A Crystallin Fold in the Interleukin-4-inducing Principle of Schistosoma mansoni Eggs (IPSE/α-1) Mediates IgE Binding for Antigen-independent Basophil Activation

The IL-4-inducing principle from Schistosoma mansoni eggs (IPSE/α-1), the major secretory product of eggs from the parasitic worm S. mansoni, efficiently triggers basophils to release the immunomodulatory key cytokine interleukin-4. Activation by IPSE/α-1 requires the presence of IgE on the basophils, but the detailed molecular mechanism underlying activation is unknown. NMR and crystallographic analysis of IPSEΔNLS, a monomeric IPSE/α-1 mutant, revealed that IPSE/α-1 is a new member of the βγ-crystallin superfamily. We demonstrate that this molecule is a general immunoglobulin-binding factor with highest affinity for IgE. NMR binding studies of IPSEΔNLS with the 180-kDa molecule IgE identified a large positively charged binding surface that includes a flexible loop, which is unique to the IPSE/α-1 crystallin fold. Mutational analysis of amino acids in the binding interface showed that residues contributing to IgE binding are important for IgE-dependent activation of basophils. As IPSE/α-1 is unable to cross-link IgE, we propose that this molecule, by taking advantage of its unique IgE-binding crystallin fold, activates basophils by a novel, cross-linking-independent mechanism.     

A clone-free,single molecule map of the domestic cow (Bos taurus) genome

Background

The cattle (Bos taurus) genome was originally selected for sequencing due to its economic importance and unique biology as a model organism for understanding other ruminants, or mammals. Currently, there are two cattle genome sequence assemblies (UMD3.1 and Btau4.6) from groups using dissimilar assembly algorithms, which were complemented by genetic and physical map resources. However, past comparisons between these assemblies revealed substantial differences. Consequently, such discordances have engendered ambiguities when using reference sequence data, impacting genomic studies in cattle and motivating construction of a new optical map resource--BtOM1.0--to guide comparisons and improvements to the current sequence builds. Accordingly, our comprehensive comparisons of BtOM1.0 against the UMD3.1 and Btau4.6 sequence builds tabulate large-to-immediate scale discordances requiring mediation.

Results

The optical map, BtOM1.0, spanning the B. taurus genome (Hereford breed, L1 Dominette 01449) was assembled from an optical map dataset consisting of 2,973,315 (439 X; raw dataset size before assembly) single molecule optical maps (Rmaps; 1 Rmap = 1 restriction mapped DNA molecule) generated by the Optical Mapping System. The BamHI map spans 2,575.30 Mb and comprises 78 optical contigs assembled by a combination of iterative (using the reference sequence: UMD3.1) and de novo assembly techniques. BtOM1.0 is a high-resolution physical map featuring an average restriction fragment size of 8.91 Kb. Comparisons of BtOM1.0 vs. UMD3.1, or Btau4.6, revealed that Btau4.6 presented far more discordances (7,463) vs. UMD3.1 (4,754). Overall, we found that Btau4.6 presented almost double the number of discordances than UMD3.1 across most of the 6 categories of sequence vs. map discrepancies, which are: COMPLEX (misassembly), DELs (extraneous sequences), INSs (missing sequences), ITs (Inverted/Translocated sequences), ECs (extra restriction cuts) and MCs (missing restriction cuts).

Conclusion

Alignments of UMD3.1 and Btau4.6 to BtOM1.0 reveal discordances commensurate with previous reports, and affirm the NCBI’s current designation of UMD3.1 sequence assembly as the “reference assembly” and the Btau4.6 as the “alternate assembly.” The cattle genome optical map, BtOM1.0, when used as a comprehensive and largely independent guide, will greatly assist improvements to existing sequence builds, and later serve as an accurate physical scaffold for studies concerning the comparative genomics of cattle breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1823-7) contains supplementary material, which is available to authorized users.     

Genetic variants in root architecture-related genes in a Glycine soja accession,a potential resource to improve cultivated soybean

Background

Root system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja.

Results

Wild and cultivated soybean both contributed alleles towards significant additive large effect QTLs on chromosome 6 and 7 for a longer total root length and root distribution, respectively. Epistatic effect QTLs were also identified for taproot length, average diameter, and root distribution. These root traits will influence the water and nutrient uptake in soybean. Two cell division-related genes (D type cyclin and auxin efflux carrier protein) with insertion/deletion variations might contribute to the shorter root phenotypes observed in G. soja compared with cultivated soybean. Based on the location of the QTLs and sequence information from a second G. soja accession, three genes (slow anion channel associated 1 like, Auxin responsive NEDD8-activating complex and peroxidase), each with a non-synonymous single nucleotide polymorphism mutation were identified, which may also contribute to changes in root architecture in the cultivated soybean. In addition, Apoptosis inhibitor 5-like on chromosome 7 and slow anion channel associated 1-like on chromosome 15 had epistatic interactions for taproot length QTLs in soybean.

Conclusion

Rare alleles from a G. soja accession are expected to enhance our understanding of the genetic components involved in root architecture traits, and could be combined to improve root system and drought adaptation in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1334-6) contains supplementary material, which is available to authorized users.     

Induction of G protein-coupled estrogen receptor (GPER) and nuclear steroid hormone receptors by gonadotropins in human granulosa cells

Estradiol and progesterone mediate their actions by binding to classical nuclear receptors, estrogen receptor α (ERα) and estrogen receptor β (ERβ) and progesterone receptor A and B (PR-A and PR-B) and the non-classical G protein-coupled estrogen receptor (GPER). Several animal knock-out models have shown the importance of the receptors for growth of the oocyte and ovulation. The aim of our study was to identify GPER in human granulosa cells (GC) for the first time. Moreover, the effect of different doses of gonadotropins on estrogen and progesterone receptors in the human ovary should be investigated as follicle stimulating hormone (FSH) and luteinizing hormone (LH) are also responsible for numerous mechanisms in the ovary like induction of the steroid biosynthesis. Human GC were cultured in vitro and stimulated with different doses of recombinant human FSH or LH. Receptor expression was analyzed by immunocytochemistry and quantitative real-time RT-PCR. GPER could be identified for the first time in human GC. It could be shown that high concentrations of LH increase GPER protein expression. Furthermore FSH and LH increased ERβ, PR-A and PR-B significantly on protein level. These findings were verified for high doses of FSH and LH on mRNA level. ERα was not affected with FSH or LH. We assume that gonadotropins induce GPER, ERβ and PR in luteinized granulosa cells.     

Proteomic analysis of childhood de novo acute myeloid leukemia and myelodysplastic syndrome/AML: correlation to molecular and cytogenetic analyses

The aim of this study was to investigate the progression of myelodysplastic syndrome (MDS) to acute myeloid leukemia (AML) and to provide additional data regarding the proteomic analysis of AML. The protein profiles obtained were correlated to cytogenetic and molecular analyses. Bone marrow (BM) and peripheral blood (PB) samples were obtained during MDS diagnosis, at MDS transformation to AML, at de novo AML diagnosis and 3 months following treatment. As controls, non-leukemic pediatric patients were studied. Cytogenetic and molecular analyses were carried out by G banding and polymerase chain reaction followed by sequencing, respectively. Differential proteomic analysis was performed by two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry. No significant correlations were noted between protein patterns and cytogenetic or molecular analyses. Certain suppressor genes, metabolic enzymes, immunoglobulins and actin-binding proteins were differentially expressed by BM or PB plasma and cell lysates compared to controls. The obtained data showed that vitamin D and gelsolin played contradicting roles in contributing and restraining leukemogenesis, while MOES, EZRI and AIFM1 could be considered as biomarkers for AML.     

Recombineering BAC transgenes for protein tagging

Protein tagging offers many advantages for proteomic and regulomic research, particularly due to the use of generic and highly sensitive methods that can be applied with reasonable throughput. Ideally, protein tagging is equivalent to having a high affinity antibody for every chosen protein. However, these advantages are compromised if the tagged protein is overexpressed, which is usually the case from cDNA expression vectors. BAC (bacterial artificial chromosome) transgenes present a way to express a chosen protein at physiological levels with all regulatory elements in their native configurations, including cell cycle, alternative splicing and microRNA regulation. Recombineering has become the method of choice for modifying large constructs like BACs. Here, we present a method for protein tagging by recombineering BACs, transfecting cells and evaluating tagged protein expression.     

Inhibin secretion in women with the polycystic ovary syndrome before and after treatment with progesterone

Objectives  

It has been suggested that inhibin secretion is altered in women with the polycystic ovary syndrome (PCOS). However, the contribution of a preceding luteal phase has not been taken into account. The aim of the present study was to investigate whether progesterone in the context of a simulated luteal phase affects basal and FSH-induced inhibin secretion in women with PCOS and elevated LH.     

Proteomics studies of childhood pilocytic astrocytoma

Childhood pilocytic astrocytoma is the most frequent brain tumor affecting children. Proteomics analysis is currently considered a powerful tool for global evaluation of protein expression and has been widely applied in the field of cancer research. In the present study, a series of proteomics, genomics, and bioinformatics approaches were employed to identify, classify and characterize the proteome content of low-grade brain tumors as it appears in early childhood. Through bioinformatics database construction, protein profiles generated from pathological tissue samples were compared against profiles of normal brain tissues. Additionally, experiments of comparative genomic hybridization arrays were employed to monitor for genetic aberrations and sustain the interpretation and evaluation of the proteomic data. The current study confirms the dominance of MAPK pathway for the childhood pilocytic astrocytoma occurrence and novel findings regarding the ERK-2 expression are reported.     

Pressurized Pepsin Digestion in Proteomics: AN AUTOMATABLE ALTERNATIVE TO TRYPSIN FOR INTEGRATED TOP-DOWN BOTTOM-UP PROTEOMICS*

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome.In-depth characterization and quantitation of protein isoforms, including post-translationally modified proteins, are challenging goals of contemporary proteomics. Traditionally, top-down (1, 2) and bottom-up (3, 4) proteomics have been two distinct analytical paths for liquid-based proteomics analysis. Top-down proteomics is the mass spectrometry (MS)-based characterization of intact proteins, whereas bottom-up proteomics requires a chemical or enzymatic proteolytic digestion of all proteins into peptides prior to MS analysis. Both strategies have their own strengths and challenges and can be thought of as complementary rather than competing analytical techniques.In a top-down proteomics approach, proteins are usually separated by one- or two-dimensional liquid chromatography (LC) and identified using high performance MS (5, 6). This approach is very attractive because it allows the identification of protein isoforms arising from various amino acid modifications, genetic variants (e.g. single nucleotide polymorphisms), mRNA splice variants, and multisite modifications (7) (e.g. specific histone modifications) as well as characterization of proteolytic processing events. However, there are several challenges that have limited the broad application of the approach. Typically, intact proteins are less soluble than their peptide complement, which effectively results in greater losses during various stages of sample handling (i.e. limited sensitivity). Similarly, proteins above ∼40–50 kDa in size are more difficult to ionize, detect, and dissociate in most high throughput MS work flows. Additionally, major challenges associated with MS data interpretation and sensitivity, especially for higher molecular mass proteins (>100 kDa) and highly hydrophobic proteins (e.g. integral membrane proteins), remain largely unsolved, thus limiting the applicability of top-down proteomics on a large scale.Bottom-up proteomics approaches have broad application because peptides are easier to separate and analyze via LC coupled with tandem mass spectrometry (MS/MS), offering a basis for more comprehensive protein identification. As this method relies on protein digestion (which produces multiple peptides for each protein), the sample complexity can become exceedingly large, requiring several dimensions of chromatographic separations (e.g. strong cation exchange and/or high pH reversed phase) prior to the final LC separation (typically reversed phase (RP)¹ C₁₈), which is oftentimes directly coupled with the mass spectrometer (3, 8). In general, the bottom-up analysis rarely achieves 100% sequence coverage of the original proteins, which can result in an incorrect/incomplete assessment of protein isoforms and combinatorial PTMs. Additionally, the digested peptides are not detected with uniform efficiency, which challenges and distorts protein quantification efforts.Because the data obtained from top-down and bottom-up work flows are complementary, several attempts have been made to integrate the two strategies (9, 10). Typically, these efforts have utilized extensive fractionation of the intact protein separation followed by bottom-up analysis of the collected fractions. Results so far have encouraged us to consider on-line digestion methods for integrating top-down and bottom-up proteomics in a higher throughput fashion. Such an on-line digestion approach would not only benefit in terms of higher sample throughput and improved overall sensitivity but would also allow a better correlation between the observed intact protein and its peptide digestion products, greatly aiding data analysis and protein characterization efforts.So far, however, none of the on-line integrated methods have proven robust enough for routine high throughput analyses. One of the reasons for this limited success relates to the choice of the proteolytic enzyme used for the bottom-up segment. Trypsin is by far the most widely used enzyme for proteome analyses because it is affordable (relative to other proteases), it has been well characterized for proteome research, and it offers a nice array of detectable peptides due to a fairly even distribution of lysines and arginines across most proteins. However, protein/peptide RPLC separations (optimal at low pH) are fundamentally incompatible with on-line trypsin digestion (optimal at pH ∼ 8) (11, 12). Therefore, on-line coupling of trypsin digestion and RPLC separations is fraught with technological challenges, and proposed solutions (12) have not proven to be robust enough for integration into demanding high throughput platforms.Our approach to this challenge was to investigate alternative proteases that may be more compatible with automated on-line digestion, peptide separation, and MS detection. Pepsin, which is acid-compatible (i.e. it acts in the stomach to initially aid in the digestion of food) (13), is a particularly promising candidate. This protease has previously been successfully used for the targeted analyses of protein complexes, hydrogen/deuterium exchange experiments (14, 15), and characterization of biopharmaceuticals (16, 17). Generally, pepsin preferentially cleaves the peptide bond located on the N-terminal side of hydrophobic amino acids, such as leucine and phenylalanine, although with less specificity than the preferential cleavage observed for trypsin at arginine and lysine. The compatibility of pepsin with typical LC-MS operation makes it an ideal choice for the development of novel approaches combining protein digestion, protein/peptide separation, and MS-based protein/peptide identification.To develop an automated system capable of simultaneously capturing top-down and bottom-up data, enzyme kinetics of the chosen protease must be extremely fast (because one cannot wait hours as is typical when performing off-line proteolysis). Another requirement is the use of immobilized enzyme or a low enough concentration of the enzyme such that autolysis products do not obscure the detection of substrate peptides. The latter was a concern when using pepsin because prior hydrogen/deuterium exchange experiments used enzyme:substrate ratios up to 1:2 (18, 19). To test whether or not such a large concentration of pepsin was necessary, we performed pepsin digestion at ratios of 1:20. Many alternative energy inputs into the system were considered for speeding up the digestion. For instance, it has been shown that an input of ultrasonic energy could accelerate the reaction rate of a typical trypsin digestion while using small amounts of a protease (20). Because ultrasonic energy results in an increase of temperature and microenvironments of high pressure, it has been hypothesized that the higher temperature was the component responsible for the enhanced enzyme activity (21). López-Ferrer et al. (22, 23), however, have demonstrated that application of higher pressure with incorporation of a Barocycler alone can make trypsin display faster enzyme kinetics. This phenomenon can easily be integrated with an LC separation (which already operates at elevated pressure) to enable an automatable ultrarapid on-line digestion LC-MS proteomics platform. Herein, we refer to this platform as the fast on-line digestion system (FOLDS) (23). Although FOLDS has been described before using trypsin, here the system is characterized with pepsin, and the results obtained are compared with results attainable with trypsin. Like trypsin, pepsin produced efficient protein digestion in just a few minutes when placed under pressure. Because of the natural maximal activity of pepsin at low pH, the FOLDS can be incorporated with a RePlay (Advion Biosciences, Ithaca, NY) system, and this powerful combination is what ultimately makes the integration of top-down and bottom-up proteomics analyses possible. The integrated analysis begins with a chromatographic separation of intact proteins. The separated proteins are then split into two streams. One stream proceeds directly to the mass spectrometer for MS and/or tandem MS analysis. The second stream is split into a long capillary where the chromatographic separation of the proteins is maintained, but their arrival to the mass spectrometer for detection is delayed. This is in essence the concept of RePlay (24, 25). Herein, we have taken the RePlay a step further by implementing our FOLDS technology into the second split delayed stream of proteins. While these delayed proteins travel down the long and narrow capillary, we exposed them to pepsin where, in combination with the pressure, the proteins are quickly and reproducibly digested. These peptide fragments are subsequently subjected to MS and/or tandem MS analysis. The FOLDS RePlay system allows the rapid and robust incorporation of the integrated top-down bottom-up proteomics work flow with the ability to not only identify proteins but also to sequence multisite/combinatorial PTMs because all detected peptides (from the FOLDS analysis) are confined to the original chromatographic peak of the protein they were derived from. The analysis of protein mixtures using this integrated strategy reduces the total amount of samples required to obtain both the top-down and bottom-up data, increases throughput, and improves protein sequence coverage.