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Offering patients with tuberculosis (TB) an optimal and timely treatment regimen depends on the rapid detection of Mycobacterium tuberculosis (Mtb) drug resistance from clinical samples. Finding Low Abundance Sequences by Hybridization (FLASH) is a technique that harnesses the efficiency, specificity, and flexibility of the Cas9 enzyme to enrich targeted sequences. Here, we used FLASH to amplify 52 candidate genes probably associated with resistance to first- and second-line drugs in the Mtb reference strain (H37Rv), then detect drug resistance mutations in cultured Mtb isolates, and in sputum samples. 92% of H37Rv reads mapped to Mtb targets, with 97.8% of target regions covered at a depth ≥ 10X. Among cultured isolates, FLASH-TB detected the same 17 drug resistance mutations as whole genome sequencing (WGS) did, but with much greater depth. Among the 16 sputum samples, FLASH-TB increased recovery of Mtb DNA compared with WGS (from 1.4% [IQR 0.5-7.5] to 33% [IQR 4.6-66.3]) and average depth reads of targets (from 6.3 [IQR 3.8-10.5] to 1991 [IQR 254.4-3623.7]). FLASH-TB identified Mtb complex in all 16 samples based on IS1081 and IS6110 copies. Drug resistance predictions for 15/16 (93.7%) clinical samples were highly concordant with phenotypic DST for isoniazid, rifampicin, amikacin, and kanamycin [15/15 (100%)], ethambutol [12/15 (80%)] and moxifloxacin [14/15 (93.3%)]. These results highlighted the potential of FLASH-TB for detecting Mtb drug resistance from sputum samples.

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New roles for RNA in mediating gene expression are being discovered at an alarming rate. A broad array of pathways control patterning of N6-methyladenosine (m6A) methylation on RNA transcripts. This review comprehensively discusses long non-coding RNAs (lncRNAs) as an additional dynamic regulator of m6A methylation, with a focus on the untranslated regions (UTRs) of mRNAs. Although there is extensive literature describing m6A modification of lncRNA, the function of lncRNA in guiding m6A writers has not been thoroughly explored. The independent control of lncRNA expression, its heterogeneous roles in RNA metabolism, and its interactions with epigenetic machinery, alludes to their potential in dynamic patterning of m6A methylation. While epigenetic regulation by histone modification of H3K36me3 has been demonstrated to pattern RNA m6A methylation, these modifications were specific to the coding and 3'UTR regions. However, there are observations that 5'UTR m6A is distinct from that of the coding and 3'UTR regions, and substantial evidence supports the active regulation of 5'UTR m6A methylation. Consequently, two potential mechanisms in patterning the UTRs m6A methylation are discussed; (1) Anti-sense lncRNA (AS-lncRNA) can either bind directly to the UTR, or (2) act indirectly via recruitment of chromatin-modifying complexes to pattern m6A. Both pathways can guide the m6A writer complex, facilitate m6A methylation and modulate protein translation. Findings in the lncRNA-histone-m6A axis could potentially contribute to the discovery of new functions of lncRNAs and clarify lncRNA-m6A findings in translational medicine.

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BACKGROUND: Guide Picker ( https://www.deskgen.com/guide-picker/ ) serves as a meta tool for designing CRISPR experiments by presenting ten different guide RNA scoring functions in one simple graphical interface. It allows investigators to simultaneously visualize and sort through every guide targeting the protein-coding regions of any mouse or human gene. RESULTS: Utilizing a multidimensional graphical display featuring two plots and four axes, Guide Picker can analyze all guides while filtering based on four different criteria at a time. Guide Picker further facilitates the CRISPR design process by using pre-computed scores for all guides, thereby offering rapid guide RNA generation and selection. CONCLUSIONS: The ease-of-use of Guide Picker complements CRISPR itself, matching a powerful and modular biological system with a flexible online web tool that can be used in a variety of genome editing experimental contexts.

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