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Streamlined analysis schema for high-throughput identification of endogenous protein complexes.

ABSTRACT: Immunoprecipitation followed by mass spectrometry (IP/MS) has recently emerged as a preferred method in the analysis of protein complex components and cellular protein networks. Targeting endogenous protein complexes of higher eukaryotes, particularly in large-scale efforts, has been challenging due to cellular heterogeneity, high proteome complexity, and, compared to lower organisms, lack of efficient in-locus epitope-tagging techniques. It is further complicated by variability in nonspecific identifications and cross-reactivity of primary antibodies. Still, the study of endogenous human protein networks is highly desired despite its challenges. Here we describe a streamlined IP/MS protocol for the purification and identification of extended endogenous protein complexes. We investigate the sources of nonspecific protein binding and develop semiquantitative specificity filters that are based on peptide spectral count measurements. We also outline logical constraints for the derivation of accurate complex composition from IP/MS data and demonstrate the effectiveness of this approach by presenting our analyses of different transcriptional coregulator complexes. We show consistent purification of novel components for the Integrator complex, analyze the composition of the Mediator complex solely from our data to demonstrate the wide usability of spectral counts, and deconvolute heterogeneous HDAC1/2 networks into core complex modules and several novel subcomplex interactions.

SUBMITTER: Malovannaya A

PROVIDER: S-EPMC2823922 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:High-throughput sequencing (HTS) has been widely used to characterize HIV-1 genome sequences. There are no algorithms currently that can directly determine genotype and quasispecies population using short HTS reads generated from long genome sequences without additional software. To establish a robust subpopulation, subtype, and recombination analysis workflow, we amplified the HIV-1 3'-half genome from plasma samples of 65 HIV-1-infected individuals and sequenced the entire amplicon (∼4,500 bp) by HTS. With direct analysis of raw reads using HIVE-hexahedron, we showed that 48% of samples harbored 2 to 13 subpopulations. We identified various subtypes (17 A1s, 4 Bs, 27 Cs, 6 CRF02_AGs, and 11 unique recombinant forms) and defined recombinant breakpoints of 10 recombinants. These results were validated with viral genome sequences generated by single genome sequencing (SGS) or the analysis of consensus sequence of the HTS reads. The HIVE-hexahedron workflow is more sensitive and accurate than just evaluating the consensus sequence and also more cost-effective than SGS.IMPORTANCE The highly recombinogenic nature of human immunodeficiency virus type 1 (HIV-1) leads to recombination and emergence of quasispecies. It is important to reliably identify subpopulations to understand the complexity of a viral population for drug resistance surveillance and vaccine development. High-throughput sequencing (HTS) provides improved resolution over Sanger sequencing for the analysis of heterogeneous viral subpopulations. However, current methods of analysis of HTS reads are unable to fully address accurate population reconstruction. Hence, there is a dire need for a more sensitive, accurate, user-friendly, and cost-effective method to analyze viral quasispecies. For this purpose, we have improved the HIVE-hexahedron algorithm that we previously developed with in silico short sequences to analyze raw HTS short reads. The significance of this study is that our standalone algorithm enables a streamlined analysis of quasispecies, subtype, and recombination patterns from long HIV-1 genome regions without the need of additional sequence analysis tools. Distinct viral populations and recombination patterns identified by HIVE-hexahedron are further validated by comparison with sequences obtained by single genome sequencing (SGS).

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Streamlined analysis schema for high-throughput identification of endogenous protein complexes.

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