Biology subjects

Butler, A.

Publications and source records attributed to Butler, A..

5 recordsLinked to original sources

bioRxiv2018

Analysis of HIV-1 latent reservoir and rebound viruses in a clinical trial of anti-HIV-1 antibody 3BNC117

A clinical trial was performed to evaluate 3BNC117, a potent anti_HIV_1 antibody, in infected individuals during suppressive antiretroviral therapy (ART) and subsequent analytical treatment interruption (ATI). The circulating reservoir was evaluated by quantitative and qualitative outgrowth assay (Q2VOA) at entry and after 6 months, prior to ATI. Although there were no significant quantitative changes in the size of the reservoir, the composition of circulating reservoir clones varied over the 6_month period before treatment interruption in a manner that did not correlate with antibody sensitivity. The neutralization profile obtained from the reservoir by Q2VOA was predictive of time to rebound after ATI, and thus of antibody efficacy. Although 3BNC117 binding site amino acid variants found in rebound viruses pre_existed in the latent reservoir, only 3 of 217 rebound viruses were identical to 868 latent viruses. Instead many of the rebound viruses appeared to be recombinants, even in individuals with resistant reservoir viruses. By incorporating the possibility of recombination, 63% of the rebound viruses could have derived from the observed latent reservoir. In conclusion, viruses emerging during ATI in individuals treated with 3BNC117 are not the dominant species found in the circulating reservoir, but instead appear to represent recombinants.\n\nSummaryIn the setting of a clinical trial evaluating the anti_HIV_1 antibody 3BNC117, Cohen et al. demonstrate that rebound viruses that emerge following interruption of antiretroviral therapy are distinct from circulating latent viruses. However, rebound viruses often appear to be recombinants between isolated latent viruses.

clinical trials↗

bioRxiv2018

Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation

Global loss of DNA methylation and CpG island (CGI) hypermethylation are regarded as key epigenomic aberrations in cancer. Global loss manifests itself in partially methylated domains (PMDs) which can extend up to megabases. However, the distribution of PMDs within and between tumor types, and their effects on key functional genomic elements including CGIs are poorly defined. Using whole genome bisulfite sequencing (WGBS) of breast cancers, we comprehensively show that loss of methylation in PMDs occurs in a large fraction of the genome and represents the prime source of variation in DNA methylation. PMDs are hypervariable in methylation level, size and distribution, and display elevated mutation rates. They impose intermediate DNA methylation levels incognizant of functional genomic elements including CGIs, underpinning a CGI methylator phenotype (CIMP). However, significant repression effects on cancer-genes are negligible as tumor suppressor genes are generally excluded from PMDs. The genomic distribution of PMDs reports tissue-of-origin of different cancers and may represent tissue-specific silent regions of the genome, which tolerate instability at the epigenetic, transcriptomic and genetic level.

cancer biology↗

bioRxiv2017

Pan-cancer analysis of whole genomes reveals driver rearrangements promoted by LINE-1 retrotransposition in human tumours

About half of all cancers have somatic integrations of retrotransposons. To characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 37 histological cancer subtypes. We identified 19,166 somatically acquired retrotransposition events, affecting 35% of samples, and spanning a range of event types. L1 insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, sometimes removing tumour suppressor genes, as well as inducing complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications in the development of human tumours.

genomics↗

bioRxiv2017

Integrated analysis of single cell transcriptomic data across conditions, technologies, and species

Single cell RNA-seq (scRNA-seq) has emerged as a transformative tool to discover and define cellular phenotypes. While computational scRNA-seq methods are currently well suited for experiments representing a single condition, technology, or species, analyzing multiple datasets simultaneously raises new challenges. In particular, traditional analytical workflows struggle to align subpopulations that are present across datasets, limiting the possibility for integrated or comparative analysis. Here, we introduce a new computational strategy for scRNA-seq alignment, utilizing common sources of variation to identify shared subpopulations between datasets as part of our R toolkit Seurat. We demonstrate our approach by aligning scRNA-seq datasets of PBMCs under resting and stimulated conditions, hematopoietic progenitors sequenced across two profiling technologies, and pancreatic cell atlases generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across datasets, and can identify subpopulations that could not be detected by analyzing datasets independently. We anticipate that these methods will serve not only to correct for batch or technology-dependent effects, but also to facilitate general comparisons of scRNA-seq datasets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.\n\nAvailabilityInstallation instructions, documentation, and tutorials are available at http://www.satijalab.org/seurat

genomics↗

bioRxiv2017

Single-Cell RNA-Seq Of Rheumatoid Arthritis Synovial Tissue Using Low Cost Microfluidic Instrumentation

Droplet-based single cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $540. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single cell transcriptome profiling of disaggregated synovial tissue from a rheumatoid arthritis patient. We sequenced 8,716 single cells from a synovectomy, revealing 16 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.

genomics↗