Project description:Label-free protein sequencing is critically enabled by bottom-up, mass spectrometry-based proteomics workflows. Applications such as antibody sequencing or antigen discovery require de novo reconstruction of peptide and protein sequences. While trypsin has long served as the gold-standard protease in proteomics, its restricted C-terminal cleavage specificity constrains peptide diversity, particularly limiting coverage in antibody hypervariable complementarity-determining regions (CDRs). As a result, current workflows yield sparse reads and sequence gaps. Although multi-protease and hybrid-fragmentation strategies can notably improve coverage, they add complexity and compromise scalability and reproducibility. Here, we present a novel approach using HyperThermoacidic Archaeal (HTA) proteases Krakatoa or Vesuvius as powerful single-enzyme solutions for de novo antibody sequencing. Each protease generated over five times more unique peptide reads than trypsin or chymotrypsin with high redundancy across CDRs. Combined with EAciD fragmentation on a ZenoTOF 7600 system, this workflow enabled complete, unambiguous antibody sequencing. Despite most de novo tools being optimized for CID/HCD-tryptic data, analysis using PEAKS/DeepNovo and Stitch softwares showed that HTA-Proteases yielded up to fourfold higher alignment scores and fewer sequence mistakes across variable regions. Redundant reads increased more than threefold compared to standard proteases, boosting confidence in amino acid assignment and reducing ambiguity in final assemblies. Our alternative HTA-EAciD approach offers short digestion times, eliminates extensive cleanup, and enables analysis in a single LC-MS/MS run. This single-protease strategy delivers sequencing performance comparable to multi-enzyme workflows, providing a scalable, efficient, and highly confident approach for de novo sequencing in antibody discovery and beyond.
Project description:Genomes and transcriptomes of non-model organisms can be analyzed using next-generation sequencing technologies, but de-novo sequencing and annotating a full eukaryotic genome is still challenging. So, -omics experimentation with non-model organisms requires a suite of technologies to obtain reliable results in a cost-effective manner. Here, a novel method for microarray-based genome analysis is presented which is especially suitable for non-model organisms. We show that it is useful for complementing regular aCGH analyses and for evaluating transcriptome next-generation sequencing reads. The principle of the method is straightforward: feature intensities obtained after hybridizing the test genome are compared with the feature intensities of a control hybridization. The control hybridization is performed with negative control probes (no targets in the control sample), and with positive control probes (with targets in the control sample). The method has in principle a resolution of a single probe and it does not depend on the structural information of a reference genome: the genomic ordering of probe targets is irrelevant. In a test, analyzing the genome content of a sequenced bacterial strain: Staphylococcus aureus MRSA252, this approach proved to be successful demonstrated by receiver operating characteristic area under the curve values larger than 0.9995.
Project description:Genomes and transcriptomes of non-model organisms can be analyzed using next-generation sequencing technologies, but de-novo sequencing and annotating a full eukaryotic genome is still challenging. So, -omics experimentation with non-model organisms requires a suite of technologies to obtain reliable results in a cost-effective manner. Here, a novel method for microarray-based genome analysis is presented which is especially suitable for non-model organisms. We show that it is useful for complementing regular aCGH analyses and for evaluating transcriptome next-generation sequencing reads. The principle of the method is straightforward: feature intensities obtained after hybridizing the test genome are compared with the feature intensities of a control hybridization. The control hybridization is performed with negative control probes (no targets in the control sample), and with positive control probes (with targets in the control sample). The method has in principle a resolution of a single probe and it does not depend on the structural information of a reference genome: the genomic ordering of probe targets is irrelevant. In a test, analyzing the genome content of a sequenced bacterial strain: Staphylococcus aureus MRSA252, this approach proved to be successful demonstrated by receiver operating characteristic area under the curve values larger than 0.9995.
Project description:Genomes and transcriptomes of non-model organisms can be analyzed using next-generation sequencing technologies, but de-novo sequencing and annotating a full eukaryotic genome is still challenging. So, -omics experimentation with non-model organisms requires a suite of technologies to obtain reliable results in a cost-effective manner. Here, a novel method for microarray-based genome analysis is presented which is especially suitable for non-model organisms. We show that it is useful for complementing regular aCGH analyses and for evaluating transcriptome next-generation sequencing reads. The principle of the method is straightforward: feature intensities obtained after hybridizing the test genome are compared with the feature intensities of a control hybridization. The control hybridization is performed with negative control probes (no targets in the control sample), and with positive control probes (with targets in the control sample). The method has in principle a resolution of a single probe and it does not depend on the structural information of a reference genome: the genomic ordering of probe targets is irrelevant. In a test, analyzing the genome content of a sequenced bacterial strain: Staphylococcus aureus MRSA252, this approach proved to be successful demonstrated by receiver operating characteristic area under the curve values larger than 0.9995. DNA from eleven Staphylococcus aureus strains was extracted in three replicates, fragmented, and hybridized onto the S. aureus multistrain microarray. DNA from MRSA252 was used as common reference, but this channel was omitted in further analyses.
Project description:Genomes and transcriptomes of non-model organisms can be analyzed using next-generation sequencing technologies, but de-novo sequencing and annotating a full eukaryotic genome is still challenging. So, -omics experimentation with non-model organisms requires a suite of technologies to obtain reliable results in a cost-effective manner. Here, a novel method for microarray-based genome analysis is presented which is especially suitable for non-model organisms. We show that it is useful for complementing regular aCGH analyses and for evaluating transcriptome next-generation sequencing reads. The principle of the method is straightforward: feature intensities obtained after hybridizing the test genome are compared with the feature intensities of a control hybridization. The control hybridization is performed with negative control probes (no targets in the control sample), and with positive control probes (with targets in the control sample). The method has in principle a resolution of a single probe and it does not depend on the structural information of a reference genome: the genomic ordering of probe targets is irrelevant. In a test, analyzing the genome content of a sequenced bacterial strain: Staphylococcus aureus MRSA252, this approach proved to be successful demonstrated by receiver operating characteristic area under the curve values larger than 0.9995. DNA from twelve Danio rerio individuals was extracted, fragmented, and hybridized onto the D. rerio microarray. DNA from the pool was used as common reference, but this channel was omitted in further analyses.
Project description:Identification of patterns of sex-biased expression in (shared) vegetative tissues before and after sexual maturity in Mercurialis annua
Project description:We developed a software package STITCH (https://github.com/snijderlab/stitch) to perform template-based assembly of de novo peptide reads from antibody samples. As a test case we generated de novo peptide reads from protein G purified whole IgG from COVID-19 patients.