Activation of Transposable Elements in Immune Cells of Fibromyalgia Patients.

Advancements in nucleic acid sequencing technology combined with an unprecedented availability of metadata have revealed that 45% of the human genome constituted by transposable elements (TEs) is not only transcriptionally active but also physiologically necessary. Dysregulation of TEs, including human retroviral endogenous sequences (HERVs) has been shown to associate with several neurologic and autoimmune diseases, including Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). However, no study has yet addressed whether abnormal expression of these sequences correlates with fibromyalgia (FM), a disease frequently comorbid with ME/CFS. The work presented here shows, for the first time, that, in fact, HERVs of the H, K and W types are overexpressed in immune cells of FM patients with or without comorbid ME/CFS. Patients with increased HERV expression (N = 14) presented increased levels of interferon (INF-ß and INF-γ) but unchanged levels of TNF-α. The findings reported in this study could explain the flu-like symptoms FM patients present with in clinical practice, in the absence of concomitant infections. Future work aimed at identifying specific genomic loci differentially affected in FM and/or ME/CFS is warranted.

ARCIMBOLDO_LITE: single-workstation implementation and use.

ARCIMBOLDO solves the phase problem at resolutions of around 2 Šor better through massive combination of small fragments and density modification. For complex structures, this imposes a need for a powerful grid where calculations can be distributed, but for structures with up to 200 amino acids in the asymmetric unit a single workstation may suffice. The use and performance of the single-workstation implementation, ARCIMBOLDO_LITE, on a pool of test structures with 40-120 amino acids and resolutions between 0.54 and 2.2 Šis described. Inbuilt polyalanine helices and iron cofactors are used as search fragments. ARCIMBOLDO_BORGES can also run on a single workstation to solve structures in this test set using precomputed libraries of local folds. The results of this study have been incorporated into an automated, resolution- and hardware-dependent parameterization. ARCIMBOLDO has been thoroughly rewritten and three binaries are now available: ARCIMBOLDO_LITE, ARCIMBOLDO_SHREDDER and ARCIMBOLDO_BORGES. The programs and libraries can be downloaded from http://chango.ibmb.csic.es/ARCIMBOLDO_LITE.

Combining phase information in reciprocal space for molecular replacement with partial models.

ARCIMBOLDO allows ab initio phasing of macromolecular structures below atomic resolution by exploiting the location of small model fragments combined with density modification in a multisolution frame. The model fragments can be either secondary-structure elements predicted from the sequence or tertiary-structure fragments. The latter can be derived from libraries of typical local folds or from related structures, such as a low-homology model that is unsuccessful in molecular replacement. In all ARCIMBOLDO applications, fragments are searched for sequentially. Correct partial solutions obtained after each fragment-search stage but lacking the necessary phasing power can, if combined, succeed. Here, an analysis is presented of the clustering of partial solutions in reciprocal space and of its application to a set of different cases. In practice, the task of combining model fragments from an ARCIMBOLDO run requires their referral to a common origin and is complicated by the presence of correct and incorrect solutions as well as by their not being independent. The F-weighted mean phase difference has been used as a figure of merit. Clustering perfect, non-overlapping fragments dismembered from test structures in polar and nonpolar space groups shows that density modification before determining the relative origin shift enhances its discrimination. In the case of nonpolar space groups, clustering of ARCIMBOLDO solutions from secondary-structure models is feasible. The use of partially overlapping search fragments provides a more favourable circumstance and was assessed on a test case. Applying the devised strategy, a previously unknown structure was solved from clustered correct partial solutions.

tRNAGlyGCC-Derived Internal Fragment (i-tRF-GlyGCC) in Ovarian Cancer Treatment Outcome and Progression.

Epithelial ovarian cancer (EOC) remains a highly-lethal gynecological malignancy, characterized by frequent recurrence, chemotherapy resistance and poor 5-year survival. Identifying novel predictive molecular markers remains an overdue challenge in the disease's clinical management. Herein, in silico analysis of TCGA-OV highlighted the tRNA-derived internal fragment (i-tRF-GlyGCC) among the most abundant tRFs in ovarian tumors, while target prediction and gene ontology (GO) enrichment analysis predicted its implication in key biological processes. Thereafter, i-tRF-GlyGCC levels were quantified in a screening EOC (n = 98) and an institutionally-independent serous ovarian cancer (SOC) validation cohort (n = 100, OVCAD multicenter study). Disease progression and patient death were used as clinical endpoints for the survival analysis. Internal validation was performed by bootstrap analysis and the clinical net benefit was estimated by decision curve analysis. The analysis highlighted the significant association of i-tRF-GlyGCC with advanced FIGO stages, suboptimal debulking and most importantly, with early progression and poor overall survival of EOC patients. The OVCAD validation cohort corroborated the unfavorable predictive value of i-tRF-GlyGCC in EOC. Ultimately, evaluation of i-tRF-GlyGCC with the established/clinically used prognostic markers offered superior patient risk-stratification and enhanced clinical benefit in EOC prognosis. In conclusion, i-tRF-GlyGCC assessment could aid towards personalized prognosis and support precision medicine decisions in EOC.

Exploiting distant homologues for phasing through the generation of compact fragments, local fold refinement and partial solution combination.

Macromolecular structures can be solved by molecular replacement provided that suitable search models are available. Models from distant homologues may deviate too much from the target structure to succeed, notwithstanding an overall similar fold or even their featuring areas of very close geometry. Successful methods to make the most of such templates usually rely on the degree of conservation to select and improve search models. ARCIMBOLDO_SHREDDER uses fragments derived from distant homologues in a brute-force approach driven by the experimental data, instead of by sequence similarity. The new algorithms implemented in ARCIMBOLDO_SHREDDER are described in detail, illustrating its characteristic aspects in the solution of new and test structures. In an advance from the previously published algorithm, which was based on omitting or extracting contiguous polypeptide spans, model generation now uses three-dimensional volumes respecting structural units. The optimal fragment size is estimated from the expected log-likelihood gain (LLG) values computed assuming that a substructure can be found with a level of accuracy near that required for successful extension of the structure, typically below 0.6 Šroot-mean-square deviation (r.m.s.d.) from the target. Better sampling is attempted through model trimming or decomposition into rigid groups and optimization through Phaser's gyre refinement. Also, after model translation, packing filtering and refinement, models are either disassembled into predetermined rigid groups and refined (gimble refinement) or Phaser's LLG-guided pruning is used to trim the model of residues that are not contributing signal to the LLG at the target r.m.s.d. value. Phase combination among consistent partial solutions is performed in reciprocal space with ALIXE. Finally, density modification and main-chain autotracing in SHELXE serve to expand to the full structure and identify successful solutions. The performance on test data and the solution of new structures are described.

The context of the size and distance of Atlantic Forest fragments in a small city in Southern Brazil

The Atlantic Forest is highly anthropized, this reduce the areas of native vegetation and impacts the biodiversity of the biome. The objective of this study is to analyze forest remnants with native vegetation characteristics using a free GIS. This analysis takes place using landscape metrics and was based on the supervised vectorization of land use in the municipality of California, PR. The area of the vectored polygons was obtained and a classified, and then the calculation was made with the nearest neighbor index, mean distance observed, Patton diversity index and the perimeter/area ratio of forest fragments. The results show that most of the fragments have an area smaller than 1 ha, the fragments with more significant area (<50 ha) represent more than 16% of the native vegetation area. The small fragments are important to maintain the connectivity, since the withdrawal of these increases the mean distance observed and nearest neighbor index. Most of the fragments are elongated and amorphous in accordance with the perimeter/area ratio and the Patton diversity index respectively, this may demonstrate the fragments may be subject to edge effects. Even with these characteristics, these fragments may be part of what is planned in public policy for preservation in the Atlantic Forest in the state of Paraná. Therefore, even small fragments with little core area are important for maintaining biodiversity, especially in a highly anthropogenic landscape.