The mRNA levels of TGF-ß Type II receptor splice variants in monocytes are associated with disease activity in patients with rheumatoid arthritis.

OBJECTIVES: In rheumatoid arthritis (RA) patients, TGF-ß exerts a singular effect on lymphocytes, macrophages, and polymorphonuclear leukocytes. Moreover, evidences indicate that TGF-ß1 stimulation affects the expression levels of TGF-ß receptors. Therefore, we analysed in different leukocyte subpopulations, whether the mRNA abundance of TGFBR2 splice variants might be related to RA. METHODS: We isolated different leukocyte subpopulations from peripheral blood from 9 healthy control volunteers and 9 RA patients, matched by gender and age (cohort 1), and 8 additional RA patients (cohort 2). Then we quantified, by RT-qPCR, the mRNA relative abundance of TGFBR2 splice variants (namely TGFBR2A and TGFBR2B) in PMNs, and PBMCs (monocytes and non-monocytes). We first checked whether the TGFBR2-splice variant mRNA profile could be associated with any particular blood cell type both, in healthy control volunteers and in RA patients. In addition, PBMC and PMN mRNA levels were correlated, using Spearman's rank-order correlation test, with clinical and biochemical determinations of RA patients. RESULTS: We have shown that TGFBR2 exhibits an alternative splicing pattern in different subpopulations of human leucocytes from healthy controls, and the lack of it in the same cell type from RA samples. Furthermore, our study yields initial evidence that TGFBR2 mRNA expression levels in monocytes might mirror RA disease activity. CONCLUSIONS: mRNA abundance of TGFBR2 splice variants in monocytes shows changes linked to RA disease activity.

Bicodon bias can determine the role of synonymous SNPs in human diseases.

BACKGROUND: For a long time synonymous single nucleotide polymorphisms were considered as silent mutations. However, nowadays it is well known that they can affect protein conformation and function, leading to altered disease susceptibilities, differential prognosis and/or drug responses, among other clinically relevant genetic traits. This occurs through different mechanisms: by disrupting the splicing signals of precursor mRNAs, affecting regulatory binding-sites of transcription factors and miRNAs, or by modifying the secondary structure of mRNAs. RESULTS: In this paper we considered 22 human genetic diseases or traits, linked to 35 synonymous single nucleotide polymorphisms in 27 different genes. We performed a local sequence context analysis in terms of the ribosomal pause propensity affected by synonymous single nucleotide polymorphisms. We found that synonymous mutations related to the above mentioned mechanisms presented small pause propensity changes, whereas synonymous mutations that were not related to those mechanisms presented large pause propensity changes. On the other hand, we did not observe large variations in the codon usage of codons associated with these mutations. Furthermore, we showed that the changes in the pause propensity associated with benign sSNPs are significantly lower than the pause propensity changes related to sSNPs associated to diseases. CONCLUSIONS: These results suggest that the genetic diseases or traits related to synonymous mutations with large pause propensity changes, could be the consequence of another mechanism underlying non-silent synonymous mutations. Namely, alternative protein configuration related, in turn, to alterations in the ribosome-mediated translational attenuation program encoded by pairs of consecutive codons, not codons. These findings shed light on the latter mechanism based on the perturbation of the co-translational folding process.

A Novel Splice Variant of Human TGF-ß Type II Receptor Encodes a Soluble Protein and Its Fc-Tagged Version Prevents Liver Fibrosis in vivo.

We describe, for the first time, a new splice variant of the human TGF-ß type II receptor (TßRII). The new transcript lacks 149 nucleotides, resulting in a frameshift and the emergence of an early stop codon, rendering a truncated mature protein of 57 amino acids. The predicted protein, lacking the transmembrane domain and with a distinctive 13-amino-acid stretch at its C-terminus, was named TßRII-Soluble Endogenous (TßRII-SE). Binding predictions indicate that the novel 13-amino-acid stretch interacts with all three TGF-ß cognate ligands and generates a more extensive protein-protein interface than TßRII. TßRII-SE and human IgG1 Fc domain were fused in frame in a lentiviral vector (Lv) for further characterization. With this vector, we transduced 293T cells and purified TßRII-SE/Fc by A/G protein chromatography from conditioned medium. Immunoblotting revealed homogeneous bands of approximately 37 kDa (reduced) and 75 kDa (non-reduced), indicating that TßRII-SE/Fc is secreted as a disulfide-linked homodimer. Moreover, high-affinity binding of TßRII-SE to the three TGF-ß isoforms was confirmed by surface plasmon resonance (SPR) analysis. Also, intrahepatic delivery of Lv.TßRII-SE/Fc in a carbon tetrachloride-induced liver fibrosis model revealed amelioration of liver injury and fibrosis. Our results indicate that TßRII-SE is a novel member of the TGF-ß signaling pathway with distinctive characteristics. This novel protein offers an alternative for the prevention and treatment of pathologies caused by the overproduction of TGF-ß ligands.

Prediction of cell position using single-cell transcriptomic data: an iterative procedure.

Single-cell sequencing reveals cellular heterogeneity but not cell localization. However, by combining single-cell transcriptomic data with a reference atlas of a small set of genes, it would be possible to predict the position of individual cells and reconstruct the spatial expression profile of thousands of genes reported in the single-cell study. With the purpose of developing new algorithms, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). Within this context, we describe here our proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes.

Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi.

Due to recent advances in reprogramming cell phenotypes, many efforts have been dedicated to developing reverse engineering procedures for the identification of gene regulatory networks that emulate dynamical properties associated with the cell fates of a given biological system. In this work, we propose a systems biology approach for the reconstruction of the gene regulatory network underlying the dynamics of the Trypanosoma cruzi's life cycle. By means of an optimisation procedure, we embedded the steady state maintenance, and the known phenotypic transitions between these steady states in response to environmental cues, into the dynamics of a gene network model. In the resulting network architecture we identified a small subnetwork, formed by seven interconnected nodes, that controls the parasite's life cycle. The present approach could be useful for better understanding other single cell organisms with multiple developmental stages.