Pattern analysis of stem cell differentiation during <Emphasis Type="Italic">in vitro Arabidopsis</Emphasis> organogenesis

Plant somatic cells have the capability to switch their cell fates from differentiated to undifferentiated status under proper culture conditions, which is designated as totipotency. As a result, plant cells can easily regenerate new tissues or organs from a wide variety of explants. However, the mechanism by which plant cells have such remarkable regeneration ability is still largely unknown. In this study, we used a set of meristem-specific marker genes to analyze the patterns of stem cell differentiation in the processes of somatic embryogenesis as well as shoot or root organogenesis in vitro. Our studies furnish preliminary and important information on the patterns of the de novo stem cell differentiation during various types of in vitro organogenesis.     

Enhancement of cell growth by intracellularly expressed herpes simplex virus thymidine kinase

A recombinant cell line (NIH3T3:pLtkSN) was made by infecting parental cells (NIH3T3) with a recombinant retrovirus (pLtkSN) encoding herpes simplex virus thymidine kinase (HSVtk) gene. The cells expressing HSVtk (NIH3T3:pLtkSN) grew 2.3 times more than the parental cells (NIH3T3) in Dulbecco's Modified Eagles Media containing 10% (v/v) horse serum. The NIH3T3:pLtkSN cells also showed a significant enhancement in the maximal cell concentration and the specific growth rate even at 2.5% serum concentration. The specific O2 uptake rate of NIH3T3 was 2.1 times greater than that of NIH3T3:pLtkSN. Under both O2-limited and O2-unlimited conditions, it appears that HSVtk plays an important role in enhancing the growth characteristics of animal cells.     

Rapid determination of substrate specificity of Clostridium histolyticum beta-collagenase using an immobilized peptide library.

The molecular basis of the substrate specificity of Clostridium histolyticum beta-collagenase was investigated using a combinatorial method. An immobilized positional peptide library, which contains 24,000 sequences, was constructed with a 7-hydroxycoumarin-4-propanoyl (Cop) fluorescent group attached at the N terminus of each sequence. This immobilized peptide library was incubated with C. histolyticum beta-collagenase, releasing fluorogenic fragments in the solution phase. The relative substrate specificity (k(cat)/K(m)) for each member of the library was determined by measuring fluorescence intensity in the solution phase. Edman sequencing was used to assign structure to subsites of active substrate mixtures. Collectively, the substrate preference for subsites (P(3)-P(4)') of C. histolyticum beta-collagenase was determined. The last position on the C-terminal side in which the identity of the amino acids affects the activity of the enzyme is P(4)', and an aromatic side chain is preferred in this position. The optimal P(1)'-P(3)' extended substrate sequence is P(1)'-Gly/Ala, P(2)'-Pro/Xaa, and P(3)'-Lys/Arg/Pro/Thr/Ser. The Cop group in either the P(2) or P(3) position is required for a high substrate activity with C. histolyticum beta-collagenase. S(2) and S(3) sites of the protease play a dominant role in fixing the substrate specificity. The immobilized peptide library proved to be a powerful approach for assessing the substrate specificity of C. histolyticum beta-collagenase, so it may be applied to the study of other proteases of interest.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

The 30-Base-Pair Deletion in Chinese Variants of the Epstein-Barr Virus LMP1 Gene Is Not the Major Effector of Functional Differences between Variant LMP1 Genes in Human Lymphocytes

One group of sequence variants of Epstein-Barr virus is characterized by a 10-amino-acid deletion within the CTAR-2 functional domain of the latent membrane protein, LMP1. A role for this deletion in enhancing the tumorigenicity of the viral oncogene in rodent fibroblasts was recently demonstrated. We examined the effect of this deletion upon LMP1 function in four human lymphoid cell lines by using three natural variants of LMP1: the prototype B95.8 gene and the CAO and AG876 genes, both of which have codons 343 to 352 of the B95.8-LMP1 deleted. These experiments revealed that LMP1-mediated upregulation of CD40 and CD54 was markedly impaired (by 60 to 90%) with CAO-LMP1 compared with B95.8-LMP1. In contrast, the function of AG876-LMP1 was indistinguishable from that of B95.8-LMP1 in two lines and was only slightly impaired in the other two lines. Activation of NF-κB by CAO-LMP1 was not impaired in any of the lines; rather, activation of an NF-κB reporter by CAO-LMP1 was consistently about twofold greater than the activation with B95.8- or AG876-LMP1. Therefore, while the CAO-LMP1 is functionally distinct from the prototype B95.8-LMP1 in human lymphocytes, the 10-amino-acid deletion appears not to be directly responsible. This conclusion was confirmed by using a B95.8-LMP1 mutant with codons 343 to 352 deleted and chimerae of CAO- and B95.8-LMP1 in which the CTAR-2 domains of these genes were exchanged. Sequences outside the CTAR-2 domain were implicated in the distinct functional characteristics of CAO-LMP1 in human lymphoid cells.     

Solution structure of the N‐terminal domain of DC‐UbP/UBTD2 and its interaction with ubiquitin

DC‐UbP/UBTD2 is a ubiquitin (Ub) domain‐containing protein first identified from dendritic cells, and is implicated in ubiquitination pathway. The solution structure and backbone dynamics of the C‐terminal Ub‐like (UbL) domain were elucidated in our previous work. To further understand the biological function of DC‐UbP, we then solved the solution structure of the N‐terminal domain of DC‐UbP (DC‐UbP_N) and studied its Ub binding properties by NMR techniques. The results show that DC‐UbP_N holds a novel structural fold and acts as a Ub‐binding domain (UBD) but with low affinity. This implies that the DC‐UbP protein, composing of a combination of both UbL and UBD domains, might play an important role in regulating protein ubiquitination and delivery of ubiquitinated substrates in eukaryotic cells.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Repeated pre-training sleep restriction in adolescent rats impaired spatial performance

Sleep and Biological Rhythms - Chronic sleep deprivation (SD) is an overwhelming problem in young students. Firstly, we investigated whether different levels of pre-training SD had effects on...