Halomonas borealis sp. nov. and Halomonas niordiana sp. nov., two new species isolated from seawater

Two Gram-negative strains obtained from tank water in a scallop hatchery in Norway, were phenotypically and genotypically characterized in order to clarify their taxonomic position. On the basis of 16S rRNA gene sequence analysis, these isolates, ATF 5.2^T and ATF 5.4^T, were included in the genus Halomonas, being their closest relatives H. smyrnensis and H. taeanensis, with similarities of 98.9% and 97.7%, respectively. Sequence analysis of the housekeeping genes atpA, ftsZ, gyrA, gyrB, mreB, rpoB, rpoD, rpoE, rpoH, rpoN and rpoS clearly differentiated the isolates from the currently described Halomonas species, and the phylogenetic analysis using concatenated sequences of these genes located them in two robust and independent branches. DNA–DNA hybridization (eDDH) percentage, together with average nucleotide identity (ANI), were calculated using the complete genome sequences of the strains, and demonstrate that the isolates constitute two new species of Halomonas, for which the names of Halomonas borealis sp. nov. and Halomonas niordiana sp. nov. are proposed, with type strains ATF 5.2^T (=CECT 9780^T = LMG 31367^T) and ATF 5.4^T (=CECT 9779^T = LMG 31227^T), respectively.     

Measuring the subgingival microbiota in periodontitis patients: Comparison of the surface layer and the underlying layers

Periodontitis is a major cause of tooth loss in adults that initially results from dental plaque. Subgingival plaque pathogenesis is affected by both community composition and plaque structures, although limited data are available concerning the latter. To bridge this knowledge gap, subgingival plaques were obtained using filter paper (the fourth layer) and curette (the first-third layers) sequentially and the phylogenetic differences between the first–third layers and the fourth layer were characterized by sequencing the V3–V4 regions of 16S rRNA. A total of 11 phyla, 148 genera, and 308 species were obtained by bioinformatic analysis, and no significant differences between the operational taxonomic unit numbers were observed for these groups. In both groups, the most abundant species were Porphyromonas gingivalis and Fusobacterium nucleatum. Actinomyces naeslundii, Streptococcus intermedius, and Prevotella intermedia possessed relatively high proportions in the first–third layers; while in the fourth layer, both traditional pathogens (Treponema denticola and Campylobacter rectus) and novel pathobionts (Eubacterium saphenum, Filifactor alocis, Treponema sp. HOT238) were prominent. Network analysis showed that either of them exhibited a scale-free property and was constructed by two negatively correlated components (the pathogen component and the nonpathogen component), while the synergy in the nonpathogen component was lower in the first–third layers than that in the fourth layer. After merging these two parts into a whole plaque group, the negative/positive correlation ratio increased. With potential connections, the first–third layers and the fourth layer showed characteristic key nodes in bacterial networks.     

Molecular characterization of rotaviruses obtained from patients with rotavirus-associated encephalitis/encephalopathy

Group A rotavirus (RVA) rarely causes severe complications such as encephalitis/encephalopathy. However, the pathophysiology of this specific complication remains unclear. Next-generation sequence analysis was used to compare the entire genome sequences of RVAs detected in patients with encephalitis/encephalopathy and gastroenteritis. This study enrolled eight patients with RVA encephalitis/encephalopathy and 10 with RVA gastroenteritis who were treated between February 2013 and July 2014. Viral RNAs were extracted from patients' stool, and whole-genome sequencing analysis was carried out to identify the specific gene mutations in RVA obtained from patients with severe neurological complications. Among the eight encephalitis/encephalopathy cases, six strains were DS-1-like G1P[8] and the remaining two were Wa-like G1P[8] (G1-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1). Meanwhile, eight of the 10 viruses detected in rotavirus gastroenteritis patients were DS-1-like G1P[8], and the remaining two were Wa-like G1P[8]. These strains were further characterized by conducting phylogenetic analysis. No specific clustering was demonstrated in RVAs detected from encephalitis/encephalopathy patients. Although the DS-1-like G1P[8] strain was predominant in both groups, no specific molecular characteristics were detected in RVAs from patients with severe central nervous system complications.     

Machine learning techniques for protein function prediction

Proteins play important roles in living organisms, and their function is directly linked with their structure. Due to the growing gap between the number of proteins being discovered and their functional characterization (in particular as a result of experimental limitations), reliable prediction of protein function through computational means has become crucial. This paper reviews the machine learning techniques used in the literature, following their evolution from simple algorithms such as logistic regression to more advanced methods like support vector machines and modern deep neural networks. Hyperparameter optimization methods adopted to boost prediction performance are presented. In parallel, the metamorphosis in the features used by these algorithms from classical physicochemical properties and amino acid composition, up to text-derived features from biomedical literature and learned feature representations using autoencoders, together with feature selection and dimensionality reduction techniques, are also reviewed. The success stories in the application of these techniques to both general and specific protein function prediction are discussed.     

Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.     

DPSN：扩增子测序引物标准化命名数据库

扩增子测序是目前用来衡量微生物多样性时使用最广泛的测序手段。因为其扩增的需要,所以选择合适的特定引物是必需的,且其对结果影响甚大。probeBase是目前最常用的记录了人工校正后的rRNA探针和引物的数据库。然而,我们发现probeBase中63.58%的引物存在不同程度的注释错误,包括命名重复、命名无规律以及匹配位置错误等。更严重的是,目前主流的短命名方式不具有唯一性,导致对应关系模糊不清。因此,我们定义了更简单可行的短命名标准并开发了新的引物科学命名数据库（DPSN）,并对probeBase里的所有173个引物进行了校正,并新加入了4个新的改良引物以及38个针对大亚基的新引物。新的短命名规则包含3个基本要素：在正链5''端的位置、版本号和方向。此外在前面加入了识别大/小亚基以及主要针对的菌界的标志。使用DPSN,可以快速查找感兴趣区域对应的引物并比较不同版本的差异选择合适的引物。同时还能建立命名与序列的明确一一对应关系,避免歧义。     

Plastid DNA sequencing and nuclear SNP genotyping help resolve the puzzle of central American Platanus

Background and Aims

Recent research on the history of Platanus reveals that hybridization phenomena occurred in the central American species. This study has two goals: to help resolve the evolutive puzzle of central American Platanus, and to test the potential of real-time polymerase chain reaction (PCR) for detecting ancient hybridization.

Methods

Sequencing of a uniparental plastid DNA marker [psbA-trnH^(GUG) intergenic spacer] and qualitative and quantitative single nucleotide polymorphism (SNP) genotyping of biparental nuclear ribosomal DNA (nrDNA) markers [LEAFY intron 2 (LFY-i2) and internal transcribed spacer 2 (ITS2)] were used.

Key Results

Based on the SNP genotyping results, several Platanus accessions show the presence of hybridization/introgression, including some accessions of P. rzedowskii and of P. mexicana var. interior and one of P. mexicana var. mexicana from Oaxaca (= P. oaxacana). Based on haplotype analyses of the psbA-trnH spacer, five haplotypes were detected. The most common of these is present in taxa belonging to P. orientalis, P. racemosa sensu lato, some accessions of P. occidentalis sensu stricto (s.s.) from Texas, P. occidentalis var. palmeri, P. mexicana s.s. and P. rzedowskii. This is highly relevant to genetic relationships with the haplotypes present in P. occidentalis s.s. and P. mexicana var. interior.

Conclusions

Hybridization and introgression events between lineages ancestral to modern central and eastern North American Platanus species occurred. Plastid haplotypes and qualitative and quantitative SNP genotyping provide information critical for understanding the complex history of Mexican Platanus. Compared with the usual molecular techniques of sub-cloning, sequencing and genotyping, real-time PCR assay is a quick and sensitive technique for analysing complex evolutionary patterns.