Sample prep for proteomics of breast cancer: proteomics and gene ontology reveal dramatic differences in protein solubilization preferences of radioimmunoprecipitation assay and urea lysis buffers

Background

An important step in the proteomics of solid tumors, including breast cancer, consists of efficiently extracting most of proteins in the tumor specimen. For this purpose, Radio-Immunoprecipitation Assay (RIPA) buffer is widely employed. RIPA buffer's rapid and highly efficient cell lysis and good solubilization of a wide range of proteins is further augmented by its compatibility with protease and phosphatase inhibitors, ability to minimize non-specific protein binding leading to a lower background in immunoprecipitation, and its suitability for protein quantitation.

Results

In this work, the insoluble matter left after RIPA buffer extraction of proteins from breast tumors are subjected to another extraction step, using a urea-based buffer. It is shown that RIPA and urea lysis buffers fractionate breast tissue proteins primarily on the basis of molecular weights. The average molecular weight of proteins that dissolve exclusively in urea buffer is up to 60% higher than in RIPA. Gene Ontology (GO) and Directed Acyclic Graphs (DAG) are used to map the collective biological and biophysical attributes of the RIPA and urea proteomes. The Cellular Component and Molecular Function annotations reveal protein solubilization preferences of the buffers, especially the compartmentalization and functional distributions. It is shown that nearly all extracellular matrix proteins (ECM) in the breast tumors and matched normal tissues are found, nearly exclusively, in the urea fraction, while they are mostly insoluble in RIPA buffer. Additionally, it is demonstrated that cytoskeletal and extracellular region proteins are more soluble in urea than in RIPA, whereas for nuclear, cytoplasmic and mitochondrial proteins, RIPA buffer is preferred. Extracellular matrix proteins are highly implicated in cancer, including their proteinase-mediated degradation and remodelling, tumor development, progression, adhesion and metastasis. Thus, if they are not efficiently extracted by RIPA buffer, important information may be missed in cancer research.

Conclusion

For proteomics of solid tumors, a two-step extraction process is recommended. First, proteins in the tumor specimen should be extracted with RIPA buffer. Second, the RIPA-insoluble material should be extracted with the urea-based buffer employed in this work.     

A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models

An increased availability of genotypes at marker loci has prompted the development of models that include the effect of individual genes. Selection based on these models is known as marker-assisted selection (MAS). MAS is known to be efficient especially for traits that have low heritability and non-additive gene action. BLUP methodology under non-additive gene action is not feasible for large inbred or crossbred pedigrees. It is easy to incorporate non-additive gene action in a finite locus model. Under such a model, the unobservable genotypic values can be predicted using the conditional mean of the genotypic values given the data. To compute this conditional mean, conditional genotype probabilities must be computed. In this study these probabilities were computed using iterative peeling, and three Markov chain Monte Carlo (MCMC) methods – scalar Gibbs, blocking Gibbs, and a sampler that combines the Elston Stewart algorithm with iterative peeling (ESIP). The performance of these four methods was assessed using simulated data. For pedigrees with loops, iterative peeling fails to provide accurate genotype probability estimates for some pedigree members. Also, computing time is exponentially related to the number of loci in the model. For MCMC methods, a linear relationship can be maintained by sampling genotypes one locus at a time. Out of the three MCMC methods considered, ESIP, performed the best while scalar Gibbs performed the worst.     

Haplotype inference in crossbred populations without pedigree information

Background

Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.

Results

We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.

Conclusion

Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.     

You can't always get what you want: size assortative mating by mutual mate choice as a resolution of sexual conflict

Background  

Assortative mating patterns for mate quality traits like body size are often observed in nature. However, the underlying mechanisms that cause assortative mating patterns are less well known. Sexual selection is one important explanation for assortment, suggesting that i) one (usually the female) or both sexes could show preferences for mates of similar size or ii) mutual mate choice could resolve sexual conflict over quality traits into assortment. We tested these hypotheses experimentally in the socially monogamous cichlid fish Pelvicachromis taeniatus, in which mate choice is mutual.     

Production of G protein‐coupled receptors in an insect‐based cell‐free system

The biochemical analysis of human cell membrane proteins remains a challenging task due to the difficulties in producing sufficient quantities of functional protein. G protein‐coupled receptors (GPCRs) represent a main class of membrane proteins and drug targets, which are responsible for a huge number of signaling processes regulating various physiological functions in living cells. To circumvent the current bottlenecks in GPCR studies, we propose the synthesis of GPCRs in eukaryotic cell‐free systems based on extracts generated from insect (Sf21) cells. Insect cell lysates harbor the fully active translational and translocational machinery allowing posttranslational modifications, such as glycosylation and phosphorylation of de novo synthesized proteins. Here, we demonstrate the production of several GPCRs in a eukaryotic cell‐free system, performed within a short time and in a cost‐effective manner. We were able to synthesize a variety of GPCRs ranging from 40 to 133 kDa in an insect‐based cell‐free system. Moreover, we have chosen the μ opioid receptor (MOR) as a model protein to analyze the ligand binding affinities of cell‐free synthesized MOR in comparison to MOR expressed in a human cell line by “one‐point” radioligand binding experiments. Biotechnol. Bioeng. 2017;114: 2328–2338. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Genome-wide association and genomic prediction for host response to porcine reproductive and respiratory syndrome virus infection

Background

Host genetics has been shown to play a role in porcine reproductive and respiratory syndrome (PRRS), which is the most economically important disease in the swine industry. A region on Sus scrofa chromosome (SSC) 4 has been previously reported to have a strong association with serum viremia and weight gain in pigs experimentally infected with the PRRS virus (PRRSV). The objective here was to identify haplotypes associated with the favorable phenotype, investigate additional genomic regions associated with host response to PRRSV, and to determine the predictive ability of genomic estimated breeding values (GEBV) based on the SSC4 region and based on the rest of the genome. Phenotypic data and 60 K SNP genotypes from eight trials of ~200 pigs from different commercial crosses were used to address these objectives.

Results

Across the eight trials, heritability estimates were 0.44 and 0.29 for viral load (VL, area under the curve of log-transformed serum viremia from 0 to 21 days post infection) and weight gain to 42 days post infection (WG), respectively. Genomic regions associated with VL were identified on chromosomes 4, X, and 1. Genomic regions associated with WG were identified on chromosomes 4, 5, and 7. Apart from the SSC4 region, the regions associated with these two traits each explained less than 3% of the genetic variance. Due to the strong linkage disequilibrium in the SSC4 region, only 19 unique haplotypes were identified across all populations, of which four were associated with the favorable phenotype. Through cross-validation, accuracies of EBV based on the SSC4 region were high (0.55), while the rest of the genome had little predictive ability across populations (0.09).

Conclusions

Traits associated with response to PRRSV infection in growing pigs are largely controlled by genomic regions with relatively small effects, with the exception of SSC4. Accuracies of EBV based on the SSC4 region were high compared to the rest of the genome. These results show that selection for the SSC4 region could potentially reduce the effects of PRRS in growing pigs, ultimately reducing the economic impact of this disease.     

Impact of miR-21, miR-126 and miR-221 as Prognostic Factors of Clear Cell Renal Cell Carcinoma with Tumor Thrombus of the Inferior Vena Cava

Clear cell renal cell carcinoma (ccRCC) characterized by a tumor thrombus (TT) extending into the inferior vena cava (IVC) generally indicates poor prognosis. Nevertheless, the risk for tumor recurrence after nephrectomy and thrombectomy varies. An applicable and accurate prediction system to select ccRCC patients with TT of the IVC (ccRCC/TT) at high risk after nephrectomy is urgently needed, but has not been established up to now. To our knowledge, a possible role of microRNAs (miRs) for the development of ccRCC/TT or their impact as prognostic markers in ccRCC/TT has not been explored yet. Therefore, we analyzed the expression of the previously described onco-miRs miR-200c, miR-210, miR-126, miR-221, let-7b, miR-21, miR-143 and miR-141 in a study collective of 74 ccRCC patients. Using the expression profiles of these eight miRs we developed classification systems that accurately differentiate ccRCC from non-cancerous renal tissue and ccRCC/TT from tumors without TT. In the subgroup of 37 ccRCC/TT cases we found that miR-21, miR-126, and miR-221 predicted cancer related death (CRD) accurately and independently from other clinico-pathological features. Furthermore, a combined risk score based on the expression of miR-21, miR-126 and miR-221 was developed and showed high sensitivity and specificity to predict cancer specific survival (CSS) in ccRCC/TT. Using the combined risk score we were able to classify ccRCC/TT patients correctly into high and low risk cases. The risk stratification by the combined risk score (CRS) will benefit from further cohort validation and might have potential for clinical application as a molecular prediction system to identify high- risk ccRCC/TT patients.     

Neurotoxic,cytotoxic, apoptotic and antiproliferative effects of some marine algae extracts on the NA2B cell line

Oxidative stress contributes to cancer pathologies and to apoptosis. Marine algae exhibit cytotoxic, antiproliferative and apoptotic effects; their metabolites have been used to treat many types of cancer. We investigated in culture extracts of Petalonia fascia, Jania longifurca and Halimeda tuna to determine their effects on mouse neuroblastoma cell line, NA2B. NA2B cells were treated with algae extracts, and the survival and proliferation of NA2B cells were assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The effects of algae extracts on oxidative stress in NA2B cells also were investigated using nitric oxide synthase (NOS) immunocytochemistry and apoptosis was assessed using terminal deoxynucleotidyl transferase dUTP nick end labeling. We observed significant neurite inhibition with moderate damage by the neurotoxicity-screening test (NST) at IC₅₀ dilutions of the extracts. MTT demonstrated that J. longifurca extracts were more toxic than P. fascia and H. tuna extracts. We found an increase of endothelial and inducible NOS immunostaining for oxidative stress and TUNEL analysis revealed increased apoptosis after application of extract. Our findings suggest that the algae we tested may have potential use for treatment of cancer.     

Regulators of complement activity mediate inhibitory mechanisms through a common C3b‐binding mode

Regulators of complement activation (RCA) inhibit complement‐induced immune responses on healthy host tissues. We present crystal structures of human RCA (MCP, DAF, and CR1) and a smallpox virus homolog (SPICE) bound to complement component C3b. Our structural data reveal that up to four consecutive homologous CCP domains (i–iv), responsible for inhibition, bind in the same orientation and extended arrangement at a shared binding platform on C3b. Large sequence variations in CCP domains explain the diverse C3b‐binding patterns, with limited or no contribution of some individual domains, while all regulators show extensive contacts with C3b for the domains at the third site. A variation of ~100° rotation around the longitudinal axis is observed for domains binding at the fourth site on C3b, without affecting the overall binding mode. The data suggest a common evolutionary origin for both inhibitory mechanisms, called decay acceleration and cofactor activity, with variable C3b binding through domains at sites ii, iii, and iv, and provide a framework for understanding RCA disease‐related mutations and immune evasion.