Uncovering differences in the composition and function of phage communities and phage-bacterium interactions in raw soy sauce

IntroductionAlthough the composition and succession of microbial communities in soy sauce fermentation have been well-characterized, the understanding of phage communities in soy sauce remains limited.MethodsThis study determined the diversity, taxonomic composition, and predicted function of phage communities and the phage-host interactions in two types of raw soy sauce (Cantonese-type fermentation, NJ; Japanese-type fermentation, PJ) using shotgun metagenomics.Results and discussionThese two raw soy sauces showed differences in phage composition (121 viral operational taxonomic units (vOTUs) in NJ and 387 vOTUs in PJ), with a higher abundance of the family Siphoviridae (58.50%) in the NJ phage community and a higher abundance of Myoviridae (33.01%) in PJ. Auxiliary metabolic functional annotation analyses showed that phages in the raw soy sauces mostly encoded genes with unknown functions (accounting for 66.33% of COG profiles), but the NJ sample contained genes mostly annotated to conventional functions related to carbohydrate metabolism (0.74%) and lipid metabolism (0.84%), while the PJ sample presented a higher level of amino acid metabolism functions (0.12%). Thirty auxiliary metabolism genes (AMGs) were identified in phage genomes, which were associated with carbohydrate utilization, cysteine and methionine metabolism, and aspartic acid biosynthesis for the host. To identify phage-host interactions, 30 host genomes (affiliated with 22 genera) were also recruited from the metagenomic dataset. The phage-host interaction analysis revealed a wide range of phage hosts, for which a total of 57 phage contigs were associated with 17 host genomes, with Shewanella fodinae and Weissella cibaria infected by the most phages. This study provides a comprehensive understanding of the phage community composition, auxiliary metabolic functions, and interactions with hosts in two different types of raw soy sauce

Comparative Analysis of the Complete Mitochondrial Genomes for Development Application

This present research work reports the comparative analysis of the entire nucleotide sequence of mitochondrial genomes of Serranochromis robustus and Buccochromis nototaenia and phylogenetic analyses of their protein-coding genes in order to establish their phylogenetic relationship within Cichlids. The mitochondrial genomes of S. robustus and B. nototaenia are 16,583 and 16,580 base pairs long, respectively, including 13 protein-coding genes (PCGs), 2 ribosomal RNA genes, 22 transfer RNA genes, and one control region (D-loop) which is 888 and 887 base pairs long, respectively, showing the same gene order and identical number of gene or regions with other well-elucidated mitogenomes of Cichlids. However, with exception of cytochrome-c oxidase subunit-1 (COX-1) gene, all the identified PCGs were initiated by ATG-codons. Structurally, 11 tRNA genes in B. nototaenia species and 9 tRNA genes in S. robustus species, folded into typical clover-leaf secondary structure created by the regions of self-complementarity within tRNA. All the 22 tRNA genes in both species lack variable loop. Moreover, 28 genes which include 12-protein-coding genes are encoded on the H-strand and the remaining 9 genes including one protein-coding gene are encoded on the L-strand. Thirteen sequences of concatenated mitochondrial protein-coding genes were aligned using MUSCLE, and the phylogenetic analyses performed using maximum likelihood and Bayesian inference showed that S. robustus and B. nototaenia had a broad phylogenetic relationship. These results may be a useful tool in resolving higher-level relationships in organisms and a useful dataset for studying the evolution of the Cichlidae mitochondrial genome, since Cichlids are well-known model species in the study of evolutionary biology, because of their extreme morphological, biogeographical, parental care behavior for eggs and larvae and phylogenetic diversities

A review on the modeling and simulations of solid-state diffusional phase transformations in metals and alloys

Solid-state diffusional phase transformations are vital approaches for controlling of the material microstructure and thus tailoring the properties of metals and alloys. To exploit this mean to a full extent, much effort is paid on the reliable and efficient modeling and simulation of the phase transformations. This work gives an overview of the developments in theoretical research of solid-state diffusional phase transformations and the current status of various numerical simulation techniques such as empirical and analytical models, phase field, cellular automaton methods, Monte Carlo models and molecular dynamics methods. In terms of underlying assumptions, physical relevance, implementation and computational efficiency for the simulation of phase transformations, the advantages and disadvantages of each numerical technique are discussed. Finally, trends or future directions of the quantitative simulation of solid-state diffusional phase transformation are provided

Distribution Property of Shear Strength Parameters of Q2 and Q3 Loess in Northwest China and Its Application in Reliability Analysis of Natural and Filled Slopes

Geological materials have randomness in nature. Statistical analysis can help revealing the variation pattern of the material parameters and the reliability of the slope. In this paper, the probability distribution and variability of shear strength parameters of typical Q2 and Q3 loess in Northwest China were statistically analysed using the collected geological survey data in Yan`an, Shaanxi Province. Resulting probability properties were applied to the reliability analysis for the natural and fill slope in loess area using the Monte Carlo Method. Finally, an optimization analysis was carried out for the fill slope in the background engineering project. Research results show that normal distribution and lognormal distribution can be used to describe the statistical properties of c and φ of Q2 and Q3 loess. Variance of c is large while the variability of φ is relatively small. The influence of the variability of φ on the reliability index of loess natural slope is generally larger than that of c. On the contrary, influence of the variability of c on the reliability index of the fill slope is generally greater than that of φ, which is related to the structural and uniformity of the soil. Finally, relation between slope height and minimum gradient coefficient is linear when the failure probability of fill slope is less than 10%. Results in this study can be used as a reference for the slope design and construction for the cut and fill engineering in loess area

Smooth Non-negative Low-Rank Graph Representation for Clustering

The existing low-rank graph representation algorithms fail to capture the global representation structure of data accurately, and cannot make full use of the valid information of data to guide the construction of the representation graph, then the constructed representation graph does not have a connected structure suitable for clustering. A smooth non-negative low-rank graph representation method for clustering (SNLRR) is proposed to solve these problems. To more accurately capture the global representation structure of data, SNLRR uses a logarithmic determinant function that is more consistent with the rank characteristics of the matrix to replace the kernel norm to estimate the rank function smoothly, which can effectively reduce the impact of larger singular values of the matrix on the rank estimation, balance the contribution of all singular values to the rank estimation, enhance the accuracy of the rank estimation, so as to more accurately capture the global representation structure of the data. The distance regularization term is also introduced to adaptively assign the optimal nearest neighbor learning representation matrix for each data point to capture the local representation structure of data. Besides, SNLRR applies rank constraint on the Laplace matrix of representation matrix so that the learned representation graph has the same number of connected components as the real number of clusters, that is, the resulting representation graph has a interconnected structure suitable for clustering. Experimental results on seven datasets with high dimensions and complex distribution, using eight comparison algorithms, show that the clustering performance of SNLRR algorithm is better than that of the eight comparison algorithms, with an average increase of 0.2073 in accuracy and 0.1758 in NMI. Therefore, SNLRR is a graph representation clustering algorithm that can effectively handle data with high dimensions and complex distribution

Research on the Soil-Plugging Effect on Small-Diameter Jacked Piles through In Situ Testing and DEM Simulation

Small-diameter jacked piles are widely used in civil engineering. The formation and development of the soil-plugging effect and surface frictional behavior of jacked piles have a high impact on the construction process and pile quality. Clarifying the developmental pattern of the soil-plugging effect and the change law of frictional force forms the premise of scientific construction and construction quality. Firstly, we carried out two groups of in situ tests on the small-diameter jacked piles, recording the relationship between penetration depth and resistance force. Then, the discrete element method (DEM) was used to analyze the mechanical behavior of the small-diameter jacked piles during the construction process. The particle flow code (PFC) 2D was used to carry out the DEM simulation. The research results show that pile resistance exhibited an irregular development trend as the construction process proceeded. There is a sudden change in pile resistance when the pile tip reaches the interface of certain soil layers. Both tests revealed the same phenomenon, yet both occurred at different depths. The DEM analysis showed that plug sliding was the main reason for the above phenomenon. The difference in strength and stiffness of adjacent soil layers causes the soil plug to slide, leading to a sudden change in pile resistance. When the upper layer is soft and the layer below is hard, this phenomenon is especially obvious. This also leads to a difference in the location of the sudden change in pile resistance between the two groups of tests. The research results of this paper can be helpful for revealing the relationship between the soil-plugging effect of small-diameter jacked piles and the development of pile resistance and also provides a reference for relevant engineering construction and design