Therapeutic Effect of Darkling Beetle (Zophobas morio) Hemolymph on Skin Thermal Injury in Mice Infected by Staphylococcus haemolyticus.

Staphylococci are the most common pathogens isolated from skin infections in livestock or companion animals. Antibiotic therapy is the best treatment for infections, but local or systemic use of antimicrobials increases the risk of bacterial resistance. Insects are rich in antimicrobial peptides, which can reduce bacterial resistance and can be used to treat bacterial infections after skin burns. We propose that the use of the darkling beetle (Z. morio) hemolymph to treat skin infections in mice by Staphylococcus haemolyticus is one of the alternatives. Z. morio hemolymph alleviated the increase in wound area temperature in mice with a skin infection, reduced the bacterial load of the wound, and accelerated the wound healing speed significantly. Pathological sections showed that Z. morio hemolymph can significantly reduce inflammatory cell infiltration, and promote skin tissue repair. Real-time fluorescent quantitative polymerase chain reaction (PCR) revealed that the Z. morio hemolymph can significantly reduce the levels of pro-inflammatory cytokines, including interleukin-1 beta (IL-1ß), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and chemokine interleukin-8 (IL-8). Our findings suggest that Z. morio antibacterial hemolymph can promote wound contraction, relieve local inflammatory responses and promote wound healing in mice infected with a heat injury, which has a positive therapeutic effect and enormous potential for skin thermal injury.

Immunization with recombinant Erns-LTB fusion protein elicits protective immune responses against bovine viral diarrhea virus.

Bovine viral diarrhea virus (BVDV), a major infectious pathogen and is associated with major economic losses and significant impact on animal welfare worldwide. Here, recombinant Erns-LTB protein vaccine containing MF59 adjuvant was prepared and assessed using a mouse model. The recombinant plasmid (pET32a-Erns-LTB) was constructed and transformed into BL21 (DE3) cells to produce Erns-LTB protein. The Erns-LTB protein was formulated with MF59 adjuvant, when delivered intraperitoneally in mice, exhibited higher immunogenic and induced superior levels of anti-BVDV IgG compared with the MF59 adjuvanted Erns protein. Importantly, after challenged with different BVDV BJ175170 and BJ1305 isolate strains, mice inoculated with Erns-LTB protein displayed alleviated pathological damage and decreased plasma virus shedding compared with mice inoculated with Erns protein. The enhanced protection from Erns-LTB protein is mediated by T cell immunity and primarily based on CD4+ T helper (Th) and CD8+ cytotoxic T lymphocyte (CTL), these results suggest that Erns-LTB protein has potential to protect against a broad range of BVDV strains thereby providing a novel direction for developing broadly protective vaccines.

[Comprehensive re-annotation of protein-coding genes for prokaryotic genomes by Z-curve and similarity-based methods].

The development of sequencing technology has generated huge genomic sequencing information and largely enriched public genetic resources. To analyze such big data, the algorithms and tools for comparison and annotation of genomes are updated continually, enabling genome annotation with higher accuracy via various annotation tools. Many prokaryotic genomes in public database were sequenced and assembled more than a decade ago, and they contained multiple genes with unknown functions. To improve the current annotation for those genomes in NCBI, we re-annotate 1587 bacterial and archaeal genomes using multiple prokaryotic gene recognition algorithms/softwares and gene expression data. The 33 Z-curve variables were applied to recognize sequences that were over-annotated to genes of 1587 bacterial and archaeal genomes deposited in public databases, and a total of 3092 sequences belonging to 177 genomes were recognized as sequences over-annotated as protein-coding genes. Next, 4447 protein-coding genes with unknown functions from 939 genomes were annotated with definite functions by similarity search. Finally, we recognized 2003 missed protein-coding genes that belong to known COG (clusters of orthologous groups of proteins) of nine genomes using three methods (ZCURVE 3.0, Glimmer 3.02 and Prodigal), which are accurate and frequently used for gene finding. Their algorithms are different and complementary. This is a comprehensive study for re-annotation of bacterial and archaeal genomes with new tools combining multi-omics data, which should provide a reference for annotation of newly sequenced strains, and also benefit further fundamental researches with the bacterial gene sequences obtained after re-annotation.

CasLocusAnno: a web-based server for annotating cas loci and their corresponding (sub)types.

In prokaryotes, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated protein (Cas) systems constitute adaptive immune systems against mobile genetic elements (MGEs). Here, we introduce the Markov cluster algorithm (MCL) to Makarova et al.'s method in order to select a more reasonable profile. Additionally, our new Maximum Continuous Cas Subcluster (MCCS) method helps identification of tightly clustered loci. The comparison with two other commonly used programs shows that the method could identify Cas proteins with higher accuracy and lower Additional Prediction Rate (APR). Moreover, we developed a web-based server, CasLocusAnno (http://cefg.uestc.cn/CasLocusAnno), capable of annotating Cas proteins, cas loci and their (sub)types less than ~ 28 s following the whole proteome sequence submission. Its standalone version can be downloaded at https://github.com/RiversDong/CasLocusAnno.

Vgas: A Viral Genome Annotation System.

The in-depth study of viral genomes is of great help in many aspects, especially in the treatment of human diseases caused by viral infections. With the rapid accumulation of viral sequencing data, improved, or alternative gene-finding systems have become necessary to process and mine these data. In this article, we present Vgas, a system combining an ab initio method and a similarity-based method to automatically find viral genes and perform gene function annotation. Vgas was compared with existing programs, such as Prodigal, GeneMarkS, and Glimmer. Through testing 5,705 virus genomes downloaded from RefSeq, Vgas demonstrated its superiority with the highest average precision and recall (both indexes were 1% higher or more than the other programs); particularly for small virus genomes (≤ 10 kb), it showed significantly improved performance (precision was 6% higher, and recall was 2% higher). Moreover, Vgas presents an annotation module to provide functional information for predicted genes based on BLASTp alignment. This characteristic may be specifically useful in some cases. When combining Vgas with GeneMarkS and Prodigal, better prediction results could be obtained than with each of the three individual programs, suggesting that collaborative prediction using several different software programs is an alternative for gene prediction. Vgas is freely available at http://cefg.uestc.cn/vgas/ or http://121.48.162.133/vgas/. We hope that Vgas could be an alternative virus gene finder to annotate new genomes or reannotate existing genome.

The GC Content as a Main Factor Shaping the Amino Acid Usage During Bacterial Evolution Process.

Understanding how proteins evolve is important, and the order of amino acids being recruited into the genetic codons was found to be an important factor shaping the amino acid composition of proteins. The latest work about the last universal common ancestor (LUCA) makes it possible to determine the potential factors shaping amino acid compositions during evolution. Those LUCA genes/proteins from Methanococcus maripaludis S2, which is one of the possible LUCA, were investigated. The evolutionary rates of these genes positively correlate with GC contents with P-value significantly lower than 0.05 for 94% homologous genes. Linear regression results showed that compositions of amino acids coded by GC-rich codons positively contribute to the evolutionary rates, while these amino acids tend to be gained in GC-rich organisms according to our results. The first principal component correlates with the GC content very well. The ratios of amino acids of the LUCA proteins coded by GC rich codons positively correlate with the GC content of different bacteria genomes, while the ratios of amino acids coded by AT rich codons negatively correlate with the increase of GC content of genomes. Next, we found that the recruitment order does correlate with the amino acid compositions, but gain and loss in codons showed newly recruited amino acids are not significantly increased along with the evolution. Thus, we conclude that GC content is a primary factor shaping amino acid compositions. GC content shapes amino acid composition to trade off the cost of amino acids with bases, which could be caused by the energy efficiency.

Comprehensive exploration of the enzymes catalysing oxygen-involved reactions and COGs relevant to bacterial oxygen utilization.

To better understand the mechanisms of bacterial adaptation in oxygen environments, we explored the aerobic living-associated genes in bacteria by comparing Clusters of Orthologous Groups of proteins' (COGs) frequencies and gene expression analyses and 38 COGs were detected at significantly higher frequencies (p-value less than 1e-6) in aerobes than in anaerobes. Differential expression analyses between two conditions further narrowed the prediction to 27 aerobe-specific COGs. Then, we annotated the enzymes associated with these COGs. Literature review revealed that 14 COGs contained enzymes catalysing oxygen-involved reactions or products involved in aerobic pathways, suggesting their important roles for survival in aerobic environments. Additionally, protein-protein interaction analyses and step length comparisons of metabolic networks suggested that the other 13 COGs may function relevantly with the 14 enzymes-corresponding COGs, indicating that these genes may be highly associated with oxygen utilization. Phylogenetic and evolutionary analyses showed that the 27 COGs did not have similar trees, and all suffered purifying selection pressures. The divergent times of species containing or lacking aerobic COGs validated that the appearing time of oxygen-utilizing gene was approximately 2.80 Gyr ago. In addition to help better understand oxygen adaption, our method may be extended to identify genes relevant to other living environments.

Mutation Landscape of Base Substitutions, Duplications, and Deletions in the Representative Current Cholera Pandemic Strain.

Pandemic cholera is a major concern for public health because of its high mortality and morbidity. Mutation accumulation (MA) experiments were performed on a representative strain of the current cholera pandemic. Although the base-pair substitution mutation rates in Vibrio cholerae (1.24 × 10-10 per site per generation for wild-type lines and 3.29 × 10-8 for mismatch repair deficient lines) are lower than that previously reported in other bacteria using MA analysis, we discovered specific high rates (8.31 × 10-8 site/generation for wild-type lines and 1.82 × 10-6 for mismatch repair deficient lines) of base duplication or deletion driven by large-scale copy number variations (CNVs). These duplication-deletions are located in two pathogenic islands, IMEX and the large integron island. Each element of these islands has discrepant rate in rapid integration and excision, which provides clues to the pandemicity evolution of V. cholerae. These results also suggest that large-scale structural variants such as CNVs can accumulate rapidly during short-term evolution. Mismatch repair deficient lines exhibit a significantly increased mutation rate in the larger chromosome (Chr1) at specific regions, and this pattern is not observed in wild-type lines. We propose that the high frequency of GATC sites in Chr1 improves the efficiency of MMR, resulting in similar rates of mutation in the wild-type condition. In addition, different mutation rates and spectra were observed in the MA lines under distinct growth conditions, including minimal media, rich media and antibiotic treatments.

Amino acid compositions contribute to the proteins' evolution under the influence of their abundances and genomic GC content.

Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes. However, there are few studies of how amino acid composition can influence evolutionary rates in bacteria. Thus, we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria. Compositions of all amino acids can on average explain 21.5% of the variation in evolutionary rates among 273 investigated bacterial organisms. In five model organisms, amino acid composition contributes more to variation in evolutionary rates than protein abundance, and frequency of optimal codons. The contribution of individual amino acid composition to evolutionary rate varies among organisms. The closer the GC-content of genome to its maximum or minimum, the better the correlation between the amino acid content and the evolutionary rate of proteins would appear in that genome. The types of amino acids that significantly contribute to evolutionary rates can be grouped into GC-rich and AT-rich amino acids. Besides, the amino acid with high composition also contributes more to evolutionary rates than amino acid with low composition in proteome. In summary, amino acid composition significantly contributes to the rate of evolution in bacterial organisms and this in turn is impacted by GC-content.

Co-adaption of tRNA gene copy number and amino acid usage influences translation rates in three life domains.

Although more and more entangled participants of translation process were realized, how they cooperate and co-determine the final translation efficiency still lacks details. Here, we reasoned that the basic translation components, tRNAs and amino acids should be consistent to maximize the efficiency and minimize the cost. We firstly revealed that 310 out of 410 investigated genomes of three domains had significant co-adaptions between the tRNA gene copy numbers and amino acid compositions, indicating that maximum efficiency constitutes ubiquitous selection pressure on protein translation. Furthermore, fast-growing and larger bacteria are found to have significantly better co-adaption and confirmed the effect of this pressure. Within organism, highly expressed proteins and those connected to acute responses have higher co-adaption intensity. Thus, the better co-adaption probably speeds up the growing of cells through accelerating the translation of special proteins. Experimentally, manipulating the tRNA gene copy number to optimize co-adaption between enhanced green fluorescent protein (EGFP) and tRNA gene set of Escherichia coli indeed lifted the translation rate (speed). Finally, as a newly confirmed translation rate regulating mechanism, the co-adaption reflecting translation rate not only deepens our understanding on translation process but also provides an easy and practicable method to improve protein translation rates and productivity.

Zisland Explorer: detect genomic islands by combining homogeneity and heterogeneity properties.

Genomic islands are genomic fragments of alien origin in bacterial and archaeal genomes, usually involved in symbiosis or pathogenesis. In this work, we described Zisland Explorer, a novel tool to predict genomic islands based on the segmental cumulative GC profile. Zisland Explorer was designed with a novel strategy, as well as a combination of the homogeneity and heterogeneity of genomic sequences. While the sequence homogeneity reflects the composition consistence within each island, the heterogeneity measures the composition bias between an island and the core genome. The performance of Zisland Explorer was evaluated on the data sets of 11 different organisms. Our results suggested that the true-positive rate (TPR) of Zisland Explorer was at least 10.3% higher than that of four other widely used tools. On the other hand, the new tool did not lose overall accuracy with the improvement in the TPR and showed better equilibrium among various evaluation indexes. Also, Zisland Explorer showed better accuracy in the prediction of experimental island data. Overall, the tool provides an alternative solution over other tools, which expands the field of island prediction and offers a supplement to increase the performance of the distinct predicting strategy. We have provided a web service as well as a graphical user interface and open-source code across multiple platforms for Zisland Explorer, which is available at http://cefg.uestc.edu.cn/Zisland_Explorer/ or http://tubic.tju.edu.cn/Zisland_Explorer/.

Genomic Complexity Places Less Restrictions on the Evolution of Young Coexpression Networks than Protein-Protein Interactions.

The differences in evolutionary patterns of young protein-protein interactions (PPIs) among distinct species have long been a puzzle. However, based on our genome-wide analysis of available integrated experimental data, we confirm that young genes preferentially integrate into ancestral PPI networks, and that this manner is consistent in all of six model organisms with widely different levels of phenotypic complexity. We demonstrate that the level of restrictions placed on the evolution of biological networks declines with a decrease of phenotypic complexity. Compared with young PPI networks, new co-expression links have less evolutionary restrictions, so a young gene with a high possibility to be coexpressed other young genes relatively frequently emerges in the four simpler genomes among the six studied. However, it is not favorable for such young-young coexpression in terms of a young gene evolving into a coexpression hub, so the coexpression pattern could gradually decline. To explain this apparent contradiction, we suggest that young genes that are initially peripheral to networks are temporarily coexpressed with other young genes, driving functional evolution because of low selective pressure. However, as the expression levels of genes increase and they gradually develop a greater effect on fitness, young genes start to be coexpressed more with members of ancestral networks and less with other young genes. Our findings provide new insights into the evolution of biological networks.

Gene re-annotation in genome of the extremophile Pyrobaculum aerophilum by using bioinformatics methods.

In this paper, we re-annotated the genome of Pyrobaculum aerophilum str. IM2, particularly for hypothetical ORFs. The annotation process includes three parts. Firstly and most importantly, 23 new genes, which were missed in the original annotation, are found by combining similarity search and the ab initio gene finding approaches. Among these new genes, five have significant similarities with function-known genes and the rest have significant similarities with hypothetical ORFs contained in other genomes. Secondly, the coding potentials of the 1645 hypothetical ORFs are re-predicted by using 33 Z curve variables combined with Fisher linear discrimination method. With the accuracy being 99.68%, 25 originally annotated hypothetical ORFs are recognized as non-coding by our method. Thirdly, 80 hypothetical ORFs are assigned with potential functions by using similarity search with BLAST program. Re-annotation of the genome will benefit related researches on this hyperthermophilic crenarchaeon. Also, the re-annotation procedure could be taken as a reference for other archaeal genomes. Details of the revised annotation are freely available at http://cobi.uestc.edu.cn/resource/paero/