Deep Sequencing of HIV-1 in Cerebrospinal Fluid.

Using deep sequencing, human immunodeficiency virus (HIV) resistance-associated mutations were detected as minority species in the cerebrospinal fluid (CSF) of 4 patients with higher HIV type 1 RNA load in CSF than in plasma, but not in 2 patients with higher plasma viral load. Deep sequencing could help our understanding of viral escape in the central nervous system.

Astrovirus VA1/HMO-C: an increasingly recognized neurotropic pathogen in immunocompromised patients.

BACKGROUND: An 18-month-old boy developed encephalopathy, for which extensive investigation failed to identify an etiology, 6 weeks after stem cell transplant. To exclude a potential infectious cause, we performed high-throughput RNA sequencing on brain biopsy. METHODS: RNA-Seq was performed on an Illumina Miseq, generating 20 million paired-end reads. Nonhost data were checked for similarity to known organisms using BLASTx. The full viral genome was sequenced by primer walking. RESULTS: We identified an astrovirus, HAstV-VA1/HMO-C-UK1(a), which was highly divergent from human astrovirus (HAstV 1-8) genotypes, but closely related to VA1/HMO-C astroviruses, including one recovered from a case of fatal encephalitis in an immunosuppressed child. The virus was detected in stool and serum, with highest levels in brain and cerebrospinal fluid (CSF). Immunohistochemistry of the brain biopsy showed positive neuronal staining. A survey of 680 stool and 349 CSF samples identified a related virus in the stool of another immunosuppressed child. CONCLUSIONS: The discovery of HAstV-VA1/HMO-C-UK1(a) as the cause of encephalitis in this case provides further evidence that VA1/HMO-C viruses, unlike HAstV 1-8, are neuropathic, particularly in immunocompromised patients, and should be considered in the differential diagnosis of encephalopathy. With a turnaround from sample receipt to result of <1 week, we confirm that RNA-Seq presents a valuable diagnostic tool in unexplained encephalitis.

A high HIV-1 strain variability in London, UK, revealed by full-genome analysis: Results from the ICONIC project.

BACKGROUND & METHODS: The ICONIC project has developed an automated high-throughput pipeline to generate HIV nearly full-length genomes (NFLG, i.e. from gag to nef) from next-generation sequencing (NGS) data. The pipeline was applied to 420 HIV samples collected at University College London Hospitals NHS Trust and Barts Health NHS Trust (London) and sequenced using an Illumina MiSeq at the Wellcome Trust Sanger Institute (Cambridge). Consensus genomes were generated and subtyped using COMET, and unique recombinants were studied with jpHMM and SimPlot. Maximum-likelihood phylogenetic trees were constructed using RAxML to identify transmission networks using the Cluster Picker. RESULTS: The pipeline generated sequences of at least 1Kb of length (median = 7.46Kb, IQR = 4.01Kb) for 375 out of the 420 samples (89%), with 174 (46.4%) being NFLG. A total of 365 sequences (169 of them NFLG) corresponded to unique subjects and were included in the down-stream analyses. The most frequent HIV subtypes were B (n = 149, 40.8%) and C (n = 77, 21.1%) and the circulating recombinant form CRF02_AG (n = 32, 8.8%). We found 14 different CRFs (n = 66, 18.1%) and multiple URFs (n = 32, 8.8%) that involved recombination between 12 different subtypes/CRFs. The most frequent URFs were B/CRF01_AE (4 cases) and A1/D, B/C, and B/CRF02_AG (3 cases each). Most URFs (19/26, 73%) lacked breakpoints in the PR+RT pol region, rendering them undetectable if only that was sequenced. Twelve (37.5%) of the URFs could have emerged within the UK, whereas the rest were probably imported from sub-Saharan Africa, South East Asia and South America. For 2 URFs we found highly similar pol sequences circulating in the UK. We detected 31 phylogenetic clusters using the full dataset: 25 pairs (mostly subtypes B and C), 4 triplets and 2 quadruplets. Some of these were not consistent across different genes due to inter- and intra-subtype recombination. Clusters involved 70 sequences, 19.2% of the dataset. CONCLUSIONS: The initial analysis of genome sequences detected substantial hidden variability in the London HIV epidemic. Analysing full genome sequences, as opposed to only PR+RT, identified previously undetected recombinants. It provided a more reliable description of CRFs (that would be otherwise misclassified) and transmission clusters.