Hypoxia-induced proliferation of human pulmonary microvascular endothelial cells depends on epidermal growth factor receptor tyrosine kinase activation

We hypothesized that hypoxia would activate epidermal growth factor receptor (EGFR) tyrosine kinase, leading to increased arginase expression and resulting in proliferation of human pulmonary microvascular endothelial cell (hPMVEC). To test this hypothesis, hPMVEC were incubated in normoxia (20% O2, 5% CO2) or hypoxia (1% O2, 5% CO2). Immunoblotting for EGFR and proliferating cell nuclear antigen was done, and protein levels of both total EGFR and proliferating cell nuclear antigen were greater in hypoxic hPMVEC than in normoxic hPMVEC. Furthermore, hypoxic hPMVEC had greater levels of EGFR activity than did normoxic hPMVEC. Hypoxic hPMVEC had a twofold greater level of proliferation compared with normoxic controls, and this increase in proliferation was prevented by the addition of AG-1478 (a pharmacological inhibitor of EGFR). Immunoblotting for arginase I and arginase II demonstrated a threefold induction in arginase II protein levels in hypoxia, with little change in arginase I protein levels. The hypoxic induction of arginase II protein was prevented by treatment with AG-1478. Proliferation assays were performed in the presence of arginase inhibitors, and hypoxia-induced proliferation was also prevented by arginase inhibition. Finally, treatment with an EGFR small interfering RNA prevented hypoxia-induced proliferation and urea production. These findings demonstrate that hypoxia activates EGFR tyrosine kinase, leading to arginase expression and thereby promoting proliferation in hPMVEC

VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data

Abstract Background Pre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files. Results Processing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5′ and 3′ PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires <10% of the run time required by pRESTO. Conclusions VDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets

VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data

BackgroundPre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files.ResultsProcessing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5' and 3' PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires &lt;10% of the run time required by pRESTO.ConclusionsVDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets

VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements

BackgroundThe genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D)J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D)J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D)J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D)J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses.ResultsTo help address this problem, we propose a standardized file format for representing V(D)J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D)J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format.ConclusionsThe VDJML suite will allow users to streamline their V(D)J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https://vdjserver.org/vdjml/ . We welcome participation from the community in developing the file format standard, as well as code contributions

VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements

Background: The genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D) J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D) J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D) J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D) J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses. Results: To help address this problem, we propose a standardized file format for representing V(D) J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D) J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format. Conclusions: The VDJML suite will allow users to streamline their V(D) J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https:// vdjserver. org/ vdjml/. We welcome participation from the community in developing the file format standard, as well as code contributions.Burroughs Welcome Fund Career Award; NIAID [AI097403]; Bioinformatics Support Contract (BISC) [HHSN272201200028C]; National Institute of Allergy and Infectious Diseases grant [U19 AI090019, R01 AI104739]; PhRMA foundation pre-doctoral informatics fellowship; National Library of Medicine of the National Institutes of Health [T15 LM07056]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]