Exploration of pathogenic microorganism within the small intestine of necrotizing enterocolitis.

BACKGROUND: Necrotizing enterocolitis (NEC) is the most common severe gastrointestinal emergency in neonates. We designed this study to identify the pathogenic microorganisms of NEC in the microbiota of the small intestine of neonates. METHODS: Using the 16S ribosomal DNA (rDNA) sequencing method, we compared and analyzed the structure and diversity of microbiotas in the intestinal feces of different groups of neonates: patients undergoing jejunostomy to treat NEC (NP group), neonates undergoing jejunostomy to treat other conditions (NN group), and neonates with NEC undergoing conservative treatment (NC group). We took intestinal feces and saliva samples from patients at different time points. RESULTS: The beta diversities of the NP, NN, and NC groups were all similar. When comparing the beta diversities between different time points in the NP group, we found similar beta diversities at time points E1 to E3 but significant differences between the E2-E3 and E4 time points: the abundances of Klebsiella and Enterococcus (Proteobacteria) were higher at the E1-E3 time points; the abundance of Escherichia-Shigella (Proteobacteria) increased at the E2 time point, and the abundance of Klebsiella decreased significantly, whereas that of Streptococcus increased significantly at the E4 time point. CONCLUSIONS: Our results suggest that the pathological changes of intestinal necrosis in the small intestine of infants with NEC are not directly caused by excessive proliferation of pathogenic bacteria in the small intestine. The sources of microbiota in the small intestine of neonates, especially in premature infants, may be affected by multiple factors.

Using Huffman coding method to visualize and analyze DNA sequences.

On the basis of the Huffman coding method, we propose a new graphical representation of DNA sequence. The representation can avoid degeneracy and loss of information in the transfer of data from a DNA sequence to its graphical representation. Then a multicomponent vector from the representation is introduced to characterize quantitatively DNA sequences. The components of the vector are derived from the graphical representation of DNA primary sequence. The examination of similarities and dissimilarities among the complete coding sequences of ß-globin gene of 11 species and six ND6 proteins shows the utility of the scheme.

Self-similarity analysis of eubacteria genome based on weighted graph.

We introduce a weighted graph model to investigate the self-similarity characteristics of eubacteria genomes. The regular treating in similarity comparison about genome is to discover the evolution distance among different genomes. Few people focus their attention on the overall statistical characteristics of each gene compared with other genes in the same genome. In our model, each genome is attributed to a weighted graph, whose topology describes the similarity relationship among genes in the same genome. Based on the related weighted graph theory, we extract some quantified statistical variables from the topology, and give the distribution of some variables derived from the largest social structure in the topology. The 23 eubacteria recently studied by Sorimachi and Okayasu are markedly classified into two different groups by their double logarithmic point-plots describing the similarity relationship among genes of the largest social structure in genome. The results show that the proposed model may provide us with some new sights to understand the structures and evolution patterns determined from the complete genomes.

New method for global alignment of 2 DNA sequences by the tree data structure.

We introduce a new approach to investigate problem of DNA sequence alignment. The method consists of three parts: (i) simple alignment algorithm, (ii) extension algorithm for largest common substring, (iii) graphical simple alignment tree (GSA tree). The approach firstly obtains a graphical representation of scores of DNA sequences by the scoring equation R(0)*R-S(0)*S-T(0)*(a+bk). Then a GSA tree is constructed to facilitate solving the problem for global alignment of 2 DNA sequences. Finally we give several practical examples to illustrate the utility and practicality of the approach.

Classification analysis of dual nucleotides using dimension reduction.

We introduce a new approach to investigate the dual nucleotides compositions of 11 Gram-positive and 12 Gram-negative eubacteria recently studied by Sorimachi and Okayasu. The approach firstly obtains a 16-dimension vector set of dual nucleotides by PN-curve from the complete genome of organism. Each vector of the set corresponds to a single gene of genome. Then we reduce the 16-dimension vector set to 2-dimension by principal components analysis (PCA). The reduction avoids possible loss of information averaging all 16-dimension vectors. Then we suggest a 2D graphical representation based on the 2-dimension vector to investigate the classification patters among different organisms.

Application of 2D graphic representation of protein sequence based on Huffman tree method.

Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts. One is about the 0-1 codes of 20 amino acids by Huffman tree with amino acid frequency. The amino acid frequency is defined as the statistical number of an amino acid in the analyzed protein sequences. The other is about the 2D graphic representation of protein sequence based on the 0-1 codes. Then the applications of the method on ten ND5 genes and seven Escherichia coli strains are presented in detail. The results show that the proposed model may provide us with some new sights to understand the evolution patterns determined from protein sequences and complete genomes.

Gene comparison based on the repetition of single-nucleotide structure patterns.

According to the repetition structure patterns of single-nucleotides, we propose a novel digital representation method to characterize primary DNA sequences. Based on this representation we give a new RP-SP (repeat and space) vector to compute the distance of different sequences. The examination of similarities/dissimilarities among different sequences illustrates the utility of the proposed RP-SP vector distance. Then, we use the proposed RP-SP vector method to analyze two groups of genomes, 15 E. coli genomes and 31 mitochondrial genomes. For comparison, we also apply other alignment-free methods to the two groups of genomes. The results show that the proposed method can distinguish characteristics of different genomes and used to reconstruct the phylogenetic tree of different genomes.

Numerical characterization of DNA sequences based on digital signal method.

Based on digital signal method, we propose a new representation of DNA primary sequence. The representation can completely avoid loss of information in the transfer of data from a DNA sequence to its mathematical representation. Afterwards, we suggest one such approach to reach quantification of similarities based on digital signal similarity theory. The examination of similarities/dissimilarities among the coding sequences of the first exon of beta-globin gene of 11 species shows the utility of the scheme.

New 3D graphical representation of DNA sequence based on dual nucleotides.

We introduce a 3D graphical representation of DNA sequences based on the pairs of dual nucleotides (DNs). Based on this representation, we consider some mathematical invariants and construct two 16-component vectors associated with these invariants. The vectors are used to characterize and compare the complete coding sequence part of beta globin gene of nine different species. The examination of similarities/dissimilarities illustrates the utility of the approach.