Isolation of a novel multiple-heavy metal resistant Lampropedia aestuarii GYF-1 and investigation of its bioremediation potential.

BACKGROUND: Heavy metal contamination has been a severe worldwide environmental issue. For industrial pollutions, heavy metals rarely exist as singular entities. Hence, researches have increasingly focused on the detrimental effect of mixed heavy metal pollution. Genome analysis of Lampropedia strains predicted a repertoire of heavy metal resistance genes. However, we are still lack of experimental evidence regarding to heavy metal resistance of Lampropedia, and their potential in mixed heavy metal removal remain elusive. RESULTS: In this study, a Lampropedia aestuarii strain GYF-1 was isolated from soil samples near steel factory. Heavy metal tolerance assay indicated L. aestuarii GYF-1 possessed minimal inhibition values of 2 mM, 10 mM, 6 mM, 4 mM, 6 mM, 0.8 mM, and 4 mM for CdCl2, K2CrO4, CuCl2, NiCl2, Pb(CH3COO)2, ZnSO4, and FeCl2, respectively. The biosorption assay demonstrated its potential in soil remediation from mixed heavy metal pollution. Next the draft genome of L. aestuarii GYF-1 was obtained and annotated, which revealed strain GYF-1 are abundant in heavy metal resistance genes. Further evaluations on differential gene expressions suggested adaptive mechanisms including increased lipopolysaccharides level and enhanced biofilm formation. CONCLUSION: In this study, we demonstrated a newly isolated L. aestuarii GYF-1 exhibited mixed heavy metal resistance, which proven its capability of being a potential candidate strain for industrial biosorption application. Further genome analysis and differential gene expression assay suggest enhanced LPS and biofilm formation contributed to the adaptation of mixed heavy metals.

Degradome sequencing-based identification of phasiRNAs biogenesis pathways in Oryza sativa.

BACKGROUND: The microRNAs(miRNA)-derived secondary phased small interfering RNAs (phasiRNAs) participate in post-transcriptional gene silencing and play important roles in various bio-processes in plants. In rice, two miRNAs, miR2118 and miR2275, were mainly responsible for triggering of 21-nt and 24-nt phasiRNAs biogenesis, respectively. However, relative fewer phasiRNA biogenesis pathways have been discovered in rice compared to other plant species, which limits the comprehensive understanding of phasiRNA biogenesis and the miRNA-derived regulatory network. RESULTS: In this study, we performed a systematical searching for phasiRNA biogenesis pathways in rice. As a result, five novel 21-nt phasiRNA biogenesis pathways and five novel 24-nt phasiRNA biogenesis pathways were identified. Further investigation of their regulatory function revealed that eleven novel phasiRNAs in 21-nt length recognized forty-one target genes. Most of these genes were involved in the growth and development of rice. In addition, five novel 24-nt phasiRNAs targeted to the promoter of an OsCKI1 gene and thereafter resulted in higher level of methylation in panicle, which implied their regulatory function in transcription of OsCKI1,which acted as a regulator of rice development. CONCLUSIONS: These results substantially extended the information of phasiRNA biogenesis pathways and their regulatory function in rice.

sRNATargetDigger: A bioinformatics software for bidirectional identification of sRNA-target pairs with co-regulatory sRNAs information.

Identification of the target genes of microRNAs (miRNAs), trans-acting small interfering RNAs (ta-siRNAs), and small interfering RNAs (siRNAs) is an important step for understanding their regulatory roles in plants. In recent years, many bioinformatics software packages based on small RNA (sRNA) high-throughput sequencing (HTS) and degradome sequencing data analysis have provided strong technical support for large-scale mining of sRNA-target pairs. However, sRNA-target regulation is achieved using a complex network of interactions since one transcript might be co-regulated by multiple sRNAs and one sRNA may also affect multiple targets. Currently used mining software can realize the mining of multiple unknown targets using known sRNA, but it cannot rule out the possibility of co-regulation of the same target by other unknown sRNAs. Hence, the obtained regulatory network may be incomplete. We have developed a new mining software, sRNATargetDigger, that includes two function modules, "Forward Digger" and "Reverse Digger", which can identify regulatory sRNA-target pairs bidirectionally. Moreover, it has the ability to identify unknown sRNAs co-regulating the same target, in order to obtain a more authentic and reliable sRNA-target regulatory network. Upon re-examination of the published sRNA-target pairs in Arabidopsis thaliana, sRNATargetDigger found 170 novel co-regulatory sRNA-target pairs. This software can be downloaded from http://www.bioinfolab.cn/sRNATD.html.

Environmental stress perception activates structural remodeling of extant Streptococcus mutans biofilms.

Transcription regulators from the LexA-like Protein Superfamily control a highly diverse assortment of genetic pathways in response to environmental stress. All characterized members of this family modulate their functionality and stability via a strict coordination with the coprotease function of RecA. Using the LexA-like protein IrvR from Streptococcus mutans, we demonstrate an exception to the RecA paradigm and illustrate how this evolutionary innovation has been coopted to diversify the stress responsiveness of S. mutans biofilms. Using a combination of genetics and biophysical measurements, we demonstrate how non-SOS stresses and SOS stresses each trigger separate regulatory mechanisms that stimulate production of a surface lectin responsible for remodeling the viscoelastic properties of extant biofilms during episodes of environmental stress. These studies demonstrate how changes in the external environment or even anti-biofilm therapeutic agents can activate biofilm-specific adaptive mechanisms responsible for bolstering the integrity of established biofilm communities. Such changes in biofilm community structure are likely to play central roles in the notorious recalcitrance of biofilm infections.

Identification of novel phasiRNAs loci on long non-coding RNAs in Arabidopsis thaliana.

Long non-coding RNAs (lncRNAs) are the "dark matters"involved in gene regulation with complex mechanisms. However, the functions of most lncRNAs remain to be determined. Our previous work revealed a massive number of degradome-supported cleavage signatures on Arabidopsis lncRNAs. Some of them have been confirmed associated with miRNAs-like sRNAs production, while others without long stem structure remain unexplored. A systematical search for phasiRNAs generating ability of these lncRNAs was conducted. Eight novel small RNA triggered lncRNA-phasiRNA pathways were discovered and three of them were found to be conserved in Arabidopsis, Oryza sativa, Glycine max and Gossypium hirsutum. Besides, Five novel ta-siRNAs derived from these lncRNAs were further identified to be involved in the regulation of plant development, stress responses and aromatic amino acids synthesis. These results substantially expanded the gene regulation mechanisms of lncRNAs.

Genome-wide identification and characterization of novel microRNAs in seed development of soybean.

MicroRNAs (miRNAs) are important and ubiquitous regulators of gene expression in eukaryotes. However, the information about miRNAs population and their regulatory functions involving in soybean seed development remains incomplete. Base on the Dicer-like1-mediated cleavage signals during miRNA processing could be employed for novel miRNA discovery, a genome-wide search for miRNA candidates involved in seed development was carried out. As a result, 17 novel miRNAs, 14 isoforms of miRNA (isomiRs) and 31 previously validated miRNAs were discovered. These novel miRNAs and isomiRs represented tissue-specific expression and the isomiRs showed significantly higher abundance than that of their miRNA counterparts in different tissues. After target prediction and degradome sequencing data-based validation, 13 novel miRNA-target pairs were further identified. Besides, five targets of 22-nt iso-gma-miR393h were found to be triggered to produce secondary trans-acting siRNA (ta-siRNAs). Summarily, our results could expand the repertoire of miRNAs with potentially important functions in soybean.

Sumoylation stabilizes RACK1B and enhance its interaction with RAP2.6 in the abscisic acid response.

The highly conserved eukaryotic WD40 repeat protein, Receptor for Activated C Kinase 1 (RACK1), is involved in the abscisic acid (ABA) response in Arabidopsis. However, the regulation of RACK1 and the proteins with which it interacts are poorly understood. Here, we show that RACK1B is sumoylated at four residues, Lys50, Lys276, Lys281 and Lys291. Sumoylation increases RACK1B stability and its tolerance to ubiquitination-mediated degradation in ABA response. As a result, sumoylation leads to enhanced interaction between RACK1B and RAP2.6, an AP2/ERF family transcription factor. RACK1B binds directly to the AP2 domain of RAP2.6, which alters the affinity of RAP2.6 for CE1 and GCC cis-acting regulatory elements. Taken together, our findings illustrate that protein stability controlled by dynamic post-transcriptional modification is a critical regulatory mechanism for RACK1B, which functions as scaffold protein for RAP2.6 in ABA signaling.

Head Tracking Latency in Virtual Environments Revisited: Do Users with Multiple Sclerosis Notice Latency Less?

Latency (i.e., time delay) in a virtual environment is known to disrupt user performance, presence and induce simulator sickness. Thus, with emerging use of virtual rehabilitation, the target populations' latency perception thresholds need to be considered to fully understand and possibly control the implications of latency in a Virtual Rehabilitation environment. We present a study that quantifies the latency discrimination thresholds of a yet untested population-a specific subset of mobility impaired participants where participants suffer from Multiple Sclerosis-and compare the results to a control group of healthy participants. The study was modeled after previous latency discrimination research and shows significant differences in latency perception between the two populations with MS participants showing lower sensitivity to latency than healthy participants.

Robust spots finding in microarray images with distortions.

Microarray images, which allow the analysis of hybridization expressions of genes, have been one of the most widely used high-throughput technologies with many different applications. Accurate and automatic microarray image analysis is very important since researchers trust the information provided in these experiments and construct conclusions based on the results produced by the software responsible in analyzing the hybridized arrays. Every microarray image contains thousands of spots, so how to do the spots finding in microarray images accurately and automatically is very meaningful. There are always some problems, such as rotation and distortion, in a microarray image caused by mechanical errors and/or optical errors in the system. All these problems will hinder "doi"ng analysis automatically. Early research has worked out several algorithms to deal with the rotation problem, but those algorithms can not handle microarray images with distortions. In this paper, we propose a robust spots finding method to deal with both rotation and/or distortion in microarray images. The proposed method provides automatic gridding and can handle a microarray image with different type of rotation (global or sub-array rotation) and optical distortions.