Direct-acting antiviral agents (DAAs) against hepatitis C virus (HCV) proteins open a whole new era for anti-HCV therapy, but DAA resistance associated variants (RAVs) could jeopardize the effectiveness of DAAs. We reported the global prevalence of DAA RAVs using published GenBank data. 58.7% of sequences (854/1455) harbored at least one dominant resistance variant and the highest RAV frequency occurred in Asia (74.1%), followed by Africa (71.9%), America (53.5%) and Europe (51.4%). The highest RAV frequency was observed in genotype (GT) 6 sequences (99%), followed by GT2 (87.9%), GT4 (85.5%), GT1a (56%), GT3 (50.0%) and GT1b (34.3%). Furthermore, 40.0% and 29.6% of sequences were detected RAVs of non-structural (NS) 5A inhibitors and NS3 protease inhibitors, respectively. However, RAVs to NS5B nucleo(t)ide inhibitor (NI) and NI-based combinations were uncommon (<4% of sequences). As expected, combinations of multiple RAVs to the IFN-free regimens recommended by current guidelines were rarely detected (0.2%–2.0%). Our results showed that the overall global prevalence of DAA RAVs was high irrespective of geography or genotype. However, the NI-based multi-DAA regimens had a low RAV prevalence, suggesting that these regimens are the most promising strategies for cure of the long-term HCV infection.

The growing number of microbial reference genomes enables the improvement of metagenomic profiling accuracy but also imposes greater requirements on the indexing efficiency, database size and runtime of taxonomic profilers. Additionally, most profilers focus mainly on bacterial, archaeal and fungal populations, while less attention is paid to viral communities. We present KMCP (K-mer-based Metagenomic Classification and Profiling), a novel k-mer-based metagenomic profiling tool that utilizes genome coverage information by splitting the reference genomes into chunks and stores k-mers in a modified and optimized Compact Bit-Sliced Signature Index for fast alignment-free sequence searching. KMCP combines k-mer similarity and genome coverage information to reduce the false positive rate of k-mer-based taxonomic classification and profiling methods. Benchmarking results based on simulated and real data demonstrate that KMCP, despite a longer running time than all other methods, not only allows the accurate taxonomic profiling of prokaryotic and viral populations but also provides more confident pathogen detection in clinical samples of low depth. The software is open-source under the MIT license and available at https://github.com/shenwei356/kmcp. Supplementary data are available at Bioinformatics online.

To estimate the diagnostic accuracy of Xpert MTB/RIF, a systematic review and meta-analysis were carried out. Up to June 20, 2015, multiple databases were screened for relevant studies. Accordingly, 106 studies included 52,410 samples were selected. Diagnostic accuracy of Xpert MTB/RIF for TB detection was validated against either culture or a composite reference standard (CRS). Additionally, selected studies were further subgrouped in four groups based on sample’s type, subject’s age, status of HIV co-infection and smear-positivity. The overall pooled sensitivity and specificity of Xpert MTB/RIF was 0.85 (95% confidence interval [CI] 0.82–0.88) and 0.98 (95% CI 0.96–0.98), respectively, compared to culture; while it was 0.59 (95% CI 0.44–0.72) and 0.99 (95% CI 0.97–1.00) compared to CRS. The overall sensitivity was lower in countries with high TB prevalence than countries with middle/low prevalence (0.84, 95% CI: 0.80–0.88 versus 0.89, 95% CI: 0.84–0.93). Furthermore, Xpert MTB/RIF has higher sensitivity in patients with positive smears (0.99, 95% CI 0.97–0.99), in patients with pulmonary TB samples (0.87, 95% CI 0.83–0.90), in adults (0.82, 95% CI 0.76–0.86) and in HIV-positive patients (0.81, 95% CI 0.73–0.87). Taken together, Xpert MTB/RIF is a quick and accurate diagnostic assay for TB which will significantly help the physicians to make their clinical decisions.