fold enrichment in read coverage. In addition, we introduce the concept of transcriptome redistribution based on TBaM-seq that dramatically reduces the required sequencing depth while still allowing for quantification of both highly and lowly abundant transcripts. These methods accurately measure gene expression changes with high technical reproducibility and agreement with gold standard, lower throughput approaches. Together, use of these library preparation protocols allows for fast, affordable generation of sequencing libraries.

Massively Parallel Selection of NanoCluster Beacons.

NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here, a high-throughput selection method is reportedthat takes advantage of repurposed next-generation-sequencing chips to screen the activation fluorescence of ≈40 000activator sequences. It is found that the nucleobases at positions 7-12of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6and 2-4are hotspots to generate yellow-orange and red POTs, respectively. Based on these findings, a "zipper-bag" model is proposed that can explain how these hotspots facilitate the formation of distinct silver cluster chromophores and alter their chemical yields. Combining high-throughput screening with machine-learning algorithms, a pipeline is established to design bright and multicolor NCBs in silico.

Advancing Rare-Earth Separation by Machine Learning.

Constituting the bulk of rare-earth elements, lanthanides need to be separated to fully realize their potential as critical materials in many important technologies. The discovery of new ligands for improving rare-earth separations by solvent extraction, the most practical rare-earth separation process, is still largely based on trial and error, a low-throughput and inefficient approach. A predictive model that allows high-throughput screening of ligands is needed to identify suitable ligands to achieve enhanced separation performance. Here, we show that deep neural networks, trained on the available experimental data, can be used to predict accurate distribution coefficients for solvent extraction of lanthanide ions, thereby opening the door to high-throughput screening of ligands for rare-earth separations. One innovative approach that we employed is a combined representation of ligands with both molecular physicochemical descriptors and atomic extended-connectivity fingerprints, which greatly boosts the accuracy of the trained model. More importantly, we synthesized four new ligands and found that the predicted distribution coefficients from our trained machine-learning model match well with the measured values. Therefore, our machine-learning approach paves the way for accelerating the discovery of new ligands for rare-earth separations.

Measuring the tail: Methods for poly(A) tail profiling.

The 3'-end poly(A) tail is an important and potent feature of most mRNA molecules that affects mRNA fate and translation efficiency. Polyadenylation is a posttranscriptional process that occurs in the nucleus by canonical poly(A) polymerases (PAPs). In some specific instances, the poly(A) tail can also be extended in the cytoplasm by noncanonical poly(A) polymerases (ncPAPs). This epitranscriptomic regulation of mRNA recently became one of the most interesting aspects in the field. Advances in RNA sequencing technologies and software development have allowed the precise measurement of poly(A) tails, identification of new ncPAPs, expansion of the function of known enzymes, discovery and a better understanding of the physiological role of tail heterogeneity, and recognition of a correlation between tail length and RNA translatability. Here, we summarize the development of polyadenylation research methods, including classic low-throughput approaches, Illumina-based genome-wide analysis, and advanced state-of-art techniques that utilize long-read third-generation sequencing with Pacific Biosciences and Oxford Nanopore Technologies platforms. A boost in technical opportunities over recent decades has allowed a better understanding of the regulation of gene expression at the mRNA level. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico.

High-throughput screening of cell-free riboswitches by fluorescence-activated droplet sorting

Cell-free systems that display complex functions without using living cells are emerging as new platforms to test our understanding of biological systems as well as for practical applications such as biosensors and biomanufacturing. Those that use cell-free protein synthesis (CFPS) systems to enable genetically programmed protein synthesis have relied on genetic regulatory components found or engineered in living cells. However, biological constraints such as cell permeability, metabolic stability, and toxicity of signaling molecules prevent development of cell-free devices using living cells even if cell-free systems are not subject to such constraints. Efforts to engineer regulatory components directly in CFPS systems thus far have been based on low-throughput experimental approaches, limiting the availability of basic components to build cell-free systems with diverse functions. Here, we report a high-throughput screening method to engineer cell-free riboswitches that respond to small molecules. Droplet-sorting of riboswitch variants in a CFPS system rapidly identified cell-free riboswitches that respond to compounds that are not amenable to bacterial screening methods. Finally, we used a histamine riboswitch to demonstrate chemical communication between cell-sized droplets.

Investigation of P1/HC-Pro-Mediated ABA/Calcium Signaling Responses via Gene Silencing through High- and Low-Throughput RNA-seq Approaches.

The P1/HC-Pro viral suppressor of potyvirus suppresses posttranscriptional gene silencing (PTGS). The fusion protein of P1/HC-Pro can be cleaved into P1 and HC-Pro through the P1 self-cleavage activity, and P1 is necessary and sufficient to enhance PTGS suppression of HC-Pro. To address the modulation of gene regulatory relationships induced by turnip mosaic virus (TuMV) P1/HC-Pro (P1/HC-ProTu), a comparative transcriptome analysis of three types of transgenic plants (P1Tu, HC-ProTu, and P1/HC-ProTu) were conducted using both high-throughput (HTP) and low-throughput (LTP) RNA-Seq strategies. The results showed that P1/HC-ProTu disturbed the endogenous abscisic acid (ABA) accumulation and genes in the signaling pathway. Additionally, the integrated responses of stress-related genes, in particular to drought stress, cold stress, senescence, and stomatal dynamics, altered the expressions by the ABA/calcium signaling. Crosstalk among the ABA, jasmonic acid, and salicylic acid pathways might simultaneously modulate the stress responses triggered by P1/HC-ProTu. Furthermore, the LTP network analysis revealed crucial genes in common with those identified by the HTP network in this study, demonstrating the effectiveness of the miniaturization of the HTP profile. Overall, our findings indicate that P1/HC-ProTu-mediated suppression in RNA silencing altered the ABA/calcium signaling and a wide range of stress responses.

Distinct Modes of Ongoing Antigen Interactions Shape Intraclonal Dynamics in Splenic Marginal Zone Lymphoma

Almost one-third of all splenic marginal zone lymphoma (SMZL) cases express B cell receptor immunoglobulin (BcR IG) encoded by the IGHV1-2*04 gene. Such cases display a distinctive profile of genomic aberrations (e.g. higher incidence of NOTCH2 and KLF2 mutations) and a more aggressive clinical course compared to SMZL cases utilizing other IGHV genes. Such skewing of the BcR IG gene repertoire implicates antigen selection in SMZL ontogeny. Although the supportive evidence is compelling, it mostly derives from low-throughput approaches, which are inherently limited in their capacity to capture the complexity of the BcR IG gene repertoire. This hinders the comprehensive assessment of the subclonal architecture of SMZL that could offer insight into the dynamics of antigen-IG interactions. Here, we sought to overcome this limitation through a high-throughput immunogenetic investigation of SMZL, focusing on the detailed characterization of somatic hypermutation (SHM) and intraclonal diversification (ID) profiles. Our study included 22 cases utilizing the IGHV1-2*04 gene and 36 cases utilizing other IGHV genes. IGHV-IGHD-IGHJ (IGH) gene rearrangements were PCR-amplified and libraries were sequenced on the Illumina MiSeq platform. Data was analyzed with the IMGT/HighV-QUEST and TRIP software as well as a novel bioinformatics/biostatistics pipeline. Clonotypes were defined as unique combinations of a given IGHV gene+VH CDR3 amino acid (aa) sequence. Only IGH gene rearrangement sequences assigned to the dominant clonotypes of each case were assessed. In detail, all nucleotide variants (nt vars, i.e. all sequences clustered in the same dominant clonotype yet displaying distinct SHM profiles) were identified and further analyzed. Starting from the most abundant nt var, a network was built representing its connections with all other nt vars. For this analysis, we introduce the terms ‘most relevant pathway’ (MRP) corresponding to the pathway including connected nt vars with the highest total number of IGH sequences; and ‘longest mutational pathways’ (LMP) corresponding to the pathways with the highest number of nt vars (Fig. 1). Different graph metrics assessed the impact of ID in different SMZL subgroups: the first one focuses on the ‘most relevant pathway’ and quantifies SHM convergence [ratio of the total number of IGH sequences corresponding to the nt vars of this pathway to the number of IGH sequences in the most abundant nt var]; while the second refers to the length of the ‘longest mutational pathways’.Cases lacking additional connected nt vars [length of the LMP=1; 3 IGHV1-2*04 cases and 4 non-IGHV1-2*04 cases] were excluded. Consequently, the analysis included 19 IGHV1-2*04 cases and 32 non-IGHV1-2*04 cases. Significant differences were noted in the SHM and ID profiles between groups; the IGHV1-2*04 group had significantly (p<0.01) higher convergence values ranging from 0.009 to 1.243 (median: 0.102), as opposed to the non-IGHV1-2*04 group (range: 0.002-1.13, median: 0.014), overall suggesting that stronger selective pressures act in SMZL cases expressing the IGHV1-2*04 versus others. Moreover, IGHV1-2*04 cases displayed significantly (p<0.01) longer mutational pathways (length range: 2-6, median: 3) compared to the other group (range: 2-5, median: 2), alluding to more pronounced ID arising due to ongoing SHM.Finally, all mutations leading to aa changes were analyzed in the context of ID networks. More recurrent aa mutations were identified amongst cases with higher levels of convergence. For instance, the VH FR2 M39I change, one of the most prominent recurrent SHMs in the IGHV1-2*04 group, was found in the most abundant nt var in 13/19 IGHV1-2*04 cases, while it was identified in nt vars with extra mutations in another 3 cases. Of interest, it was present at the end of the mutational pathways in these 16 cases, whilst in the other group it was present only in one case using the IGHV1-2*02 gene, and absent in the rest (p<0.01).In conclusion, in the first large-scale high-throughput immunogenetic analysis of SMZL we provide strong evidence for more pronounced antigenic pressure in cases utilizing IGHV1-2*04 versus other IGHV genes. Our findings highlight a unique subclonal architecture for IGHV1-2*04 SMZL and corroborate the hypothesis that this group may represent a distinct molecular variant of SMZL. [Display omitted] DisclosuresRossi: Abbvie: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Verastem: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Cellestia: Honoraria, Research Funding. Chatzidimitriou: Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Stamatopoulos: Janssen: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding.

Global DNA methylation: role, status and genome-wide approaches to study epigenetic mark in cloned embryos

Somatic cell nuclear transfer (SCNT) technique has been proving its worth for more than two decades now as over 20 different species have been successfully cloned. SCNT protocol for cloning is well established but efficiency in terms of live birth rate is still low. Epigenetic abnormality following nuclear reprogramming is considered as the main culprit behind its low efficiency. DNA methylation is one of the most important epigenetic modifications that directly or indirectly regulate gene expression pattern, development and genome stability. Embryos produced through SCNT are found to express abnormal DNA methylation profile in comparison with in vivo or in vitro produced embryos. In order to improve DNA methylation profile in cloned embryos, a complete database of whole genome is required to find out specific faulty targets. Many techniques including low throughput and high throughput approach has been used to profile DNA methylation pattern in bovine embryos throughout the developmental stages. In the present review, we have compiled the overall status of global DNA methylation, the effect of aberrant DNA methylation on development and evolution in methodologies used for profiling global DNA methylome in cloned embryos.

An Innovative Setup for High-Throughput Respirometry of Small Aquatic Animals

Metabolic rate is often measured as a phenotype in evolutionary genetics, among other fields including many facets of physiology, behavior, and ecology, because it impacts organismal fitness, is repeatable and heritable, and is responsive to numerous environmental variables. Aquatic respirometry, a method used to measure metabolic rate, has allowed key questions in these fields to be investigated, namely: 1) why do individuals from the same population exhibit up to three fold differences in metabolic rate, 2) how does metabolic rate change during an individual’s lifetime, and 3) what metabolic rate is advantageous in a specific environment? Current respirometry studies often suffer from small sample sizes and rely on low throughput approaches to measure metabolic rate, making it difficult to answer these and other relevant ecological and evolutionary questions due to lack of power, failure to capture true biological variation, and confounding variables, like time, that are introduced due to limitations in methodology. Here we describe a scalable high-throughput intermittent flow respirometer (HIFR) design and use it to measure the metabolic rates of 19 aquatic animals in one night while reducing equipment costs and time by more than 50%.

High-Throughput Screening of Biofilm Formation of Listeria monocytogenes on Stainless Steel Coupons Using a 96-Well Plate Format.

Listeria monocytogenes is a foodborne pathogen capable of colonizing and persisting in the food production environment (FPE). While there are a variety of factors involved in L. monocytogenes' ability to persist in FPE, the ability to form biofilms has the potential to increase their chance of survival and long-term colonization. Understanding the mechanisms involved in L. monocytogenes ability to form biofilms may potentially help food safety managers optimize control strategies targeting it in the FPE. In this chapter, a high-throughput method to determine L. monocytogenes ability to attach and form biofilms utilizing FPE-grade stainless steel is described. This method provides fast and efficient results, facilitating scaling up to large numbers of isolates to measure their ability to form biofilms, where lower-throughput approaches can then be utilized to further characterize isolates of interest.

A parallelized, automated platform enabling individual or sequential ChIP of histone marks and transcription factors

Despite its popularity, chromatin immunoprecipitation followed by sequencing (ChIP-seq) remains a tedious (>2 d), manually intensive, low-sensitivity and low-throughput approach. Here, we combine principles of microengineering, surface chemistry, and molecular biology to address the major limitations of standard ChIP-seq. The resulting technology, FloChIP, automates and miniaturizes ChIP in a beadless fashion while facilitating the downstream library preparation process through on-chip chromatin tagmentation. FloChIP is fast (<2 h), has a wide dynamic range (from 106 to 500 cells), is scalable and parallelized, and supports antibody- or sample-multiplexed ChIP on both histone marks and transcription factors. In addition, FloChIP's interconnected design allows for straightforward chromatin reimmunoprecipitation, which allows this technology to also act as a microfluidic sequential ChIP-seq system. Finally, we ran FloChIP for the transcription factor MEF2A in 32 distinct human lymphoblastoid cell lines, providing insights into the main factors driving collaborative DNA binding of MEF2A and into its role in B cell-specific gene regulation. Together, our results validate FloChIP as a flexible and reproducible automated solution for individual or sequential ChIP-seq.

Co-cultured non-marine ostracods from a temporary wetland harbor host-specific microbiota of different metabolic profiles

Rapid development of high-throughput sequencing methods and metagenomics revealed a diverse world of microbiota associated with multicellular organisms. Although recent discoveries indicate that freshwater invertebrates are hosts for specific bacteria, it is still unknown if this specificity is driven by host-derived factors or by the environment, especially in animals with diapause in ephemeral habitats, where parents and offspring are separated in time and space. In this work, using both low-throughput molecular approach and Next-generation sequencing of 16S ribosomal RNA gene, we present a taxonomic analysis of bacteria associated with two species of non-marine ostracods Sclerocypris tuberculata and Potamocypris mastigophora raised from diapausing eggs and co-cultured in laboratory conditions. Our analysis showed that despite sharing the same environment, each ostracod host developed distinct bacterial communities. The major difference was caused by the dominance of the family Comamonadaceae (Betaproteobacteria) in P. mastigophora and the Aeromonadaceae (Gammaproteobacteria) in S. tuberculata. Furthermore, prediction of metabolic pathways in metagenomes, revealed that microbiota of P. mastigophora exhibit higher number of sequences associated with the membrane transport and xenobiotics biodegradation and metabolism. Our study not only provides an insight into microbiota of non-marine ostracods but also shows that different ostracod species host functionally distinct bacterial communities.

Wafer-scale mono-crystalline GeSn alloy on Ge by sputtering and solid phase epitaxy

Germanium-tin (GeSn) alloys are of great interest for electronic as well as photonic applications, and their integration on a group-IV (Si or Ge) platform. This letter describes a low deposition temperature, process integration-friendly, high throughput and low cost approach for growing device-quality GeSn epilayers on Ge substrates. Mono-crystalline, wafer-scale GeSn alloy with 3.4% Sn content was grown on Ge (100) substrates by sputtering an amorphous GeSn layer followed by solid phase epitaxy (SPE) at . Deposition of amorphous layers at room temperature enables incorporation of high bulk Sn content in GeSn epilayers. SPE of the amorphous layer at leads to a strained, high quality GeSn epilayer having a low full width half maximum of , root mean square surface roughness of 0.3 nm and a good GeSn/Ge interface as confirmed through extensive x-ray diffraction measurements, atomic force microscopy and transmission electron microscopy imaging. Additionally, an SiO2 capping layer employed during SPE is shown to prevent Sn out-diffusion and segregation at the surface. To examine electrical properties for potential applications of the GeSn/n-Ge heterostructure, metal/GeSn/n-Ge vertical contact diodes and metal/GeSn circular transfer length method contact structures were fabricated and electrically characterized.

Prospect and challenge of detecting dynamic gene copy number increases in stem cells by whole genome sequencing

Gene amplification is an evolutionarily well-conserved and highly efficient mechanism to increase the amount of specific proteins. In humans, gene amplification is a hallmark of cancer and has recently been found during stem cell differentiation. Amplifications in stem cells are restricted to specific tissue areas and time windows, rendering their detection difficult. Here, we report on the performance of deep WGS sequencing (average 82-fold depth of coverage) on the BGISEQ with nanoball technology to detect amplifications in human mesenchymal and neural stem cells. As reference technology, we applied array-based comparative genomic hybridization (aCGH), fluorescence in situ hybridization (FISH), and qPCR. Using different in silico strategies for amplification detection, we analyzed the potential of WGS for amplification detection. Our results provide evidence that WGS accurately identifies changes of the copy number profiles in human stem cell differentiation. However, the identified changes are not in all cases consistent between WGS and aCGH. The results between WGS and the validation by qPCR were concordant in 83.3% of all tested 36 cases. In sum, both genome-wide techniques, aCGH and WGS, have unique advantages and specific challenges, calling for locus-specific confirmation by the low-throughput approaches qPCR or FISH.Key messagesWGS allows for the identification of dynamic copy number changes in human stem cells.Less stringent threshold setting is crucial for detection of copy number increase.Broad knowledge of dynamic copy number is pivotal to estimate stem cell capabilities.

High-Throughput Site-Directed Mutagenesis.

Protein engineering has an array of uses: whether you are studying a disease mutation, removing undesirable sequences, adding stabilizing mutations for structural purposes, or simply dissecting protein function. Protein engineering is almost exclusively performed using site-directed mutagenesis (SDM) as this provides targeted modification of specific amino acids, as well as the option of rewriting the native sequence to include or exclude certain regions. Despite its widespread use, SDM has often proved to be a bottleneck, requiring precision manipulation on a sample-by-sample basis to make it work. When dealing with large volumes of samples it is not possible to use such a low-throughput approach. Here we describe a high-throughput (HTP) method for SDM, optimized and used by the Structural Genomics Consortium (SGC) to complement structural studies.

Venomics-Accelerated Cone Snail Venom Peptide Discovery.

Cone snail venoms are considered a treasure trove of bioactive peptides. Despite over 800 species of cone snails being known, each producing over 1000 venom peptides, only about 150 unique venom peptides are structurally and functionally characterized. To overcome the limitations of the traditional low-throughput bio-discovery approaches, multi-omics systems approaches have been introduced to accelerate venom peptide discovery and characterisation. This “venomic” approach is starting to unravel the full complexity of cone snail venoms and to provide new insights into their biology and evolution. The main challenge for venomics is the effective integration of transcriptomics, proteomics, and pharmacological data and the efficient analysis of big datasets. Novel database search tools and visualisation techniques are now being introduced that facilitate data exploration, with ongoing advances in related omics fields being expected to further enhance venomics studies. Despite these challenges and future opportunities, cone snail venomics has already exponentially expanded the number of novel venom peptide sequences identified from the species investigated, although most novel conotoxins remain to be pharmacologically characterised. Therefore, efficient high-throughput peptide production systems and/or banks of miniaturized discovery assays are required to overcome this bottleneck and thus enhance cone snail venom bioprospecting and accelerate the identification of novel drug leads.

Development and Application of High-Content Biological Screening for Modulators of NET Production.

Neutrophil extracellular traps (NETs) are DNA-based antimicrobial web-like structures whose release is predominantly mediated by reactive oxygen species (ROS); their purpose is to combat infections. However, unbalanced NET production and clearance is involved in tissue injury, circulation of auto-antibodies and development of several chronic diseases. Currently, there is lack of agreement regarding the high-throughput methods available for NET investigation. This study, therefore, aimed to develop and optimize a high-content analysis (HCA) approach, which can be applied for the assay of NET production and for the screening of compounds involved in the modulation of NET release. A suitable paraformaldehyde fixation protocol was established to enable HCA of neutrophils and NETs. Bespoke and in-built bioinformatics algorithms were validated by comparison with standard low-throughput approaches for application in HCA of NETs. Subsequently, the optimized protocol was applied to high-content screening (HCS) of a pharmaceutically derived compound library to identify modulators of NETosis. Of 56 compounds assessed, 8 were identified from HCS for further characterization of their effects on NET formation as being either inducers, inhibitors or biphasic modulators. The effects of these compounds on naïve neutrophils were evaluated by using specific assays for the induction of ROS and NET production, while their modulatory activity was validated in phorbol 12-myristate 13-acetate-stimulated neutrophils. Results indicated the involvement of glutathione reductase, Src family kinases, molecular-target-of-Rapamycin, and mitogen-activated-protein-kinase pathways in NET release. The compounds and pathways identified may provide targets for novel therapeutic approaches for treating NET-associated pathologies.

Formation of Anisotropic Liquid Crystalline Nanoparticles via Polymerization-Induced Hierarchical Self-Assembly.

Polymeric nanoparticles (NPs) containing liquid crystalline (LC) mesogens with tunable anisotropic morphologies have applications in various fields, but their preparation typically suffers from tedious and low-throughput approaches. Here we present an efficient route to the preparation of anisotropic morphologies of azobenzene-containing block copolymers (BCPs) at high solids content via a polymerization-induced hierarchical self-assembly in ethanol. Various anisotropic NPs, including cuboids, short belts, lamellae, and ellipsoidal vesicles, have been obtained in a remarkably broad range of BCP compositions. The NPs exhibit a smectic phase with ordered stripes when observed under TEM. This internal LC ordering plays a significant role on the formation of these intriguing anisotropic morphologies. Morphological transitions from anisotropic to isotropic spheres can be obtained upon UV illumination due to the photoresponsive properties of the azobenzene mesogens. This work significantly expands the scope of accessible morphologies in PISA and suggests that the under explored LC BCPs may have an impactful role in the PISA field.