Detection of Proteome Diversity Resulted from Alternative Splicing is Limited by Trypsin Cleavage Specificity

A mass spectrometry guided approach for the identification of novel vaccine candidates in gram-negative pathogens

Vaccination is the most effective method to prevent infectious diseases. However, approaches to identify novel vaccine candidates are commonly laborious and protracted. While surface proteins are suitable vaccine candidates and can elicit antibacterial antibody responses, systematic approaches to define surfomes from gram-negatives have rarely been successful. Here we developed a combined discovery-driven mass spectrometry and computational strategy to identify bacterial vaccine candidates and validate their immunogenicity using a highly prevalent gram-negative pathogen, Helicobacter pylori, as a model organism. We efficiently isolated surface antigens by enzymatic cleavage, with a design of experiment based strategy to experimentally dissect cell surface-exposed from cytosolic proteins. From a total of 1,153 quantified bacterial proteins, we thereby identified 72 surface exposed antigens and further prioritized candidates by computational homology inference within and across species. We next tested candidate-specific immune responses. All candidates were recognized in sera from infected patients, and readily induced antibody responses after vaccination of mice. The candidate jhp_0775 induced specific B and T cell responses and significantly reduced colonization levels in mouse therapeutic vaccination studies. In infected humans, we further show that jhp_0775 is immunogenic and activates IFNγ secretion from peripheral CD4+ and CD8+ T cells. Our strategy provides a generic preclinical screening, selection and validation process for novel vaccine candidates against gram-negative bacteria, which could be employed to other gram-negative pathogens.

Deep profiling and custom databases improve detection of proteoforms generated by alternative splicing

Alternative pre-mRNA splicing has long been proposed to contribute greatly to proteome complexity. However, the extent to which mature mRNA isoforms are successfully translated into protein remains controversial. Here, we used high-throughput RNA sequencing and mass spectrometry (MS)–based proteomics to better evaluate the translation of alternatively spliced mRNAs. To increase proteome coverage and improve protein quantitation, we optimized cell fractionation and sample processing steps at both the protein and peptide level. Furthermore, we generated a custom peptide database trained on analysis of RNA-seq data with MAJIQ, an algorithm optimized to detect and quantify differential and unannotated splice junction usage. We matched tandem mass spectra acquired by data-dependent acquisition (DDA) against our custom RNA-seq based database, as well as SWISS-PROT and RefSeq databases to improve identification of splicing-derived proteoforms by 28% compared with use of the SWISS-PROT database alone. Altogether, we identified peptide evidence for 554 alternate proteoforms corresponding to 274 genes. Our increased depth and detection of proteins also allowed us to track changes in the transcriptome and proteome induced by T-cell stimulation, as well as fluctuations in protein subcellular localization. In sum, our data here confirm that use of generic databases in proteomic studies underestimates the number of spliced mRNA isoforms that are translated into protein and provides a workflow that improves isoform detection in large-scale proteomic experiments.

Combination of Proteogenomics with Peptide De Novo Sequencing Identifies New Genes and Hidden Posttranscriptional Modifications

Next-generation sequencing techniques have considerably increased the number of completely sequenced eukaryotic genomes. These genomes are mostly automatically annotated, and ab initio gene prediction is commonly combined with homology-based search approaches and often supported by transcriptomic data. The latter in particular improve the prediction of intron splice sites and untranslated regions. However, correct prediction of translation initiation sites (TIS), alternative splice junctions, and protein-coding potential remains challenging. Here, we present an advanced proteogenomics approach, namely, the combination of proteogenomics and de novo peptide sequencing analysis, in conjunction with Blast2GO and phylostratigraphy. Using the model fungus Sordaria macrospora as an example, we provide a comprehensive view of the proteome that not only increases the functional understanding of this multicellular organism at different developmental stages but also immensely enhances the genome annotation quality.

Proteogenomics combines proteomics, genomics, and transcriptomics and has considerably improved genome annotation in poorly investigated phylogenetic groups for which homology information is lacking. Furthermore, it can be advantageous when reinvestigating well-annotated genomes. Here, we applied an advanced proteogenomics approach, combining standard proteogenomics with peptide de novo sequencing, to refine annotation of the well-studied model fungus Sordaria macrospora. We investigated samples from different developmental and physiological conditions, resulting in the detection of 104 so-far hidden proteins and annotation changes in 575 genes, including 389 splice site refinements. Significantly, our approach provides peptide-level evidence for 113 single-amino-acid variations and 15 C-terminal protein elongations originating from A-to-I RNA editing, a phenomenon recently detected in fungi. Coexpression and phylostratigraphic analysis of the refined proteome suggest that new functions in evolutionarily young genes correlate with distinct developmental stages. In conclusion, our advanced proteogenomics approach supports and promotes functional studies of fungal model systems.

FusionPro, a Versatile Proteogenomic Tool for Identification of Novel Fusion Transcripts and Their Potential Translation Products in Cancer Cells

Fusion proteoforms are translation products derived from gene fusion. Although very rare, the fusion proteoforms play important roles in biomedical science. For example, fusion proteoforms influence the development of tumors by serving as cancer markers or cell cycle regulators. Although numerous studies have reported bioinformatics tools that can predict fusion transcripts, few proteogenomic tools are available that can predict and identify proteoforms. In this study, we develop a versatile proteogenomic tool "FusionPro," which facilitates the identification of fusion transcripts and their potential translatable peptides. FusionPro provides an independent gene fusion prediction module and can build sequence databases for annotated fusion proteoforms. FusionPro shows greater sensitivity than the available fusion finders when analyzing simulated or real RNA sequencing data sets. We use FusionPro to identify 18 fusion junction peptides and three potential fusion-derived peptides by MS/MS-based analysis of leukemia cell lines (Jurkat and K562) and ovarian cancer tissues from the Clinical Proteomic Tumor Analysis Consortium. Among the identified fusion proteins, we molecularly validate two fusion junction isoforms and a translation product of FAM133B:CDK6. Moreover, sequence analysis suggests that the fusion protein participates in the cell cycle progression. In addition, our prediction results indicate that fusion transcripts often have multiple fusion junctions and that these fusion junctions tend to be distributed in a nonrandom pattern at both the chromosome and gene levels. Thus, FusionPro allows users to detect various types of fusion translation products using a transcriptome-informed approach and to gain a comprehensive understanding of the formation and biological roles of fusion proteoforms.

Alternative mRNA splicing in cancer immunotherapy

Immunotherapies are yielding effective treatments for several previously untreatable cancers. Still, the identification of suitable antigens specific to the tumour that can be targets for cancer vaccines and T cell therapies is a challenge. Alternative processing of mRNA, a phenomenon that has been shown to alter the proteomic diversity of many cancers, may offer the potential of a broadened target space. Here, we discuss the promise of analysing mRNA processing events in cancer cells, with an emphasis on mRNA splicing, for the identification of potential new targets for cancer immunotherapy. Further, we highlight the challenges that must be overcome for this new avenue to have clinical applicability.

Perspective on Alternative Splicing and Proteome Complexity in Plants

Alternative splicing (AS) generates multiple transcripts from the same gene, however, AS contribution to proteome complexity remains elusive in plants. AS is prevalent under stress conditions in plants, but it is counterintuitive why plants would invest in protein synthesis under declining energy supply. We propose that plants employ AS not only to potentially increasing proteomic complexity, but also to buffer against the stress-responsive transcriptome to reduce the metabolic cost of translating all AS transcripts. To maximise efficiency under stress, plants may make fewer proteins with disordered domains via AS to diversify substrate specificity and maintain sufficient regulatory capacity. Furthermore, we suggest that chromatin state-dependent AS engenders short/long-term stress memory to mediate reproducible transcriptional response in the future.

Alternative Splicing in Apicomplexan Parasites

Alternative splicing is a widespread, essential, and complex component of gene regulation. Apicomplexan parasites have long been recognized to produce alternatively spliced transcripts for some genes and can produce multiple protein products that are essential for parasite growth.

Alternative splicing is a widespread, essential, and complex component of gene regulation. Apicomplexan parasites have long been recognized to produce alternatively spliced transcripts for some genes and can produce multiple protein products that are essential for parasite growth. Recent approaches are now providing more wide-ranging surveys of the extent of alternative splicing; some indicate that alternative splicing is less widespread than in other model eukaryotes, whereas others suggest levels comparable to those of previously studied groups. In many cases, apicomplexan alternative splicing events appear not to generate multiple alternative proteins but instead produce aberrant or noncoding transcripts. Nonetheless, appropriate regulation of alternative splicing is clearly essential in Plasmodium and Toxoplasma parasites, suggesting a biological role for at least some of the alternative splicing observed. Several studies have now disrupted conserved regulators of alternative splicing and demonstrated lethal effects in apicomplexans. This minireview discusses methods to accurately determine the extent of alternative splicing in Apicomplexa and discuss potential biological roles for this conserved process in a phylum of parasites with compact genomes.

Alternative Splicing and Protein Diversity: Plants Versus Animals

Plants, unlike animals, exhibit a very high degree of plasticity in their growth and development and employ diverse strategies to cope with the variations during diurnal cycles and stressful conditions. Plants and animals, despite their remarkable morphological and physiological differences, share many basic cellular processes and regulatory mechanisms. Alternative splicing (AS) is one such gene regulatory mechanism that modulates gene expression in multiple ways. It is now well established that AS is prevalent in all multicellular eukaryotes including plants and humans. Emerging evidence indicates that in plants, as in animals, transcription and splicing are coupled. Here, we reviewed recent evidence in support of co-transcriptional splicing in plants and highlighted similarities and differences between plants and humans. An unsettled question in the field of AS is the extent to which splice isoforms contribute to protein diversity. To take a critical look at this question, we presented a comprehensive summary of the current status of research in this area in both plants and humans, discussed limitations with the currently used approaches and suggested improvements to current methods and alternative approaches. We end with a discussion on the potential role of epigenetic modifications and chromatin state in splicing memory in plants primed with stresses.

Alternative splicing of the vitamin D receptor modulates target gene expression and promotes ligand-independent functions

Alternative splicing modulates gene function by creating splice variants with alternate functions or non-coding RNA activity. Naturally occurring variants of nuclear receptor (NR) genes with dominant negative or gain-of-function phenotypes have been documented, but their cellular roles, regulation, and responsiveness to environmental stress or disease remain unevaluated. Informed by observations that class I androgen and estrogen receptor variants display ligand-independent signaling in human cancer tissues, we questioned whether the function of class II NRs, like the vitamin D receptor (VDR), would also respond to alternative splicing regulation. Artificial VDR constructs lacking exon 3 (Dex3-VDR), encoding part of the DNA binding domain (DBD), and exon 8 (Dex8-VDR), encoding part of the ligand binding domain (LBD), were transiently transfected into DU-145 cells and stably-integrated into Caco-2 cells to study their effect on gene expression and cell viability. Changes in VDR promoter signaling were monitored by the expression of target genes (e.g. CYP24A1, CYP3A4 and CYP3A5). Ligand-independent VDR signaling was observed in variants lacking exon 8, and a significant loss of gene suppressor function was documented for variants lacking exon 3. The gain-of-function behavior of the Dex8-VDR variant was recapitulated in vitro using antisense oligonucleotides (ASO) that induce the skipping of exon 8 in wild-type VDR. ASO targeting the splice acceptor site of exon 8 significantly stimulated ligand-independent VDR reporter activity and the induction of CYP24A1 above controls. These results demonstrate how alternative splicing can re-program NR gene function, highlighting novel mechanisms of toxicity and new opportunities for the use of splice-switching oligonucleotides (SSO) in precision medicine.

A new approach for quantitative characterization of hydrolytic action of proteases to elastin in leather manufacturing

Leather biotechnology based on enzyme is one of the main directions toward clean technology in the leather manufacturing process. Proteins such as collagen, elastin, and keratin are important components in animal hides or skins, and proteases are most frequently used in the leather manufacturing process for the removal of interfibrillar substance and opening-up of collagen fiber instead of toxic chemicals. Elastin is an important and highly elastic structural protein in the animal hides or skins and significantly affects the properties of the final leather product. For improving the quality of leather product, thorough understanding of the mechanism of action of proteases on elastin is necessary. The action of proteases on elastin has been mostly studied either qualitatively by histological analysis or quantitatively based on substrate casein or stained substrates, such as congo red-elastin and Remazol Brilliant Blue R-elastin; however, the resulting products have not been accurately characterized and thus these methods are not up to the standard. Besides, controlling the hydrolytic action of proteases to elastin has been very difficult, and excessive hydrolytic action of protease damages the elastin, restricting the wide application of proteases in the leather manufacturing process. In order to quantitatively evaluate the hydrolytic action of proteases on elastin in a more accurate manner, in this study, a new method was established by determining the unique amino acid desmosine based on the covalently bonded elastin-desmosine conjugate. Quantitative analysis of desmosine was performed in liquor based on cowhides substrate, and qualitative characterization was accomplished by histological analysis of elastic fiber in hides using an optical microscope. The results of this study indicated that the newly developed method is sensitive, accurate, and reproducible. In addition, the unhairing trials also demonstrated the suitability of newly established method in the leather manufacturing process to evaluate the action of proteases on the elastin in animal hides or skins.

ProteomeGenerator: A Framework for Comprehensive Proteomics Based on de Novo Transcriptome Assembly and High-Accuracy Peptide Mass Spectral Matching

Modern mass spectrometry now permits genome-scale and quantitative measurements of biological proteomes. However, analysis of specific specimens is currently hindered by the incomplete representation of biological variability of protein sequences in canonical reference proteomes and the technical demands for their construction. Here, we report ProteomeGenerator, a framework for de novo and reference-assisted proteogenomic database construction and analysis based on sample-specific transcriptome sequencing and high-accuracy mass spectrometry proteomics. This enables the assembly of proteomes encoded by actively transcribed genes, including sample-specific protein isoforms resulting from non-canonical mRNA transcription, splicing, or editing. To improve the accuracy of protein isoform identification in non-canonical proteomes, ProteomeGenerator relies on statistical target-decoy database matching calibrated using sample-specific controls. Its current implementation includes automatic integration with MaxQuant mass spectrometry proteomics algorithms. We applied this method for the proteogenomic analysis of splicing factor SRSF2 mutant leukemia cells, demonstrating high-confidence identification of non-canonical protein isoforms arising from alternative transcriptional start sites, intron retention, and cryptic exon splicing as well as improved accuracy of genome-scale proteome discovery. Additionally, we report proteogenomic performance metrics for current state-of-the-art implementations of SEQUEST HT, MaxQuant, Byonic, and PEAKS mass spectral analysis algorithms. Finally, ProteomeGenerator is implemented as a Snakemake workflow within a Singularity container for one-step installation in diverse computing environments, thereby enabling open, scalable, and facile discovery of sample-specific, non-canonical, and neomorphic biological proteomes.

ASV-ID, a Proteogenomic Workflow To Predict Candidate Protein Isoforms on the Basis of Transcript Evidence

One of the goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to map and characterize the functions of protein isoforms produced by alternative splicing of genes. However, identifying alternative splice variants (ASVs) via mass spectrometry remains a major challenge, because ASVs usually contain highly homologous peptide sequences. A routine protein sequence analysis suggests that more than half of the investigated proteins do not generate two or more uniquely mapping peptides that would enable their isoforms to be distinguished. Here, we develop a new proteogenomics method, named "ASV-ID" (alternative splicing variants identification), which enables identification of ASVs by using a cell type-specific protein sequence database that is supported by RNA-Seq data. Using this workflow, we identify 1935 distinct proteins under highly stringent conditions. In fact, transcript evidence on these 841 proteins helps us distinguish them from other isoforms, despite the fact that these proteins are not predicted to make 2 or more uniquely mapping peptides. We also demonstrate that ASV-ID enables detection of 19 differently expressed isoforms present in several cell lines. Thus, a new workflow using ASV-ID has the potential to map yet-to-be-identified difficult protein isoforms in a simple and robust way.

Deep proteomic network analysis of Alzheimer's disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease

BACKGROUND

The complicated cellular and biochemical changes that occur in brain during Alzheimer's disease are poorly understood. In a previous study we used an unbiased label-free quantitative mass spectrometry-based proteomic approach to analyze these changes at a systems level in post-mortem cortical tissue from patients with Alzheimer's disease (AD), asymptomatic Alzheimer's disease (AsymAD), and controls. We found modules of co-expressed proteins that correlated with AD phenotypes, some of which were enriched in proteins identified as risk factors for AD by genetic studies.

METHODS

The amount of information that can be obtained from such systems-level proteomic analyses is critically dependent upon the number of proteins that can be quantified across a cohort. We report here a new proteomic systems-level analysis of AD brain based on 6,533 proteins measured across AD, AsymAD, and controls using an analysis pipeline consisting of isobaric tandem mass tag (TMT) mass spectrometry and offline prefractionation.

RESULTS

Our new TMT pipeline allowed us to more than double the depth of brain proteome coverage. This increased depth of coverage greatly expanded the brain protein network to reveal new protein modules that correlated with disease and were unrelated to those identified in our previous network. Differential protein abundance analysis identified 350 proteins that had altered levels between AsymAD and AD not caused by changes in specific cell type abundance, potentially reflecting biochemical changes that are associated with cognitive decline in AD. RNA binding proteins emerged as a class of proteins altered between AsymAD and AD, and were enriched in network modules that correlated with AD pathology. We developed a proteogenomic approach to investigate RNA splicing events that may be altered by RNA binding protein changes in AD. The increased proteome depth afforded by our TMT pipeline allowed us to identify and quantify a large number of alternatively spliced protein isoforms in brain, including AD risk factors such as BIN1, PICALM, PTK2B, and FERMT2. Many of the new AD protein network modules were enriched in alternatively spliced proteins and correlated with molecular markers of AD pathology and cognition.

CONCLUSIONS

Further analysis of the AD brain proteome will continue to yield new insights into the biological basis of AD.

Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients

Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects alternative splicing events and tumor variants by reanalyzing RNA and whole-exome sequencing data. Tumors have up to 30% more alternative splicing events than normal samples. Association analysis of somatic variants with alternative splicing events confirmed known trans associations with variants in SF3B1 and U2AF1 and identified additional trans-acting variants (e.g., TADA1, PPP2R1A). Many tumors have thousands of alternative splicing events not detectable in normal samples; on average, we identified ≈930 exon-exon junctions ("neojunctions") in tumors not typically found in GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast and ovarian tumor samples, we confirmed ≈1.7 neojunction- and ≈0.6 single nucleotide variant-derived peptides per tumor sample that are also predicted major histocompatibility complex-I binders ("putative neoantigens").

Cancer-Specific Splicing Changes and the Potential for Splicing-Derived Neoantigens

In this issue of Cancer Cell, Kahles et al. perform a comprehensive analysis of RNA splicing across cancer types and identify novel correlations between genetic alterations and splicing in cancer. In addition, they identify that tumor-specific splicing has the potential to generate a large new class of tumor-specific neoantigens.

gpGrouper: A Peptide Grouping Algorithm for Gene-Centric Inference and Quantitation of Bottom-Up Proteomics Data

In quantitative mass spectrometry, the method by which peptides are grouped into proteins can have dramatic effects on downstream analyses. Here we describe gpGrouper, an inference and quantitation algorithm that offers an alternative method for assignment of protein groups by gene locus and improves pseudo-absolute iBAQ quantitation by weighted distribution of shared peptide areas. We experimentally show that distributing shared peptide quantities based on unique peptide peak ratios improves quantitation accuracy compared with conventional winner-take-all scenarios. Furthermore, gpGrouper seamlessly handles two-species samples such as patient-derived xenografts (PDXs) without ignoring the host species or species-shared peptides. This is a critical capability for proper evaluation of proteomics data from PDX samples, where stromal infiltration varies across individual tumors. Finally, gpGrouper calculates peptide peak area (MS1) based expression estimates from multiplexed isobaric data, producing iBAQ results that are directly comparable across label-free, isotopic, and isobaric proteomics approaches.