Decomposition is a complex process involving the interaction of both biotic and abiotic factors. Microbes play a critical role in the process of carrion decomposition. In this study, we analysed bacterial communities from live rats and rat remains decomposed under natural conditions, or excluding sarcosaphagous insect interference, in China using Illumina MiSeq sequencing of 16S rRNA gene amplicons. A total of 1,394,842 high-quality sequences and 1,938 singleton operational taxonomic units were obtained. Bacterial communities showed notable variation in relative abundance and became more similar to each other across body sites during the decomposition process. As decomposition progressed, Proteobacteria (mostly Gammaproteobacteria) became the predominant phylum in both the buccal cavity and rectum, while Firmicutes and Bacteroidetes in the mouth and rectum, respectively, gradually decreased. In particular, the arrival and oviposition of sarcosaphagous insects had no obvious influence on bacterial taxa composition, but accelerated the loss of biomass. In contrast to the rectum, the microbial community structure in the buccal cavity of live rats differed considerably from that of rats immediately after death. Although this research indicates that bacterial communities can be used as a “microbial clock” for the estimation of post-mortem interval, further work is required to better understand this concept.

Insects attracted to cadavers may provide important indications of the postmortem interval (PMI). However, use of the flesh flies (Diptera: Sarcophagidae) for PMI estimation is limited as the species are often not morphologically distinct, especially as immatures. In this study, 23 forensically important flesh flies were collected from 13 locations in 10 Chinese provinces. Then, a 278-bp segment of the cytochrome oxidase subunits one (COI) gene and a 289-bp segment of the 16S rDNA gene of all specimens were successfully sequenced. Phylogenetic analysis of the sequenced segments showed that all sarcophagid specimens were properly assigned into four species (Boerttcherisca peregrina [Robineau-Desvoidy, 1830], Helicophagella melanura [Meigen, 1826], Parasarcophaga albiceps [Meigen, 1826], and Parasarcophaga dux [Thompson, 1869]) with relatively strong supporting values, thus indicating that the COI and 16S rDNA regions are suitable for identification of sarcophagid species. The difference between intraspecific threshold and interspecific divergence confirmed the potential of the two regions for sarcophagid species identification.

Background An outbreak of infection caused by SARS-CoV-2 recently has brought a great challenge to public health. Rapid identification of immune epitopes would be an efficient way to screen the candidates for vaccine development at the time of pandemic. This study aimed to predict the protective epitopes with bioinformatics methods and resources for vaccine development. Methods The genome sequence and protein sequences of SARS-CoV-2 were retrieved from the National Center for Biotechnology Information (NCBI) database. ABCpred and BepiPred servers were utilized for sequential B-cell epitope analysis. Discontinuous B-cell epitopes were predicted via DiscoTope 2.0 program. IEDB server was utilized for HLA-1 and HLA-2 binding peptides computation. Surface accessibility, antigenicity, and other important features of forecasted epitopes were characterized for immunogen potential evaluation. Results A total of 63 sequential B-cell epitopes on spike protein were predicted and 4 peptides (Spike315–324, Spike333–338, Spike648–663, Spike1064–1079) exhibited high antigenicity score and good surface accessibility. Ten residues within spike protein (Gly496, Glu498, Pro499, Thr500, Leu1141, Gln1142, Pro1143, Glu1144, Leu1145, Asp1146) are forecasted as components of discontinuous B-cell epitopes. The bioinformatics analysis of HLA binding peptides within nucleocapsid protein produced 81 and 64 peptides being able to bind MHC class I and MHC class II molecules respectively. The peptides (Nucleocapsid66–75, Nucleocapsid104–112) were predicted to bind a wide spectrum of both HLA-1 and HLA-2 molecules. Conclusions B-cell epitopes on spike protein and T-cell epitopes within nucleocapsid protein were identified and recommended for developing a protective vaccine against SARS-CoV-2.

We propose a minimum span clustering (MSC) method for clustering and visualizing complex networks using the interrelationship of network components. To demonstrate this method, it is applied to classify the social science network in terms of aggregated journal-journal citation relations of the Institute of Scientific Information (ISI) Journal Citation Reports. This method of network classification is shown to be efficient, with a processing time that is linear to network size. The classification results provide an in-depth view of the network structure at various scales of resolution. For the social science network, there are 4 resolution scales, including 294 batches of journals at the highest scale, 65 categories of journals at the second, 15 research groups at the third scale, and 3 knowledge domains at the lowest resolution. By comparing the relatedness of journals within clusters, we show that our clustering method gives a better classification of social science journals than ISI's heuristic approach and hierarchical clustering. In combination with the minimum spanning tree approach and multi-dimensional scaling, MSC is also used to investigate the general structure of the network and construct a map of the social science network for visualization.

No abstract