Unraveling the interplay between the leucine zipper and forkhead domains of FOXP2: Implications for DNA binding, stability and dynamics.

FOXP2 is a transcription factor associated with speech and language. Like other FOX transcription factors, it has a DNA binding region called the forkhead domain (FHD). This domain can exist as a monomer or a domain swapped dimer. In addition to the FHD, the leucine zipper region (LZ) of FOXP2 is also believed to be associated with both DNA binding and oligomerization. To better understand the relationship between DNA binding and oligomerization of FOXP2, we investigated its structure, stability and dynamics, focusing specifically on the FHD and the LZ. We did this by using two constructs: one containing the isolated FHD and one containing both the LZ and the FHD (LZ-END). We demonstrate in this work, that while the FHD maintains a monomeric form that is capable of binding DNA, the LZ-END undergoes a dynamic transition between oligomeric states in the presence of DNA. Our findings suggest that FOXP2's LZ domain influences DNA binding affinity through a change in oligomeric state. We show through hydrogen exchange mass spectroscopy that certain parts of the FHD and interlinking region become less dynamic when in the presence of DNA, confirming DNA binding and oligomerization in these regions. Moreover, the detection of a stable equilibrium intermediate state during LZ-END unfolding supports the idea of cooperation between these two domains. Overall, our study sheds light on the interplay between two FOXP2 domains, providing insight into the protein's ability to respond dynamically to DNA, and enriching our understanding of FOXP2's role in gene regulation.

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome.

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 µL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.

A Semiautomated Proteomics and Phosphoproteomics Protocol for the Identification of Novel Therapeutic Targets and Predictive Biomarkers in In Vivo Xenograft Models of Pediatric Cancers.

Genomic profiling has identified therapeutic targets for precision treatment of certain cancers, but many patients lack actionable mutations. Additional omics approaches, like proteomics and phosphoproteomics, are essential for comprehensive mapping of cancer-associated molecular phenotypes. In vivo models, such as cell line and patient-derived xenografts (PDX), offer valuable insights into cancer biology and treatment strategies.This chapter presents a semiautomated high-throughput workflow for integrated proteomics and phosphoproteomics analysis on the Kingfish platform coupled with MagReSyn® Zr-IMAC HP. It enhances protein extraction from in vivo xenograft samples and provides better insights into cancers with poor prognosis. The approach successfully identified over 11,000 unique phosphosites and ~6000 proteins in SJSA-1 pediatric osteosarcoma xenografts, demonstrating its efficacy. This workflow is a valuable tool for studying tumor biology and developing precision oncology strategies.

Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort.

BACKGROUND: Hypertension is an important public health priority with a high prevalence in Africa. It is also an independent risk factor for kidney outcomes. We aimed to identify potential proteins and pathways involved in hypertension-associated albuminuria by assessing urinary proteomic profiles in black South African participants with combined hypertension and albuminuria compared to those who have neither condition. METHODS: The study included 24 South African cases with both hypertension and albuminuria and 49 control participants who had neither condition. Protein was extracted from urine samples and analysed using ultra-high-performance liquid chromatography coupled with mass spectrometry. Data were generated using data-independent acquisition (DIA) and processed using Spectronaut™ 15. Statistical and functional data annotation were performed on Perseus and Cytoscape to identify and annotate differentially abundant proteins. Machine learning was applied to the dataset using the OmicLearn platform. RESULTS: Overall, a mean of 1,225 and 915 proteins were quantified in the control and case groups, respectively. Three hundred and thirty-two differentially abundant proteins were constructed into a network. Pathways associated with these differentially abundant proteins included the immune system (q-value [false discovery rate] = 1.4 × 10- 45), innate immune system (q = 1.1 × 10- 32), extracellular matrix (ECM) organisation (q = 0.03) and activation of matrix metalloproteinases (q = 0.04). Proteins with high disease scores (76-100% confidence) for both hypertension and chronic kidney disease included angiotensinogen (AGT), albumin (ALB), apolipoprotein L1 (APOL1), and uromodulin (UMOD). A machine learning approach was able to identify a set of 20 proteins, differentiating between cases and controls. CONCLUSIONS: The urinary proteomic data combined with the machine learning approach was able to classify disease status and identify proteins and pathways associated with hypertension-associated albuminuria.

Secretomics reveals hormone-therapy of breast cancer may induce survival by facilitating hypercoagulation and immunomodulation in vitro.

Tumour cell haematogenous dissemination is predicated on molecular changes that enhance their capacity for invasion and preparation of the pre-metastatic niche. It is increasingly evident that platelets play an essential role in this transformation. The systemic nature of signalling molecules and extravascular factors that participate in mediating platelet-tumour cell interactions led to the development of an in vitro co-culture using whole blood and breast tumour cells, allowing us to decipher the impact of hormone-therapy on tumour cells and associated changes in the plasma proteome. Using mass spectrometry, we determined dysregulation of proteins associated with maintaining an invasive tumour phenotype. Tumour changes in genes associated with EMT and survival were documented. This is postulated to be induced via tumour cell interactions with the coagulatory and immune systems. Results highlight tumour cell adaptability to both treatment and blood resulting in a pro-tumorigenic response and a hypercoagulatory state. We illustrate that the breast cancer cell secretome can be altered by hormone-therapy, subject to the tumour subphenotype and linked to platelet activation. More sophisticated co-culture systems are required to recapitulate these interactions to better understand tumorigenesis. Moreover, deeper plasma profiling, using abundant protein depleted and/or vesicle enriched strategies, will likely reveal additional secretory proteins related to tumour cell-platelet interactions.

Assessing the dynamics and macromolecular interactions of the intrinsically disordered protein YY1.

YY1 is a ubiquitously expressed, intrinsically disordered transcription factor involved in neural development. The oligomeric state of YY1 varies depending on the environment. These structural changes may alter its DNA binding ability and hence its transcriptional activity. Just as YY1's oligomeric state can impact its role in transcription, so does its interaction with other proteins such as FOXP2. The aim of this work is to study the structure and dynamics of YY1 so as to determine the influence of oligomerisation and associations with FOXP2 on its DNA binding mechanism. The results confirm that YY1 is primarily a disordered protein, but it does consist of certain specific structured regions. We observed that YY1 quaternary structure is a heterogenous mixture of oligomers, the overall size of which is dependent on ionic strength. Both YY1 oligomerisation and its dynamic behaviour are further subject to changes upon DNA binding, whereby increases in DNA concentration result in a decrease in the size of YY1 oligomers. YY1 and the FOXP2 forkhead domain were found to interact with each other both in isolation and in the presence of YY1-specific DNA. The heterogeneous, dynamic multimerisation of YY1 identified in this work is, therefore likely to be important for its ability to make heterologous associations with other proteins such as FOXP2. The interactions that YY1 makes with itself, FOXP2 and DNA form part of an intricate mechanism of transcriptional regulation by YY1, which is vital for appropriate neural development.

Urine-HILIC: Automated Sample Preparation for Bottom-Up Urinary Proteome Profiling in Clinical Proteomics.

Urine provides a diverse source of information related to a patient's health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at ≥8.35-fold change in abundance, ≥2 unique peptides and ≤1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

Protocol for high-throughput semi-automated label-free- or TMT-based phosphoproteome profiling.

Tandem mass tags data-dependent acquisition (TMT-DDA) as well as data-independent acquisition-based label-free quantification (LFQ-DIA) have become the leading workflows to achieve deep proteome and phosphoproteome profiles. We present a modular pipeline for TMT-DDA and LFQ-DIA that integrates steps to perform scalable phosphoproteome profiling, including protein lysate extraction, clean-up, digestion, phosphopeptide enrichment, and TMT-labeling. We also detail peptide and/or phosphopeptide fractionation and pre-mass spectrometry desalting and provide researchers guidance on choosing the best workflow based on sample number and input. For complete details on the use and execution of this protocol, please refer to Koenig et al.1 and Martínez-Val et al.2.

SAPrIm, a semi-automated protocol for mid-throughput immunopeptidomics.

Human leukocyte antigen (HLA) molecules play a crucial role in directing adaptive immune responses based on the nature of their peptide ligands, collectively coined the immunopeptidome. As such, the study of HLA molecules has been of major interest in the development of cancer immunotherapies such as vaccines and T-cell therapies. Hence, a comprehensive understanding and profiling of the immunopeptidome is required to foster the growth of these personalised solutions. We herein describe SAPrIm, an Immunopeptidomics tool for the Mid-Throughput era. This is a semi-automated workflow involving the KingFisher platform to isolate immunopeptidomes using anti-HLA antibodies coupled to a hyper-porous magnetic protein A microbead, a variable window data independent acquisition (DIA) method and the ability to run up to 12 samples in parallel. Using this workflow, we were able to concordantly identify and quantify ~400 - 13000 unique peptides from 5e5 - 5e7 cells, respectively. Overall, we propose that the application of this workflow will be crucial for the future of immunopeptidome profiling, especially for mid-size cohorts and comparative immunopeptidomics studies.

Experimental Ultrasound Approach for Studying Knee Intra-Articular Femur-Tibia Movements under Different Loads.

The purpose of the present study was to develop an experimental model for the study of intra-articular knee movements depending on the function of the knee joint and involved muscle groups under isometric stretching conditions with different loads. The experimental procedure included an ultrasound examination of a knee joint after isometric stretching in healthy men (n = 32). The changes (in millimeters) in the distances between the femur and tibia were measured using an ultrasound sonographer at three stages. The first stage was performed on ten (n = 10) healthy men in five different sitting and upright positions. In the second and third experimental model stages, lower limbs loading was applied to 22 participants. Our hypothesis, which was confirmed, was that as a result of increased loads on the participant's back, an intra-articular decrease in the femur-tibia cartilage surface distance would be observed. The accuracy of the created experimental model was improved over its three stages from 30% to 9%. Quantitative model data can help to create a mathematical model of the mechanical effects during the deformation of knee joint bone cartilage and it can also help outline some future tasks: increasing loading weights, enlarging participant groups, performing comparisons of men and women, and performing comparisons of healthy and pathological individuals.

Covalent binding of human two-domain CD4 to an HIV-1 subtype C SOSIP.664 trimer modulates its structural dynamics.

The human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein (Env) mediates host cell infection by binding to the cellular receptor CD4. Recombinant Env bound to CD4 has been explored for its potential as an HIV vaccine immunogen as receptor binding exposes otherwise shielded, conserved functional sites. Previous preclinical studies showed an interchain disulphide linkage facilitated between Env and 2dCD4S60C generates an immunogenic complex that elicits potent, broadly neutralizing antibodies (bNAbs) against clinically relevant HIV-1. This study investigated conformational dynamics of 2dCD4WT and 2dCD4S60C bound to an HIV-1C SOSIP.664 Env trimer using hydrogen-deuterium exchange mass spectrometry. The Env:2dCD4S60C complex maintains key contact residues required for MHCII and Env/gp120 binding and the residues encompassing Ibalizumab's epitope. Important residues remaining anchored, with an increased flexibility in surrounding regions, evidenced by the higher exchange seen in flanking residues compared to Env:2dCD4WT. While changes in Env:2dCD4S60C dynamics in domain 1 were moderate, domain 2 exhibited greater variation. Lack of stability-inducing H-bonds in these allosteric sites suggest the improved immunogenicity of Env:2dCD4S60C result from exposed CD4 residues providing diverse/novel antigenic targets for the development of potent, broadly neutralizing Ibalizumab-like antibodies.

Transcriptome and proteome of the corm, leaf and flower of Hypoxis hemerocallidea (African potato).

The corm of Hypoxis hemerocallidea, commonly known as the African potato, is used in traditional medicine to treat several medical conditions such as urinary infections, benign prostate hyperplasia, inflammatory conditions and testicular tumours. The metabolites contributing to the medicinal properties of H. hemerocallidea have been identified in several studies and, more recently, the active terpenoids of the plant were profiled. However, the biosynthetic pathways and the enzymes involved in the production of the terpene metabolites in H. hemerocallidea have not been characterised at a transcriptomic or proteomic level. In this study, total RNA extracted from the corm, leaf and flower tissues of H. hemerocallidea was sequenced on the Illumina HiSeq 2500 platform. A total of 143,549 transcripts were assembled de novo using Trinity and 107,131 transcripts were functionally annotated using the nr, GO, COG, KEGG and SWISS-PROT databases. Additionally, the proteome of the three tissues were sequenced using LC-MS/MS, revealing aspects of secondary metabolism and serving as data validation for the transcriptome. Functional annotation led to the identification of numerous terpene synthases such as nerolidol synthase, germacrene D synthase, and cycloartenol synthase amongst others. Annotations also revealed a transcript encoding the terpene synthase phytoalexin momilactone A synthase. Differential expression analysis using edgeR identified 946 transcripts differentially expressed between the three tissues and revealed that the leaf upregulates linalool synthase compared to the corm and the flower tissues. The transcriptome as well as the proteome of Hypoxis hemerocallidea presented here provide a foundation for future research.

Zirconium(IV)-IMAC Revisited: Improved Performance and Phosphoproteome Coverage by Magnetic Microparticles for Phosphopeptide Affinity Enrichment.

Phosphopeptide enrichment is an essential step in large-scale, quantitative phosphoproteomics by mass spectrometry. Several phosphopeptide affinity enrichment techniques exist, such as immobilized metal-ion affinity chromatography (IMAC) and metal oxide affinity chromatography (MOAC). We compared zirconium(IV) IMAC (Zr-IMAC) magnetic microparticles to more commonly used titanium(IV) IMAC (Ti-IMAC) and TiO2 magnetic microparticles for phosphopeptide enrichment from simple and complex protein samples prior to phosphopeptide sequencing and characterization by mass spectrometry (liquid chromatography-tandem mass spectrometry, LC-MS/MS). We optimized sample-loading conditions to increase phosphopeptide recovery for Zr-IMAC-, Ti-IMAC-, and TiO2-based workflows by 22, 24, and 35%, respectively. The optimized protocol resulted in improved performance of Zr-IMAC over Ti-IMAC and TiO2 as well as high-performance liquid chromatography-based Fe(III)-IMAC with up to 23% more identified phosphopeptides. The different enrichment chemistries showed a high degree of overlap but also differences in phosphopeptide selectivity and complementarity. We conclude that Zr-IMAC improves phosphoproteome coverage and recommend that this complementary and scalable affinity enrichment method is more widely used in biological and biomedical studies of cell signaling and the search for biomarkers. Data are available via ProteomeXchange with identifier PXD018273.

Insights from the First Phosphopeptide Challenge of the MS Resource Pillar of the HUPO Human Proteome Project.

Mass spectrometry has greatly improved the analysis of phosphorylation events in complex biological systems and on a large scale. Despite considerable progress, the correct identification of phosphorylated sites, their quantification, and their interpretation regarding physiological relevance remain challenging. The MS Resource Pillar of the Human Proteome Organization (HUPO) Human Proteome Project (HPP) initiated the Phosphopeptide Challenge as a resource to help the community evaluate methods, learn procedures and data analysis routines, and establish their own workflows by comparing results obtained from a standard set of 94 phosphopeptides (serine, threonine, tyrosine) and their nonphosphorylated counterparts mixed at different ratios in a neat sample and a yeast background. Participants analyzed both samples with their method(s) of choice to report the identification and site localization of these peptides, determine their relative abundances, and enrich for the phosphorylated peptides in the yeast background. We discuss the results from 22 laboratories that used a range of different methods, instruments, and analysis software. We reanalyzed submitted data with a single software pipeline and highlight the successes and challenges in correct phosphosite localization. All of the data from this collaborative endeavor are shared as a resource to encourage the development of even better methods and tools for diverse phosphoproteomic applications. All submitted data and search results were uploaded to MassIVE (https://massive.ucsd.edu/) as data set MSV000085932 with ProteomeXchange identifier PXD020801.

SWATH-MS based proteomic profiling of pancreatic ductal adenocarcinoma tumours reveals the interplay between the extracellular matrix and related intracellular pathways.

Pancreatic cancer accounts for 2.8% of new cancer cases worldwide and is projected to become the second leading cause of cancer-related deaths by 2030. Patients of African ancestry appear to be at an increased risk for pancreatic ductal adenocarcinoma (PDAC), with more severe disease and outcomes. The purpose of this study was to map the proteomic and genomic landscape of a cohort of PDAC patients of African ancestry. Thirty tissues (15 tumours and 15 normal adjacent tissues) were obtained from consenting South African PDAC patients. Optimisation of the sample preparation method allowed for the simultaneous extraction of high-purity protein and DNA for SWATH-MS and OncoArray SNV analyses. We quantified 3402 proteins with 49 upregulated and 35 downregulated proteins at a minimum 2.1 fold change and FDR adjusted p-value (q-value) ≤ 0.01 when comparing tumour to normal adjacent tissue. Many of the upregulated proteins in the tumour samples are involved in extracellular matrix formation (ECM) and related intracellular pathways. In addition, proteins such as EMIL1, KBTB2, and ZCCHV involved in the regulation of ECM proteins were observed to be dysregulated in pancreatic tumours. Downregulation of pathways involved in oxygen and carbon dioxide transport were observed. Genotype data showed missense mutations in some upregulated proteins, such as MYPN, ESTY2 and SERPINB8. Approximately 11% of the dysregulated proteins, including ISLR, BP1, PTK7 and OLFL3, were predicted to be secretory proteins. These findings help in further elucidating the biology of PDAC and may aid in identifying future plausible markers for the disease.

Interrogating Fractionation and Other Sources of Variability in Shotgun Proteomes Using Quality Metrics.

The increasing amount of publicly available proteomics data creates opportunities for data scientists to investigate quality metrics in novel ways. QuaMeter IDFree is used to generate quality metrics from 665 RAW files and 97 WIFF files representing publicly available "shotgun" mass spectrometry datasets. These experiments are selected to represent Mycobacterium tuberculosis lysates, mouse MDSCs, and exosomes derived from human cell lines. Machine learning techniques are demonstrated to detect outliers within experiments and it is shown that quality metrics may be used to distinguish sources of variability among these experiments. In particular, the findings demonstrate that according to nested ANOVA performed on an SDS-PAGE shotgun principal component analysis, runs of fractions from the same gel regions cluster together rather than technical replicates, close temporal proximity, or even biological samples. This indicates that the individual fraction may have had a higher impact on the quality metrics than other factors. In addition, sample type, instrument type, mass analyzer, fragmentation technique, and digestion enzyme are identified as sources of variability. From a quality control perspective, the importance of study design and in particular, the run order, is illustrated in seeking ways to limit the impact of technical variability.

Plant-based production of highly potent anti-HIV antibodies with engineered posttranslational modifications.

Broadly neutralising antibodies (bNAbs) against human immunodeficiency virus type 1 (HIV-1), such as CAP256-VRC26 are being developed for HIV prevention and treatment. These Abs carry a unique but crucial post-translational modification (PTM), namely O-sulfated tyrosine in the heavy chain complementarity determining region (CDR) H3 loop. Several studies have demonstrated that plants are suitable hosts for the generation of highly active anti-HIV-1 antibodies with the potential to engineer PTMs. Here we report the expression and characterisation of CAP256-VRC26 bNAbs with posttranslational modifications (PTM). Two variants, CAP256-VRC26 (08 and 09) were expressed in glycoengineered Nicotiana benthamiana plants. By in planta co-expression of tyrosyl protein sulfotransferase 1, we installed O-sulfated tyrosine in CDR H3 of both bNAbs. These exhibited similar structural folding to the mammalian cell produced bNAbs, but non-sulfated versions showed loss of neutralisation breadth and potency. In contrast, tyrosine sulfated versions displayed equivalent neutralising activity to mammalian produced antibodies retaining exceptional potency against some subtype C viruses. Together, the data demonstrate the enormous potential of plant-based systems for multiple posttranslational engineering and production of fully active bNAbs for application in passive immunisation or as an alternative for current HIV/AIDS antiretroviral therapy regimens.

Biochemical Pulldown of mRNAs and Long Noncoding RNAs from Cellular Lysates Coupled with Mass Spectrometry to Identify Protein Binding Partners.

RNA binding proteins (RBPs) interact with cellular mRNAs, controlling various steps throughout the lifetime of these transcripts, including transcription, cellular transport, subcellular localization, translation and degradation. In addition to binding mRNA transcripts, a growing number of RBPs are shown to bind long noncoding RNAs (lncRNAs), controlling key cellular processes, including gene expression and translation of proteins. Current methodologies aimed at identifying and characterizing protein binding partners of specific RNAs of interest typically rely on tagging of the RNA with affinity aptamers, using in vitro transcribed RNA or immobilized oligonucleotides to capture RNA-protein complexes under native conditions. These assays are coupled with mass spectrometry or Western Blot analysis to identify or/and confirm interacting proteins. Here, we describe an alternative approach to identify protein binding partners of mRNAs and large long noncoding RNAs. This approach relies on biochemical pulldown of specific target RNAs and interacting protein partners from cellular lysates coupled with mass spectrometry to identify novel interacting proteins. By using 24-48 ~20 mer biotinylated DNA probes that hybridize to the target RNA, the method ensures high specificity and minimal off target binding. This approach is reproducible and fast and serves as a base for discovery studies to identify proteins that bind to RNAs of interest.

Purification and biochemical characterisation of a putative sodium channel agonist secreted from the South African Knobbly sea anemone Bunodosoma capense.

Voltage gated ion channels have become a subject of investigation as possible pharmaceutical targets. Research has linked the activity of ion channels directly to anti-inflammatory pathways, energy homeostasis, cancer proliferation and painful diabetic neuropathy. Sea anemones secrete a diverse array of bioactive compounds including potassium and sodium channel toxins. A putative novel sodium channel agonist (molecular mass of 4619.7 Da) with a predicted sequence: CLCNSDGPSV RGNTLSGILW LAGCPSGWHN CKKHKPTIGW CCK was isolated from Bunodosoma capense using a modified stimulation technique to induce the secretion of the neurotoxin rich mucus confirmed by an Artemia nauplii bio-assay. The peptide purification combined size-exclusion and reverse-phase high performance liquid chromatography. A thallium-based ion flux assay confirmed the presence of a sodium channel agonist/inhibitor and purity was determined using a modified tricine SDS-PAGE system. The peptide isolated indicated the presence of multiple disulfide bonds in a tight ß-defensin cystine conformation. An IC50 value of 26 nM was determined for total channel inhibition on MCF-7 cells. The unique putative sodium channel agonist initiating with a cystine bond indicates a divergent evolution to those previously isolated from Bunodosoma species.

Publisher Correction: Immune genes are primed for robust transcription by proximal long noncoding RNAs located in nuclear compartments.

In the version of this article initially published, '+' and '-' labels were missing from the graph keys at the bottom of Fig. 8d. The error has been corrected in the HTML and PDF versions of the article.