ADAR1-mediated RNA editing promotes B cell lymphomagenesis.

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-κB signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-κB signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3'UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

MultiEditR: The first tool for the detection and quantification of RNA editing from Sanger sequencing demonstrates comparable fidelity to RNA-seq.

We present MultiEditR (Multiple Edit Deconvolution by Inference of Traces in R), the first algorithm specifically designed to detect and quantify RNA editing from Sanger sequencing (z.umn.edu/multieditr). Although RNA editing is routinely evaluated by measuring the heights of peaks from Sanger sequencing traces, the accuracy and precision of this approach has yet to be evaluated against gold standard next-generation sequencing methods. Through a comprehensive comparison to RNA sequencing (RNA-seq) and amplicon-based deep sequencing, we show that MultiEditR is accurate, precise, and reliable for detecting endogenous and programmable RNA editing.

Harnessing self-labeling enzymes for selective and concurrent A-to-I and C-to-U RNA base editing.

The SNAP-ADAR tool enables precise and efficient A-to-I RNA editing in a guideRNA-dependent manner by applying the self-labeling SNAP-tag enzyme to generate RNA-guided editases in cell culture. Here, we extend this platform by combining the SNAP-tagged tool with further effectors steered by the orthogonal HALO-tag. Due to their small size (ca. 2 kb), both effectors are readily integrated into one genomic locus. We demonstrate selective and concurrent recruitment of ADAR1 and ADAR2 deaminase activity for optimal editing with extended substrate scope and moderate global off-target effects. Furthermore, we combine the recruitment of ADAR1 and APOBEC1 deaminase activity to achieve selective and concurrent A-to-I and C-to-U RNA base editing of endogenous transcripts inside living cells, again with moderate global off-target effects. The platform should be readily transferable to further epitranscriptomic writers and erasers to manipulate epitranscriptomic marks in a programmable way with high molecular precision.

SARS-CoV-2 variant evolution in the United States: High accumulation of viral mutations over time likely through serial Founder Events and mutational bursts.

Since the first case of COVID-19 in December 2019 in Wuhan, China, SARS-CoV-2 has spread worldwide and within a year and a half has caused 3.56 million deaths globally. With dramatically increasing infection numbers, and the arrival of new variants with increased infectivity, tracking the evolution of its genome is crucial for effectively controlling the pandemic and informing vaccine platform development. Our study explores evolution of SARS-CoV-2 in a representative cohort of sequences covering the entire genome in the United States, through all of 2020 and early 2021. Strikingly, we detected many accumulating Single Nucleotide Variations (SNVs) encoding amino acid changes in the SARS-CoV-2 genome, with a pattern indicative of RNA editing enzymes as major mutators of SARS-CoV-2 genomes. We report three major variants through October of 2020. These revealed 14 key mutations that were found in various combinations among 14 distinct predominant signatures. These signatures likely represent evolutionary lineages of SARS-CoV-2 in the U.S. and reveal clues to its evolution such as a mutational burst in the summer of 2020 likely leading to a homegrown new variant, and a trend towards higher mutational load among viral isolates, but with occasional mutation loss. The last quartile of 2020 revealed a concerning accumulation of mostly novel low frequency replacement mutations in the Spike protein, and a hypermutable glutamine residue near the putative furin cleavage site. Finally, end of the year data and 2021 revealed the gradual increase to prevalence of known variants of concern, particularly B.1.1.7, that have acquired additional Spike mutations. Overall, our results suggest that predominant viral genomes are dynamically evolving over time, with periods of mutational bursts and unabated mutation accumulation. This high level of existing variation, even at low frequencies and especially in the Spike-encoding region may become problematic when super-spreader events, akin to serial Founder Events in evolution, drive these rare mutations to prominence.

C-to-U RNA Editing: From Computational Detection to Experimental Validation.

The AID/APOBEC family of enzymes are cytidine deaminases that act upon DNA and RNA. Among APOBECs, the best characterized family member to act on RNA is the enzyme APOBEC1. APOBEC1-mediated RNA editing plays a key role in lipid metabolism and in maintenance of brain homeostasis. Editing can be easily detected in RNA-seq data as a cytosine to thymine (C-to-T) change with regard to the reference. However, there are many other sources of base conversions relative to reference, such as PCR errors, SNPs, and even DNA editing by mutator APOBECs. Furthermore, APOBEC1 exhibits disparate activity in different cell types, with respect to which transcripts are edited and the level to which they are edited. When considering these potential sources of error and variability, an RNA-seq comparison between wild-type APOBEC1 sample and a matched control with an APOBEC1 knockout is a reliable method for the discrimination of true sites edited by APOBEC1. Here we present a detailed description of a method for studying APOBEC1 RNA editing, specifically in the murine macrophage cell line RAW 264.7. Our method covers the production of an APOBEC1 knockout cell line using the CRISPR/Cas9 system, through to experimental validation and quantification of editing sites (where we discuss a recently published algorithm (termed MultiEditR) which allows for the detection and quantification of RNA editing from Sanger sequencing). Importantly, this same protocol can be adapted to any RNA modification detectable by RNA-seq analysis for which the responsible protein is known.

Characterization and Quantitative Determination of a Diverse Group of Bacillus subtilis subsp. subtilis NCIB 3610 Antibacterial Peptides.

Five antibacterial peptides produced by Bacillus subtilis NCIB 3610 were purified, quantified, characterized, and identified in the present study. Cell-free extracts were subjected to three purification protocols employing ammonium sulfate or organic solvent precipitation and their combination, followed by ion-exchange chromatography, solid-phase extraction, and preparative high-performance liquid chromatography (HPLC). The combined ammonium sulfate and organic solvent precipitation extraction protocol presented the best results for peptide purification. In the five fractions that presented antimicrobial activity, antibacterial peptides were quantified by the turbidometric method and by HPLC using nisin for external calibration, with the second providing more accurate results. All peptides were pH- and temperature-resistant and their sensitivity to proteases treatment indicated their proteinic nature. The five peptides were subjected to microwave-assisted acid hydrolysis (MAAH) and following derivatization were analyzed using norleucine as the internal standard, to determine their amino acid content. The identification of the isolated peptides using the UniProt and PubChem databases indicated that the four peptides correspond to UniProt entries of the bacteriocins Subtilosin-A (Q1W152) Subtilosin-SbOX (H6D9P4), Ericin B (Q93GH3), Subtilin (P10946), and the fifth to the non-ribosomal antibacterial lipopeptide surfactin (CID:443592). The amino acid content determination and computational analyses, applied in the present work on the antimicrobial peptides of B. subtilis, proved an efficient screening and quantification method of bacteriocins that could potentially be applied in other bacterial strains. The constructed phylogenetic trees heterogeneity observed across the five peptides investigated might be indicative of competitive advantage of the strain.

Identification of bacteriocins secreted by the probiotic Lactococcus lactis following microwave-assisted acid hydrolysis (MAAH), amino acid content analysis, and bioinformatics.

A novel, generally applicable method of identifying peptides using HPLC, microwave-assisted acid hydrolysis (MAAH), and bioinformatics is described. Method validation was performed on bacteriocins-antibacterial peptides produced by probiotic bacteria-using nine different bacteriocin isolates secreted by the probiotic Lactococcus lactis. Calibration curves were constructed for 23 amino acid PTH derivatives, and analysis was performed using norleucine as the internal standard. Validation of amino acid analysis performed in the range 2.5-100 nmol/mL indicated excellent method linearity, while the LODs ranged from 0.17 to 2.88 nmol/mL and the LOQs from 0.51 to 8.75 nmol/mL. The MAAH method was developed by irradiating nisaplin for various durations at 700 W, with 7 min providing the best results. The amino acid content of each sample was estimated following the application of MAAH to ten different samples. The bacteriocins in our samples were identified using the UniProt database. Eight of nine peptides were identified as UniProt entries: nisin A (P13068), nisin Z (P29559), I4DSZ9, OB7236, P36499, OB7237, A0A0M7BH60, and T2C9F0. The phylogenetic tree was constructed for nisin A and nisin Z using the multiple sequence aligning tool Clustal Ω. The identified nisin types presented excellent correlation with their ModBase-predicted structures. The present method gives true, precise, and rapid results, and requires only standard technical equipment. Our results suggest that the present approach can facilitate the discovery of novel bacteriocins and provide useful information on not only the amino acid contents of peptides but also the evolution of protein biology. Graphical abstract Identification of eight bacteriocins secreted by the probiotic L. lactis, following microwave assisted acid hydrolysis (MAAH), amino acid content analysis of each sample with HPLC-DAD and bioinformatics analysis using Uniprot, Clustal Ω and ModBase.