定向进化人α型干扰素基因家族的研究

应用DNA改组(DNAshuffling)技术重组了12种人α型干扰素基因,并结合噬菌体表面呈现(phagedisplay)技术构建了噬菌体干扰素改组文库,采用简便的、功能性的定向竞争筛选方法,获得了比活达1 0×109IU/mg的新型α型基因工程复合干扰素,是目前国际上已投产的α2型干扰素的5倍,具有生产应用前景,上述策略也为其它细胞因子或酶的改造提供了借鉴方法。     

Identification of sequence motifs at the breakpoint junctions in three t(1;9)(p36.3;q34) and delineation of mechanisms involved in generating balanced translocations

Although approximately 1 in 500 individuals carries a reciprocal translocation, little is known about the mechanisms that result in their formation. We analyzed the sequences surrounding the breakpoints in three unbalanced translocations of 1p and 9q, all of which were designated t(1;9)(p36.3;q34), to investigate the presence of sequence motifs that might mediate nonhomologous end joining (NHEJ). The breakpoint regions were unique in all individuals. Two of three translocations demonstrated insertions and duplications at the junctions, suggesting NHEJ in the formation of the rearrangements. No homology was identified in the breakpoint regions, further supporting NHEJ. We found translin motifs at the breakpoint junctions, suggesting the involvement of translin in the joining of the broken chromosome ends. We propose a model for balanced translocation formation in humans similar to transposition in bacteria, in which staggered nicks are repaired resulting in duplications and insertions at the translocation breakpoints.     

The basic science of vascular biology: implications for the practicing surgeon

A thorough understanding of vascular biology will assist the reconstructive surgeon in both operative planning and development of novel surgical approaches to treat chronic wounds and tissue loss, and to optimize regenerative strategies for tissue reconstruction. In this review, several fundamental concepts of the basic science of vascular biology are discussed, with specific emphasis on the clinical implications most relevant to the reconstructive surgeon. Topics include the vascular physiology of tissue flaps and grafts, the principles of neovascularization including angiogenesis and vasculogenesis, and the basic concepts of bioengineering of vascularized tissue constructs for use in reconstruction. As basic science research increases our collective understanding of vascular physiology--specifically, in the areas of neovascularization and tissue engineering--reconstructive surgeons will be able to improve treatment of the sequelae of ischemic injuries, tissue loss, and chronic wounds.     

Insulin resistance and decreased spexin in Indian Patients with Type 2 Diabetes Mellitus

Spexin is novel biomarker, which plays a potential role in glucose and lipid metabolisms. However, there was paucity of serum spexin levels in obesity and diabetes mellitus subjects. Hence the current study was aimed to find the relationship between the serum spexin levels in type 2 Diabetes mellitus (type 2 DM) with extrapolation of cardiovascular disease (CVD) risk. A cross-sectional study included 330 participants, subdivided as control (n=110), type 2 DM (n=110) and type 2 DM with CVD groups (n=110). HbA1c, insulin, lipid profile, spexin & leptin including blood pressure and body mass index were analyzed from all the participants. The serum spexin levels (ng/ml) were significantly decreased in type 2 DM (mean ± sd: 0.65 ± 0.03) and type 2 DM with CVD (0.48 ± 0.02) groups compared to the control (0.79 ± 0.03) group (p<0.001). The decreased spexin levels were observed in type 2 DM, and further more decreased in type 2 DM with CVD patients compared to controls indicating that spexin levels could be served as an early prediction of obesity-induced T2DM with CVD risk.     

Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population

Background

A haplotype approach to genomic prediction using high density data in dairy cattle as an alternative to single-marker methods is presented. With the assumption that haplotypes are in stronger linkage disequilibrium (LD) with quantitative trait loci (QTL) than single markers, this study focuses on the use of haplotype blocks (haploblocks) as explanatory variables for genomic prediction. Haploblocks were built based on the LD between markers, which allowed variable reduction. The haploblocks were then used to predict three economically important traits (milk protein, fertility and mastitis) in the Nordic Holstein population.

Results

The haploblock approach improved prediction accuracy compared with the commonly used individual single nucleotide polymorphism (SNP) approach. Furthermore, using an average LD threshold to define the haploblocks (LD≥0.45 between any two markers) increased the prediction accuracies for all three traits, although the improvement was most significant for milk protein (up to 3.1 % improvement in prediction accuracy, compared with the individual SNP approach). Hotelling’s t-tests were performed, confirming the improvement in prediction accuracy for milk protein. Because the phenotypic values were in the form of de-regressed proofs, the improved accuracy for milk protein may be due to higher reliability of the data for this trait compared with the reliability of the mastitis and fertility data. Comparisons between best linear unbiased prediction (BLUP) and Bayesian mixture models also indicated that the Bayesian model produced the most accurate predictions in every scenario for the milk protein trait, and in some scenarios for fertility.

Conclusions

The haploblock approach to genomic prediction is a promising method for genomic selection in animal breeding. Building haploblocks based on LD reduced the number of variables without the loss of information. This method may play an important role in the future genomic prediction involving while genome sequences.     

Selection of haplotype variables from a high-density marker map for genomic prediction

Background

Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs.

Results

The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability).

Conclusions

Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks or all individual SNPs, with the benefit of having a much lower computational demand.     

Combinatorial Optimization of Cystine-Knot Peptides towards High-Affinity Inhibitors of Human Matriptase-1

Cystine-knot miniproteins define a class of bioactive molecules with several thousand natural members. Their eponymous motif comprises a rigid structured core formed by six disulfide-connected cysteine residues, which accounts for its exceptional stability towards thermic or proteolytic degradation. Since they display a remarkable sequence tolerance within their disulfide-connected loops, these molecules are considered promising frameworks for peptide-based pharmaceuticals. Natural open-chain cystine-knot trypsin inhibitors of the MCoTI (Momordica cochinchinensis trypsin inhibitor) and SOTI (Spinacia oleracea trypsin inhibitor) families served as starting points for the generation of inhibitors of matriptase-1, a type II transmembrane serine protease with possible clinical relevance in cancer and arthritic therapy. Yeast surface-displayed libraries of miniproteins were used to select unique and potent matriptase-1 inhibitors. To this end, a knowledge-based library design was applied that makes use of detailed information on binding and folding behavior of cystine-knot peptides. Five inhibitor variants, four of the MCoTI family and one of the SOTI family, were identified, chemically synthesized and oxidatively folded towards the bioactive conformation. Enzyme assays revealed inhibition constants in the low nanomolar range for all candidates. One subnanomolar binder (K_i = 0.83 nM) with an inverted selectivity towards trypsin and matriptase-1 was identified.     

Mechanical force prolongs acute inflammation via T-cell-dependent pathways during scar formation

Mechanical force significantly modulates both inflammation and fibrosis, yet the fundamental mechanisms that regulate these interactions remain poorly understood. Here we performed microarray analysis to compare gene expression in mechanically loaded wounds vs. unloaded control wounds in an established murine hypertrophic scar (HTS) model. We identified 853 mechanically regulated genes (false discovery rate <2) at d 14 postinjury, a subset of which were enriched for T-cell-regulated pathways. To substantiate the role of T cells in scar mechanotransduction, we applied the HTS model to T-cell-deficient mice and wild-type mice. We found that scar formation in T-cell-deficient mice was reduced by almost 9-fold (P < 0.001) with attenuated epidermal (by 2.6-fold, P < 0.01) and dermal (3.9-fold, P < 0.05) proliferation. Mechanical stimulation was highly associated with sustained T-cell-dependent Th2 cytokine (IL-4 and IL-13) and chemokine (MCP-1) signaling. Further, T-cell-deficient mice failed to recruit systemic inflammatory cells such as macrophages or monocytic fibroblast precursors in response to mechanical loading. These findings indicate that T-cell-regulated fibrogenic pathways are highly mechanoresponsive and suggest that mechanical forces induce a chronic-like inflammatory state through immune-dependent activation of both local and systemic cell populations.     

The role of stem cells in cutaneous wound healing: what do we really know?

Wound repair is a complex process involving the orchestrated interaction of multiple growth factors, cytokines, chemokines, and cell types. Dysregulation of this process leads to problems such as excessive healing in the form of keloids and hypertrophic scars and chronic, nonhealing wounds. These issues have broad global implications. Stem cells offer enormous potential for enhancing tissue repair and regeneration following injury. The rapidly developing fields of stem cell biology and skin tissue engineering create translational opportunities for the development of novel stem cell-based wound-healing therapies.