By combining X-ray crystallography and modeling, we describe here the atomic structure of distinct adhesive moieties of FimA, the shaft fimbrillin of Actinomyces type 2 fimbriae, which uniquely mediates the receptor-dependent intercellular interactions between Actinomyces and oral streptococci as well as host cells during the development of oral biofilms. The FimA adhesin is built with three IgG-like domains, each of which harbors an intramolecular isopeptide bond, previously described in several Gram-positive pilins. Genetic and biochemical studies demonstrate that although these isopeptide bonds are dispensable for fimbrial assembly, cell-cell interactions and biofilm formation, they contribute significantly to the proteolytic stability of FimA. Remarkably, FimA harbors two autonomous adhesive modules, which structurally resemble the Staphylococcus aureus Cna B domain. Each isolated module can bind the plasma glycoprotein asialofetuin as well as the polysaccharide receptors present on the surface of oral streptococci and epithelial cells. Thus, FimA should serve as an excellent paradigm for the development of therapeutic strategies and elucidating the precise molecular mechanisms underlying the interactions between cellular receptors and Gram-positive fimbriae.

Background Whole exome sequencing (WES) is a cost-effective method that identifies clinical variants but it demands accurate variant caller tools. Currently available tools have variable accuracy in predicting specific clinical variants. But it may be possible to find the best combination of aligner-variant caller tools for detecting accurate single nucleotide variants (SNVs) and small insertion and deletion (InDels) separately. Moreover, many important aspects of InDel detection are overlooked while comparing the performance of tools, particularly its base pair length. Results We assessed the performance of variant calling pipelines using the combinations of four variant callers and five aligners on human NA12878 and simulated exome data. We used high confidence variant calls from Genome in a Bottle (GiaB) consortium for validation, and GRCh37 and GRCh38 as the human reference genome. Based on the performance metrics, both BWA and Novoalign aligners performed better with DeepVariant and SAMtools callers for detecting SNVs, and with DeepVariant and GATK for InDels. Furthermore, we obtained similar results on human NA24385 and NA24631 exome data from GiaB. Conclusion In this study, DeepVariant with BWA and Novoalign performed best for detecting accurate SNVs and InDels. The accuracy of variant calling was improved by merging the top performing pipelines. The results of our study provide useful recommendations for analysis of WES data in clinical genomics. Electronic supplementary material The online version of this article (10.1186/s12859-019-2928-9) contains supplementary material, which is available to authorized users.

PURPOSE. MicroRNAs (miRNAs) are small, stable, noncoding RNA molecules with regulatory function and marked tissue specificity that posttranscriptionally regulate gene expression. However, their role in fungal keratitis remains unknown. The purpose of this study was to identify the miRNA profile and its regulatory role in fungal keratitis. METHODS.Normal donor (n ¼ 3) and fungal keratitis (n ¼ 5) corneas were pooled separately, and small RNA deep sequencing was performed using a sequencing platform. A bioinformatics approach was applied to identify differentially-expressed miRNAs and their targets, and select miRNAs were validated by real-time quantitative PCR (qPCR). The regulatory functions of miRNAs were predicted by combining miRNA target genes and pathway analysis. The mRNA expression levels of select target genes were further analyzed by qPCR.RESULTS. By deep sequencing, 75 miRNAs were identified as differentially expressed with fold change greater than 2 and probability score greater than 0.9 in fungal keratitis corneas. The highly dysregulated miRNAs (miR-511-5p, miR-142-3p, miR-155-5p, and miR-451a) may regulate wound healing as they were predicted to specifically target wound inflammatory genes. Moreover, the increased expression of miR-451a in keratitis correlated with reduced expression of its target, macrophage migration inhibitory factor, suggesting possible regulatory functions.CONCLUSIONS. This is, to our knowledge, the first report on comprehensive human corneal miRNA expression profile in fungal keratitis. Several miRNAs with high expression in fungal keratitis point toward their potential role in regulation of pathogenesis. Further insights in understanding their role in corneal wound inflammation may help design new therapeutic strategies.

BackgroundThe spectrum of RB1gene mutations in Retinoblastoma (RB) patients and the necessity of multiple traditional methods for complete variant analysis make the molecular diagnosis a cumbersome, labor-intensive and time-consuming process. Here, we have used targeted next generation sequencing (NGS) approach with in-house analysis pipeline to explore its potential for the molecular diagnosis of RB.MethodsThirty-three patients with RB and their family members were selected randomly. DNA from patient blood and/or tumor was used for RB1 gene targeted sequencing. The raw reads were obtained from Illumina Miseq. An in-house bioinformatics pipeline was developed to detect both single nucleotide variants (SNVs) and small insertions/deletions (InDels) and to distinguish between somatic and germline mutations. In addition, ExomeCNV and Cn. MOPS were used to detect copy number variations (CNVs). The pathogenic variants were identified with stringent criteria, and were further confirmed by conventional methods and cosegregation in families.ResultsUsing our approach, an array of pathogenic variants including SNVs, InDels and CNVs were detected in 85% of patients. Among the variants detected, 63% were germline and 37% were somatic. Interestingly, nine novel pathogenic variants (33%) were also detected in our study.ConclusionsWe demonstrated for the first time that targeted NGS is an efficient approach for the identification of wide spectrum of pathogenic variants in RB patients. This study is helpful for the molecular diagnosis of RB in a comprehensive and time-efficient manner.

The whole exome sequencing (WES) is a time-consuming technology in the identification of clinical variants and it demands the accurate variant caller tools. The currently available tools compromise accuracy in predicting the specific types of variants. Thus, it is important to find out the possible combination of best aligner-variant caller tools for detecting SNVs and InDels separately. Moreover, many important aspects of InDel detection are not overlooked while comparing the performance of tools. One such aspect is the detection of InDels with respect to base pair length. To assess the performance of variant (especially InDels) caller in combination with different aligners, 20 automated pipelines were developed and evaluated using gold reference variant dataset (NA12878) from Genome in a Bottle (GiaB) consortium of human whole exome sequencing. Additionally, the simulated exome data from two human reference genome sequences (GRCh37 and GRCh38) were used to compare the performance of the pipelines. By analyzing various performance metrices, we observed that BWA and Novoalign aligners performed better with DeepVariant and SAMtools callers for detecting SNVs, and with DeepVariant and GATK for Indels. Altogether, DeepVariant with BWA and Novoalign performed best. Further, we showed that merging the top performing pipelines improved the accurate variant call set. Collectively, this study would help the investigators to effectively improve the sensitivity and accuracy in detecting specific variants.