Benchmarking the Orbitrap Tribrid Eclipse for Next Generation Multiplexed Proteomics.
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ABSTRACT:
SUBMITTER: Yu Q
PROVIDER: S-EPMC7295122 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The rise of sample multiplexing in quantitative proteomics for the dissection of complex phenotypic comparisons has been advanced by the development of ever more sensitive and robust instrumentation. Here, we evaluated the utility of the Orbitrap Eclipse Tribrid mass spectrometer (advanced quadrupole filter, optimized FTMS scan overhead) and new instrument control software features (Precursor Fit filtering, TurboTMT and Real-time Peptide Search filtering). Multidimensional comparisons of these novel features increased total peptide identifications by 20% for SPS-MS3 methods and 14% for HRMS2 methods. Importantly Real-time Peptide Search filtering enabled a ~2X throughput improvement for quantification. Across the board, these sensitivity increases were attained without sacrificing quantitative accuracy. New hardware and software features enable more efficient characterization in pursuit of comparative whole proteome insights.
2022-01-07 | PXD016766 | Pride
Project description:MotivationOver the last decades, vast numbers of sequences were deposited in public databases. Bioinformatics tools allow homology and consequently functional inference for these sequences. New profile-based homology search tools have been introduced, allowing reliable detection of remote homologs, but have not been systematically benchmarked. To provide such a comparison, which can guide bioinformatics workflows, we extend and apply our previously developed benchmark approach to evaluate the 'next generation' of profile-based approaches, including CS-BLAST, HHSEARCH and PHMMER, in comparison with the non-profile based search tools NCBI-BLAST, USEARCH, UBLAST and FASTA.MethodWe generated challenging benchmark datasets based on protein domain architectures within either the PFAM + Clan, SCOP/Superfamily or CATH/Gene3D domain definition schemes. From each dataset, homologous and non-homologous protein pairs were aligned using each tool, and standard performance metrics calculated. We further measured congruence of domain architecture assignments in the three domain databases.ResultsCSBLAST and PHMMER had overall highest accuracy. FASTA, UBLAST and USEARCH showed large trade-offs of accuracy for speed optimization.ConclusionProfile methods are superior at inferring remote homologs but the difference in accuracy between methods is relatively small. PHMMER and CSBLAST stand out with the highest accuracy, yet still at a reasonable computational cost. Additionally, we show that less than 0.1% of Swiss-Prot protein pairs considered homologous by one database are considered non-homologous by another, implying that these classifications represent equivalent underlying biological phenomena, differing mostly in coverage and granularity.Availability and implementationBenchmark datasets and all scripts are placed at (http://sonnhammer.org/download/Homology_benchmark).Contactforslund@embl.deSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5013910 | biostudies-literature
Project description:BackgroundRecent advancements in next-generation sequencing have rapidly improved our ability to study genomic material at an unprecedented scale. Despite substantial improvements in sequencing technologies, errors present in the data still risk confounding downstream analysis and limiting the applicability of sequencing technologies in clinical tools. Computational error correction promises to eliminate sequencing errors, but the relative accuracy of error correction algorithms remains unknown.ResultsIn this paper, we evaluate the ability of error correction algorithms to fix errors across different types of datasets that contain various levels of heterogeneity. We highlight the advantages and limitations of computational error correction techniques across different domains of biology, including immunogenomics and virology. To demonstrate the efficacy of our technique, we apply the UMI-based high-fidelity sequencing protocol to eliminate sequencing errors from both simulated data and the raw reads. We then perform a realistic evaluation of error-correction methods.ConclusionsIn terms of accuracy, we find that method performance varies substantially across different types of datasets with no single method performing best on all types of examined data. Finally, we also identify the techniques that offer a good balance between precision and sensitivity.
| S-EPMC7079412 | biostudies-literature
Project description:With the advent of next generation sequencing (NGS) technologies, single nucleotide polymorphisms (SNPs) have become the major type of marker for genotyping in many crops. However, the availability of SNP markers for important traits of bread wheat (Triticum aestivum L.) that can be effectively used in marker-assisted selection (MAS) is still limited and SNP assays for MAS are usually uniplex. A shift from uniplex to multiplex assays will allow the simultaneous analysis of multiple markers and increase MAS efficiency. We designed 33 locus-specific markers from SNP or indel-based marker sequences that linked to 20 different quantitative trait loci (QTL) or genes of agronomic importance in wheat and analyzed the amplicon sequences using an Ion Torrent Proton Sequencer and a custom allele detection pipeline to determine the genotypes of 24 selected germplasm accessions. Among the 33 markers, 27 were successfully multiplexed and 23 had 100% SNP call rates. Results from analysis of "kompetitive allele-specific PCR" (KASP) and sequence tagged site (STS) markers developed from the same loci fully verified the genotype calls of 23 markers. The NGS-based multiplexed assay developed in this study is suitable for rapid and high-throughput screening of SNPs and some indel-based markers in wheat.
| S-EPMC4666610 | biostudies-literature
Project description:Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain "live" (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines' implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
| S-EPMC9243550 | biostudies-literature
Project description:Host-pathogen interactions are pivotal in regulating establishment, progression, and outcome of an infection. While affinity-purification mass spectrometry has become instrumental in characterizing such interactions, it suffers from limitations in scalability and biological authenticity. Here we present the use of co-fractionation mass spectrometry for high throughput analysis of host-pathogen interactions from native viral infections of two jumbophages (ϕKZ and ϕPA3) in Pseudomonas aeruginosa. This approach enabled the detection of > 6000 unique host-pathogen interactions for each phage, encompassing > 50% of their respective proteomes. This deep coverage provided evidence for interactions between KZ-like phage proteins and the host ribosome, and revealed protein complexes for previously undescribed phage ORFs, including a ϕPA3 complex showing strong structural and sequence similarity to ϕKZ non-virion RNA polymerase. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of host-pathogen interactomes and protein complex dynamics upon infection.
| S-EPMC10449902 | biostudies-literature
Project description:A new instrument configuration for native ion mobility-mass spectrometry (IM-MS) is described. Macromolecule ions are generated by using a static ESI source coupled to an RF ion funnel, and these ions are then mobility and mass analyzed using a periodic focusing drift tube IM analyzer and an Orbitrap mass spectrometer. The instrument design retains the capabilities for first-principles determination of rotationally averaged ion-neutral collision cross sections and high-resolution measurements in both mobility and mass analysis modes for intact protein complexes. Operation in the IM mode utilizes FT-IMS modes (originally described by Knorr ( Knorr , F. J. Anal. Chem . 1985 , 57 ( 2 ), 402 - 406 )), which provides a means to overcome the inherent duty cycle mismatch for drift tube (DT)-IM and Orbitrap mass analysis. The performance of the native ESI-FT-DT-IM-Orbitrap MS instrument was evaluated using the protein complexes Gln K (MW 44 kDa) and streptavidin (MW 53 kDa) bound to small molecules (ADP and biotin, respectively) and transthyretin (MW 56 kDa) bound to thyroxine and zinc.
| S-EPMC6464636 | biostudies-literature
Project description:BACKGROUND: Compared to classical genotyping, targeted next-generation sequencing (tNGS) can be custom-designed to interrogate entire genomic regions of interest, in order to detect novel as well as known variants. To bring down the per-sample cost, one approach is to pool barcoded NGS libraries before sample enrichment. Still, we lack a complete understanding of how this multiplexed tNGS approach and the varying performance of the ever-evolving analytical tools can affect the quality of variant discovery. Therefore, we evaluated the impact of different software tools and analytical approaches on the discovery of single nucleotide polymorphisms (SNPs) in multiplexed tNGS data. To generate our own test model, we combined a sequence capture method with NGS in three experimental stages of increasing complexity (E. coli genes, multiplexed E. coli, and multiplexed HapMap BRCA1/2 regions). RESULTS: We successfully enriched barcoded NGS libraries instead of genomic DNA, achieving reproducible coverage profiles (Pearson correlation coefficients of up to 0.99) across multiplexed samples, with <10% strand bias. However, the SNP calling quality was substantially affected by the choice of tools and mapping strategy. With the aim of reducing computational requirements, we compared conventional whole-genome mapping and SNP-calling with a new faster approach: target-region mapping with subsequent 'read-backmapping' to the whole genome to reduce the false detection rate. Consequently, we developed a combined mapping pipeline, which includes standard tools (BWA, SAMtools, etc.), and tested it on public HiSeq2000 exome data from the 1000 Genomes Project. Our pipeline saved 12 hours of run time per Hiseq2000 exome sample and detected ~5% more SNPs than the conventional whole genome approach. This suggests that more potential novel SNPs may be discovered using both approaches than with just the conventional approach. CONCLUSIONS: We recommend applying our general 'two-step' mapping approach for more efficient SNP discovery in tNGS. Our study has also shown the benefit of computing inter-sample SNP-concordances and inspecting read alignments in order to attain more confident results.
| S-EPMC3563481 | biostudies-literature
Project description:Selenium (Se) functions as a cellular redox gatekeeper through its incorporation into proteins as the 21st amino acid, selenocysteine (Sec). Supplementation of macrophages with exogenous Se (as sodium selenite) downregulates inflammation and intracellular oxidative stress by effectively restoring redox homeostasis upon challenge with bacterial endotoxin lipopolysaccharide (LPS). Here, we examined the use of a standard Tandem Mass Tag (TMT)-labeling mass spectrometry-based proteomic workflow to quantitate and examine temporal regulation of selenoproteins in such inflamed cells. Se-deficient murine primary bone marrow-derived macrophages (BMDMs) exposed to LPS in the presence or absence of selenite treatment for various time periods (0-20 h) were used to analyze the selenoproteome expression using isobaric labeling and shotgun proteomic workflow. To overcome the challenge of identification of Sec peptides, we used the identification of non-Sec containing peptides downstream of Sec as a reliable evidence of ribosome readthrough indicating efficient decoding of Sec codon. Results indicated a temporal regulation of the selenoproteome with a general increase in their expression in inflamed cells in a Se-dependent manner. Selenow, Gpx1, Msrb1, and Selenom were highly upregulated upon stimulation with LPS when compared to other selenoproteins. Interestingly, Selenow appeared to be one amongst the highly regulated selenoproteins in macrophages that was previously thought to be mainly restricted to myocytes. Collectively, TMT-labeling method of non-Sec peptides offers a reliable method to quantitate and study temporal regulation of selenoproteins; however, further optimization to include Sec-peptides could make this strategy more robust and sensitive compared to other semi-quantitative or qualitative methods. Graphical Abstract.
| S-EPMC6592718 | biostudies-literature
Project description:BackgroundNext-generation sequencing (NGS) has enabled efficient high-resolution typing of human leukocyte antigen (HLA) genes with minimal ambiguity. Most commercially available assays amplify individual or subgroup of HLA genes by long-range PCR followed by library preparation and sequencing. The AllType assay simplifies the workflow by amplifying 11 transplant-relevant HLA genes in one PCR reaction. Here, we report the performance of this unique workflow evaluated using 218 genetically diverse samples.MethodsFive whole genes (HLA-A/B/C/DQA1/DPA1) and six near-whole genes (HLA-DRB1/DRB345/DQB1/DPB1; excluding exon 1 and part of intron 1) were amplified in a multiplexed, long-range PCR. Manual library preparation was performed per manufacturer's protocol, followed by template preparation and chip loading on the Ion Chef, and sequencing on the Ion S5 sequencer. Pre-specified rules for quality control and repeat testing were followed; technologists were blinded to the reference results. The concordance between AllType and reference results was determined at 2-field resolution. We also describe the ranges of input DNA and library concentrations, read number per sample and per locus, and key health metrics in relation to typing results.ResultsThe concordance rates were 98.6%, 99.8% and 99.9% at the sample (n = 218), genotype (n = 1688), and allele (n = 3376) levels, respectively. Three genotypes were discordant, all of which shared the same G group typing results with the reference. Most ambiguous genotypes (116 out of 144, 80.6%) were due to the lack of exon 1 and intron 1 coverage for HLA-DRB1/DRB345/DQB1/DPB1 genes. A broad range of input DNA concentrations and library concentrations were tolerated. Per sample read numbers were adequate for accurate genotyping. Per locus read numbers showed some inter-lot variations, and a trend toward improved inter-locus balance was observed with later lots of reagents.ConclusionThe AllType assay on the Ion Chef/Ion S5 platform offers a robust and efficient workflow for clinical HLA typing at the 2-field resolution. The multiplex PCR strategy simplifies the laboratory procedure without compromising the typing accuracy.
| S-EPMC7179861 | biostudies-literature