Noncoding RNAs (ncRNAs) have numerous roles in development and disease, and one of the prominent roles is to regulate gene expression. A vast number of circular RNAs (circRNAs) have been identified, and some have been shown to function as microRNA sponges in animal cells. Here, we report a class of circRNAs associated with RNA polymerase II in human cells. In these circRNAs, exons are circularized with introns 'retained' between exons; we term them exon-intron circRNAs or EIciRNAs. EIciRNAs predominantly localize in the nucleus, interact with U1 snRNP and promote transcription of their parental genes. Our findings reveal a new role for circRNAs in regulating gene expression in the nucleus, in which EIciRNAs enhance the expression of their parental genes in cis, and highlight a regulatory strategy for transcriptional control via specific RNA-RNA interaction between U1 snRNA and EIciRNAs.

To combat the spread of antibiotic resistance, methods that quantitatively assess the metabolism-inhibiting effects of drugs in a rapid and culture-independent manner are urgently needed. Here using four oral bacteria as models, we show that heavy water (DO)-based single-cell Raman microspectroscopy (DO-Raman) can probe bacterial response to different drugs using the Raman shift at the C-D (carbon-deuterium vibration) band in 2040 to 2300 cm as a universal biomarker for metabolic activity at single-bacterial-cell resolution. The "minimum inhibitory concentration based on metabolic activity" (MIC-MA), defined as the minimal dose under which the median ΔC-D-ratio at 8 h of drug exposure is ≤0 and the standard deviation (SD) of the ΔC-D ratio among individual cells is ≤0.005, was proposed to evaluate the metabolism-inhibiting efficacy of drugs. In addition, heterogeneity index of MIC-MA (MIC-MA-HI), defined as SD of C-D ratio among individual cells, quantitatively assesses the among-cell heterogeneity of metabolic activity after drug regimens. When exposed to 1× MIC of sodium fluoride (NaF), 1× MIC of chlorhexidine (CHX), or 60× MIC of ampicillin, the cariogenic oral pathogen Streptococcus mutans UA159 ceased propagation yet remained metabolically highly active. This underscores the advantage of MIC-MA over the growth-based MIC in being able to detect the "nongrowing but metabolically active" (NGMA) cells that underlie many latent or recurring infections. Moreover, antibiotic susceptible and resistant S. mutans strains can be readily discriminated at as early as 0.5 h. Thus, DO-Raman can serve as a universal method for rapid and quantitative assessment of antimicrobial effects based on general metabolic activity at single-cell resolution.

Our study provided evidence of the efficacy of PRP injection in the healing of small to medium PTRCTs. Moreover, the combined injection of SH and PRP yielded a better clinical outcome than SH or PRP alone.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Amplification and sequencing of 16S amplicons are widely used for profiling the structure of oral microbiota. However, it remains not clear whether and to what degree DNA extraction and targeted 16S rRNA hypervariable regions influence the analysis. Based on a mock community consisting of five oral bacterial species in equal abundance, we compared the 16S amplicon sequencing results on the Illumina MiSeq platform from six frequently employed DNA extraction procedures and three pairs of widely used 16S rRNA hypervariable primers targeting different 16S rRNA regions. Technical reproducibility of selected 16S regions was also assessed. DNA extraction method exerted considerable influence on the observed bacterial diversity while hypervariable regions had a relatively minor effect. Protocols with beads added to the enzyme-mediated DNA extraction reaction produced more accurate bacterial community structure than those without either beads or enzymes. Hypervariable regions targeting V3-V4 and V4-V5 seemed to produce more reproducible results than V1-V3. Neither sequencing batch nor change of operator affected the reproducibility of bacterial diversity profiles. Therefore, DNA extraction strategy and 16S rDNA hypervariable regions both influenced the results of oral microbiota biodiversity profiling, thus should be carefully considered in study design and data interpretation.

Replicating circular RNAs are independent plant pathogens known as viroids, or act to modulate the pathogenesis of plant and animal viruses as their satellite RNAs. The rate of discovery of these subviral pathogens was low over the past 40 years because the classical approaches are technical demanding and time-consuming. We previously described an approach for homology-independent discovery of replicating circular RNAs by analysing the total small RNA populations from samples of diseased tissues with a computational program known as progressive filtering of overlapping small RNAs (PFOR). However, PFOR written in PERL language is extremely slow and is unable to discover those subviral pathogens that do not trigger in vivo accumulation of extensively overlapping small RNAs. Moreover, PFOR is yet to identify a new viroid capable of initiating independent infection. Here we report the development of PFOR2 that adopted parallel programming in the C++ language and was 3 to 8 times faster than PFOR. A new computational program was further developed and incorporated into PFOR2 to allow the identification of circular RNAs by deep sequencing of long RNAs instead of small RNAs. PFOR2 analysis of the small RNA libraries from grapevine and apple plants led to the discovery of Grapevine latent viroid (GLVd) and Apple hammerhead viroid-like RNA (AHVd-like RNA), respectively. GLVd was proposed as a new species in the genus Apscaviroid, because it contained the typical structural elements found in this group of viroids and initiated independent infection in grapevine seedlings. AHVd-like RNA encoded a biologically active hammerhead ribozyme in both polarities, and was not specifically associated with any of the viruses found in apple plants. We propose that these computational algorithms have the potential to discover novel circular RNAs in plants, invertebrates and vertebrates regardless of whether they replicate and/or induce the in vivo accumulation of small RNAs.

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The potential of Raman-activated cell sorting (RACS) is inherently limited by conflicting demands for signal quality and sorting throughput. Here, we present positive dielectrophoresis–based Raman-activated droplet sorting (pDEP-RADS), where a periodical pDEP force was exerted to trap fast-moving cells, followed by simultaneous microdroplet encapsulation and sorting. Screening of yeasts for triacylglycerol (TAG) content demonstrated near-theoretical-limit accuracy, ~120 cells min−1 throughput and full-vitality preservation, while sorting fatty acid degree of unsaturation (FA-DU) featured ~82% accuracy at ~40 cells min−1. From a yeast library expressing algal diacylglycerol acyltransferases (DGATs), a pDEP-RADS run revealed all reported TAG-synthetic variants and distinguished FA-DUs of enzyme products. Furthermore, two previously unknown DGATs producing low levels of monounsaturated fatty acid–rich TAG were discovered. This first demonstration of RACS for enzyme discovery represents hundred-fold saving in time consumables and labor versus culture-based approaches. The ability to automatically flow-sort resonance Raman–independent phenotypes greatly expands RACS’ application.

In the version of this article initially published, the blots in Figure 2c were inadvertently replaced with a duplicate of the blots in Figure 2b.