Identification of potential miRNA biomarkers for traumatic osteonecrosis of femoral head

Traumatic osteonecrosis of femoral head (TONFH) is a common orthopedic disease caused by physical injury in hip. However, the unclear pathogenesis mechanism of TONFH and lacking of simple noninvasive early diagnosis method cause the necessity of hip replacement for most patients with TONFH. In this study, we aimed to identify circulating microRNAs (miRNAs) by integrated bioinformatics analyses as potential biomarker of TONFH. mRNA expression profiles were downloaded from the Gene Expression Omnibus database. Then we combined two miRNA screen methods: Weighted gene co-expression network analysis and fold change based differentially expressed miRNAs analysis. As a result, we identified 14 key miRNAs as potential biomarkers for TONFH. Besides, 302 target genes of these miRNAs were obtained and the miRNA–mRNA interaction network was constructed. Furthermore, the results of Kyoto Encyclopedia of Gene and Genome pathway analysis, Gene Ontology function analysis, protein–protein interaction (PPI) network analysis and PPI network module analysis showed close correlation between these 14 key miRNAs and TONFH. Then we established receiver operating characteristic curves and identified 6-miRNA signature with highly diagnosis value including miR-93-5p (area under the curve [AUC] = 0.93), miR-1324 (AUC = 0.92), miR-4666a-3p (AUC = 0.92), miR-5011-3p (AUC = 0.92), and miR-320a (AUC = 0.89), miR-185-5p (AUC = 0.89). Finally, the results of quantitative real-time polymerase chain reaction confirmed the significantly higher expression of miR-93-5p and miR-320a in the serum of patients with ONFH. These circulating miRNAs could serve as candidate early diagnosis markers and potential treatment targets of TONFH.     

水热增加下黑土细菌群落共生网络特征

黑土是有机质含量高且肥沃的土壤类型之一,气候变化会显著改变黑土中微生物群落的结构,同时影响群落间的潜在相互作用关系。[目的] 揭示水热增加对黑土中的细菌群落结构及潜在互作关系的影响。[方法] 基于土壤移置试验,采用16S rRNA高通量测序解析农田黑土（原位黑土、水热增加1和水热增加2）中的细菌群落结构对水热增加的响应;使用CoNet构建微生物群落共生网络,识别共生网络中的枢纽微生物;利用结构方程模型、相关性分析探究水热条件变化下土壤性质、微生物交互作用、多样性之间的直接、间接关系。[结果] 黑土中的微生物以疣微菌、变形杆菌、酸性杆菌和放线菌为主。水热增加下土壤微生物共生网络的拓扑性质发生显著变化,网络中表征微生物潜在竞争关系的负连线随着水热增加而显著增加。气候因素通过改变微生物潜在相互作用影响了群落水平分类多样性。物种竞争增强可能直接导致了土壤有机碳含量的降低。[结论] 水热增加会显著改变黑土中微生物之间的潜在交互作用,枢纽微生物的响应更加敏感。     

The complex fluctuations of probabilistic Boolean networks

Probabilistic Boolean networks (PBNs) are extensions of Boolean networks (BNs), and both have been widely used to model biological systems. In this paper, we study the long-range correlations of PBNs based on their corresponding Markov chains. PBN states are quantified by the deviation of their steady-state distributions. The results demonstrate that, compared with BNs, PBNs can exhibit these dynamics over a wider and higher noise range. In addition, the constituent BNs significantly impact the generation of 1/f dynamics of PBNs, and PBNs with homogeneous steady-state distributions tend to sustain the 1/f dynamics over a wider noise range.     

Converting differential-equation models of biological systems to membrane computing

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand–receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular.     

Long-term temporal variation in the organization of an ant–plant network

Background and Aims

Functional groups of species interact and coevolve in space and time, forming complex networks of interacting species. A long-term study of temporal variation of an ant–plant network is presented with the aims of: (1) depicting its structural changes over a 20-year period; (2) detailing temporal variation in network topology, as revealed by nestedness and modularity analysis and other parameters (i.e. connectance, niche overlap); and (3) identifying long-term turnover in taxonomic structure (i.e. switches in ant resource use or plant visitor assemblages according to taxa).

Methods

Fieldwork was carried out at La Mancha, Mexico, and ant–plant interactions were observed between 1989 and 1991, between 1998 and 2000, and between May 2010 and 2011. Occurrences of ants on extrafloral nectaries (EFNs) were recorded. The resulting ant–plant networks were constructed from qualitative presence–absence data determined by a species–species matrix defined by the frequency of occurrence of each pairwise ant–plant interaction.

Key Results

Network variation across time was stable and a persistent nested structure may have contributed to the maintenance of resilient and species-rich communities. Modularity was lower than expected, especially in the most recent networks, indicating that the community exhibited high overlap among interacting species (e.g. few species were hubs in the more recent network, being partly responsible for the nested pattern). Structurally, the connections created among modules by super-generalists gave cohesion to subsets of species that otherwise would remain unconnected. This may have allowed an increasing cascade-effect of evolutionary events among modules. Mutualistic ant–plant interactions were structured 20 years ago mainly by the subdominant nectarivorous ant species Camponotus planatus and Crematogaster brevispinosa, which monopolized the best extrafloral nectar resources and out-competed other species with broader feeding habits. Through time, these ants, which are still present, lost their position as network hubs and diminished in their importance in structuring the network; simultaneously, plants gained in importance.

Conclusions

The long-term network analysis reveals a decrease in attended plant species richness, a notable increase in plant species participation from 1990 to 2010 (sustained by less plant taxonomic similarity in the older 1990 network), an increase in the number of ant species and a diminishing dominance of super-generalist ants. The structure of the community has remained highly nested and connected with low modularity, suggesting overall a more participative, homogeneous, cohesive interaction network. Although previous studies have suggested that interactions between ants and EFN-bearing plants are susceptible to seasonality, abiotic factors and perturbation, this cohesive structure appears to be the key for biodiversity and community maintenance.     

Recombinase-mediated cassette exchange (RMCE) — A rapidly-expanding toolbox for targeted genomic modifications

Starting in 1991, the advance of Tyr-recombinases Flp and Cre enabled superior strategies for the predictable insertion of transgenes into compatible target sites of mammalian cells. Early approaches suffered from the reversibility of integration routes and the fact that co-introduction of prokaryotic vector parts triggered uncontrolled heterochromatization. Shortcomings of this kind were overcome when Flp-Recombinase Mediated Cassette Exchange entered the field in 1994. RMCE enables enhanced tag-and-exchange strategies by precisely replacing a genomic target cassette by a compatible donor construct. After “gene swapping” the donor cassette is safely locked in, but can nevertheless be re-mobilized in case other compatible donor cassettes are provided (“serial RMCE”). These features considerably expand the options for systematic, stepwise genome modifications. The first decade was dominated by the systematic generation of cell lines for biotechnological purposes. Based on the reproducible expression capacity of the resulting strains, a comprehensive toolbox emerged to serve a multitude of purposes, which constitute the first part of this review. The concept per se did not, however, provide access to high-producer strains able to outcompete industrial multiple-copy cell lines. This fact gave rise to systematic improvements, among these certain accumulative site-specific integration pathways. The exceptional value of RMCE emerged after its entry into the stem cell field, where it started to contribute to the generation of induced pluripotent stem (iPS-) cells and their subsequent differentiation yielding a variety of cell types for diagnostic and therapeutic purposes. This topic firmly relies on the strategies developed in the first decade and can be seen as the major ambition of the present article. In this context an unanticipated, potent property of serial Flp-RMCE setups concerns the potential to re-open loci that have served to establish the iPS status before the site underwent the obligatory silencing process. Other relevant options relate to the introduction of composite Flp-recognition target sites (“heterospecific FRT-doublets”), into the LTRs of lentiviral vectors. These “twin sites” enhance the safety of iPS re-programming and -differentiation as they enable the subsequent quantitative excision of a transgene, leaving behind a single “FRT-twin”. Such a strategy combines the established expression potential of the common retro- and lentiviral systems with options to terminate the process at will. The remaining genomic tag serves to identify and characterize the insertion site with the goal to identify genomic “safe harbors” (GOIs) for re-use. This is enabled by the capacity of “FRT-twins” to accommodate any incoming RMCE-donor cassette with a compatible design.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.